Nuclear SafetyNEA/CSNI/R(2017)2/ADD1July 2017www.oecd-nea.org

Fatigue of Nuclear Reactor Components

Proceedings of the 4th International Conference28 September-1 October 2015Seville, Spain

Appendix 4

OECD/NEA CSNI WGIAGE; Fourth International Conference on Fatigue of Nuclear Reactor Components

28th September-1st October, 2015, Sevilla, Spain

Fatigue Evaluation of Nuclear Plant Components with Environmental Effects

David Fernández de Rucoba1 1Fundación Centro Tecnológico de Componentes (CTC), Spain, info@ctcomponentes.com

Román Cicero González, Roberto Báscones Vega1, Iñaki Gorrochategui Sánchez, Víctor Gómez

Fernández2, Raúl Muñoz Roldán2, Enrique Gómez Poncela2. 2Equipos Nucleares, S. A. (ENSA), Spain, direcc.fabrica@ensa.es

SUMMARY

In this work, a complete algorithm for monitoring fatigue was developed for nuclear components; in particular, a feedwater nozzle of a BWR reactor was studied. Firstly, a methodology and an algorithm was developed which is capable of monitoring the actual fatigue of a component in service by means of mathematical models during its lifetime. The mathematical models use transfer and influence functions and are based on Duhamel’s principle. Discrete convolution of the functions was done by numerical analysis. Influence and transfer functions were obtained with a 3D FE model of the nozzle. Combination of thermal and structural 3D models was needed to obtain them. This new method was compared in terms of stress intensity with the results of FE models for the complete transient, showing good correlation. Finally, a methodology was also developed and computed for calculating CUFs in the component critical zones with regards of environmental effects during service life taking into account two different calculation options.

Keywords: Fatigue, monitoring.

INTRODUCTION

The maximum number of load cycles (Nadm) that can be supported by the component and the

expected number of cycles (n) for the different stress levels to be applied during its lifetime are determined in a fatigue assessment. The ratio between both numbers gives the partial damage factor for each stress level. The cumulative usage factor is then determined as the sum of all the partial damage factors. The maximum number of cycles that a component can resist without failure (for instance, in a transient) is calculated from experimental curves, called S-N fatigue curves (S stress or strain amplitude, N number of cycles), obtained from fatigue tests with standard samples of the material in air. These curves have been published in design codes approved by regulatory agencies in

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each country. The number of allowable cycles is reduced compared with those in air, due to the detrimental effect of the environment when the material is subjected to fatigue in an aggressive environment. This effect has been studied in detail in recent decades in the case of primary system components of the reactors of nuclear power plants [1].

BACKGROUND

Existing data show a significant reduction in fatigue life immersed in light water reactors components [2]. Under these conditions the fatigue life of carbon steels, low alloy steels and stainless steels decreases considerably when the thresholds of four parameters are simultaneously exceeded: applied strain amplitude, operating temperature, dissolved oxygen concentration in cooling water and the strain rate. In addition to the previous factors, the sulfur content of the steel is also a very important parameter in fatigue life prediction with environmental effect. Other parameters such as conductivity and flow of water, steel heat treatment and surface finish also influence on the effect of the environment, but not significantly [2]. The mentioned data indicate that a low strain rate applied during part of the cycle in which tensile stresses occur is the main cause of the reduction in predicted fatigue life. In the last decades, new fatigue curves have been developed for the different components, depending on the material studied and the medium in which they are located. Experimental studies [3] have been performed with different components of nuclear power plants, and the results confirm the expected decrease in fatigue life as a result of the environmental impact. The ASME Section III [4] defines the S-N curves to be used in the fatigue assessment and Subsection NB-3121 of the code specifies that such curves were obtained for samples in air condition. For this reason, different agencies and laboratories have conducted studies to determine the influence of the environment on the components in order to include this aspect in the design codes and applicable regulations [3]. Government agencies such as the US Nuclear Regulatory Commission (NRC), the International Atomic Energy Agency (IAEA) and the Committee of the Thermal and Nuclear Power Engineering Society (Japan) have focused their research on obtaining an environmental factor (Fen) taking into account the effects of the environment in which the components are immersed. These effects must be considered and analyzed in new nuclear power plants and in those ones whose license has been extended. The detrimental effect of the environment has been included in the current regulation guidelines [5] and recommendations for the management of ageing of components [6], [7]. First the fatigue evaluation is performed using the curves obtained in fatigue tests in air condition as specified in the ASME code [4]. Later, an estimated environmental factor reducing the maximum number of cycles is applied. Therefore, the evaluation of the harmful effect of the environment is included. Given the difficulty of obtaining an S-N curve for every environment, the regulatory guide [5] proposes mathematical expressions with experimental basis for the calculation of the environmental factor. The mathematical expressions depend on temperature, dissolved oxygen concentration, sulfur content of the steel, and the strain rate of the component. Along the same lines, the Electric Power Research Institute (EPRI) has developed the MRP-47 guide [8] proposing the main guidelines for the evaluation of the factor in changing environmental conditions for LWR reactors, although it has not been approved by regulators. Another aspect is that characteristics of the actual transients under which shall be subjected the component during operation are not known in advance [9]. Therefore, in recent years it is proceeding to monitor critical components during operation at the nuclear power plants. Monitoring provides real-time evolution of the loads on the component, creating a record. Monitoring software converts these loads into stress tensor components and then calculates the partial usage factor. The mathematical methods introduced in the software need transfer and influence functions.

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The procedure for obtaining transfer and influence functions is not regulated. Currently, there are notifications of regulatory bodies who question the procedures used [10].

ANALYSIS

The first step in order to create a monitoring system is to know the response of the component to static and dynamic loads. The behavior of the component is analyzed. The first outputs of the analysis are the transfer and influence functions. Transfer and influence functions relate stress tensor components to their generating loads. Transfer functions are defined herein as linear equations that relate loads directly to stress components. Transfer functions are used when the loads produce instant stress states (not time-dependent). However, thermal loads produce deferred stress states and consequently they are time-dependent. Therefore, the stress state changes through the time although the load level might stay constant. For the analysis of the case with deferred stress states, influence functions are developed, allowing us to obtain the stress tensor history. The first step for the fatigue assessment is the right selection of the component and the location of the points to be included in the stress analysis. This selection affects the rest of the analysis. The component selection is made in regards to different criteria:

Codes, standards and regulatory guides. Reports of learnt lessons by nuclear power plant operators. Environmental conditions. Checkpoints. Design modifications due to repairs. Additional engineering criteria.

Once component selection has been made, it is needed to choose the points to be studied in detail.

The basic criteria for the selection of these locations into the components are: Geometric or material discontinuity. Welds location. Same criteria previously mentioned for the component selection.

A 3D FE model of the components to be analyzed is developed. The accuracy of the model

fulfills the same requirements needed for a technical report. The material properties are an issue which needs careful study. The thermal and mechanical properties of materials change depending on the temperature. So strains and stresses produced by a temperature variation will also depend on the initial temperature. Three options in the material properties configuration are frequently used in calculations:

Constant material properties which correspond to in-service average temperature. Variable and actual material properties. Selection of constant material properties combination producing the highest stresses.

Once the model is finished and the material properties are configured, several analyses are done.

For those loads which need transfer functions, only steady state structural analyses are needed (type I stresses). On the other hand, temperature variations generate loads which produce deferred stress states (type II stresses). As the thermal load needs influence functions, thermal dynamic analyses and steady structural analyses must be done. Special attention has to be paid to the thermal analysis. The influence functions are calculated from thermal load steps representing sudden rising or falling fluid

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temperatures. The temperature maps change once the fluid temperature step happens. The temperature maps of the steel components change during a transient in a few seconds. So the thermal analyses need accurate time steps in the beginning of the transient. Transient stress analyses are finished when the temperature stabilizes and not before. The two-phase state of the fluid influences the fatigue. For a given pressure, if the fluid temperature is above the saturation temperature, the liquid will be saturated and steam bubbles will appear. However, if the fluid temperature is below the saturation temperature, fluid behaves like a sub-cooled liquid. In any of the previous cases, a different level of convective heat transfer is produced. In actual transients, conditions can be given such that generate a two-phase state, and therefore, the analysis of two phase state applies for a more precise calculation of influence functions. The initial temperature and the sign of the fluid temperature modify the influence on the deferred stress state. So these parameters have to be taken into account in the development of the influence functions. The convection coefficient between the fluid and the steel component is a function of circulating flow. The simplest and most conservative estimate is always the consideration of high flow conditions. This means higher convection coefficients, and therefore more abrupt temperature changes. When conservatism is not high, that is, when the differences of the influence functions between high and low flow considered are not large, this criterion is applied. Anyway, when large differences in tensions are present and different flow levels are considered, it is advisable to evaluate at least two or more influence functions. When only two influence functions are used, it is recommended that one is used for high flow and the other for low flow rates. In situations where the difference of the influence functions is very noticeable in regards to the chosen flow, and besides the design margin cannot address large conservatism, they should be used to configure the appropriate number of influence functions, trying to balance calculation accuracy and costs of computational and engineering time.

Figure 1

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PROCEDURE

Every load modifies the value of the total stress tensor. NB-3000 [4] establishes a separation between membrane, bending and peak stresses. Additionally, a classification of primary and secondary stress is required by the code [4]. Due to the different load origin and the classification of the stress required by the code, several transfer and influence functions for each type of stress and stress tensor component are needed. Principal stresses are obtained as eigenvalues of the stress tensor [11]. The stress intensity is expressed as the maximum difference in absolute value between the three principal stresses for each type of stress (total, membrane, bending and peak). After obtaining the stress intensity at each time step for each type of stress in the studied point, it is possible to make an assessment of fatigue in a transient or in a set of transients. First of all, a cycle counting is performed. During the count of cycles, the stress values of the peaks and valleys are obtained. The procedure used to group the peaks and valleys in load pairs is what differentiates one method of cycle counting from another. This is necessary to assess the fatigue in a record of variable stresses. Different cycle counting methods are known, for example [12]: Range-Pair method, Simple-Range method or Rain-Flow method. It is common practice to use the last one [13], [14] because it takes into account the hysteresis loops of the material. The method used for the case study of this research is the Rain-flow cycle counting method as indicated in the ASTM standard [12]. To obtain the partial fatigue usage factor, the S-N curves contained in the ASME code [4] are used. The choice between the S-N curves depends on factors specific to the material, such as steel composition and the ultimate tensile stress. To introduce the amplitude of the stress intensity it is required by the code [4] to make some corrections to the stress intensity amplitude. One is the correction due to different values of Young's modulus between the one used in the S-N curves and the elastic modulus considered in the calculus of the influence functions. Another important correction to be applied occurs when the yield stress is exceeded. This is due to the elastic-plastic behavior of the material. So the correction factor Ke is introduced for this purpose. For the estimation of Ke factor, it is commonly needed to calculate the PPS factor. The PPS factor is defined as the ratio between the total stress intensity with the primary and secondary membrane plus bending stress intensity.

SISI

PPS QbQmPbPm

The PPS factor may be applied by three different methods. For the case study in the three

methods, the PPS value is calculated in every time-step of the transient. The maximum PPS factor is calculated in the transient. A PPS constant value is then applied

to the total stress intensity for each time-step of the transient. A linear regression is calculated after the calculation of PPS in a transient. This linear

regression is a function which relates the PPS with the instant total stress intensity of the transient. Then, the PPS is applied to the total stress intensity of every step of the transient.

Direct application. The factor PPS is applied in every step of every transient from the transfer and influence functions. Then the peaks, valleys and the duration of peaks and valleys are extracted and operated with the Rain-flow method.

Then, the selected PPS is applied to the instant stress intensity in order to calculate the range of

primary and secondary stress intensity. Finally, the NB-3228.5 [4] paragraph is applied to calculate the Ke factor.

mQbQmPbPme

QbQmPbPm

SSInmfKSIPPSfSI

,,,

,

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Where m and n are constants of the materials as NB-3228.5 [4] and Sm is the stress limit [17]. For the evaluation of the cumulative usage factor produced by a sequence of cycles, the

Palmgren-Miner rule is used [15],[16]. This rule is frequently used in fatigue analysis and is mandatory in accordance with ASME Section III [4]. The main input data for the fatigue monitoring algorithm developed herein are:

Temperature versus time of the transients. Pressure versus time of the transients. Fluid flow versus time of the transients. Time step. Transfer and influence functions. Material properties.

The main output data for the same monitoring algorithm are:

Cumulative usage factor, CUF. Number of cycles or semi-cycles if the Rain-Flow method is used. Fatigue limits for each cycle according to ASME Code [4]. Stress Intensity in every step of the transient for every type of stress. Stress Intensity corrected for every cycle. Ke correction factor. Time at the peak and at the valley for every cycle or semi-cycle related from the start time of

the transient or sequence of transients.

As previously mentioned in Background, the LWR water coolant environment reduces the fatigue lifetime of the components immersed in this environment. In nuclear power components this effect is evaluated by means of the environmental fatigue life correction factor. The environmental fatigue life correction factor (Fen) is defined by the expression [2],[18]:

Aen

W

NFN

Being NA fatigue life (number of cycles to failure) in air condition at room temperature for a

specified stress amplitude; and NW the fatigue life (number of cycles to failure) in the in-service conditions (coolant water at high temperature). Fen factor is used to modify Miner’s rule thus obtaining the cumulative fatigue usage factor with the next equation:

1

,

ii

en en im i

nCUF FN

Different statistical models have been developed for the estimation of Fen by different

organizations, for example: ASME [19], ANL [2], MITI and JSME. The Fen estimates are based on the different environmental parameters (like dissolved oxygen concentration, temperature), load strain rate and steel chemical composition. These models usually have the form:

* *exp( )enF A B S T O

Where A and B are model fitting parameters to experimental fatigue tests considering steel type and BWR or PWR environments. Besides S*, T*, O* and * are transformed sulfur content,

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temperature, dissolved oxygen concentration (DO) and strain rate, respectively. The process flowchart for environmental fatigue evaluation is summarized in the Figure 1. In Case Study, ANL model from [2] is used. The expressions provided by ANL for wrought and cast austenitic steels are:

* *, exp(0.734 )en nomF T O

Where T*, O* and * are defined as:

* 0T 150ºT C * 150 175T T 150 325ºT C

* 1T 325ºT C * 0.281O All DO levels

* 0 0.04% / s * ln( 0.4) 0.0004 0.4%/ s * ln(0.0004 / 0.4) 0.0004% / s

It has to be noted that if strain amplitude (εa, half of strain range) value of 0.10% is not exceeded

then Fen takes a value equal to 1 and there is no environmental effect in this case for wrought and austenitic steels. Another relevant issue for the calculation of the environmental fatigue correction factor is to obtain it in each load pair set corresponding to a cycle or half-cycle. The Modified Rate Approach is the method suggested by EPRI [20]. In each cycle, Fen,i is calculated for every time step regarding the instantaneous strain rate and strain range (Δεi). The total cycle Fen factor is obtained as an integrated summation [20]. Two options for the analysis of the Fen factor within a cycle where peak and valley are not consecutive are investigated herein. Option A (EPRI Method) is to calculate the integration from the valley in the stress intensity cycle to the next peak in the sequence and up from the preceding valley to the peak of the cycle [20]. Option B consists of integrating the Fen factor with the tensile strain following the water drop path from the valley to the peak in the same parts of the cycle or half-cycle traced in the Rain-flow cycle counting method. Additionally, the three options for Ke calculation are also studied for the environmental effect, because Ke is also needed to calculate the strain range in the Modified Rate Approach [20]. So, six different options are studied for environmental effect.

CASE STUDY

A reactor pressure vessel nozzle is selected to be studied from a BWR reactor because is subjected to numerous transients during its in-service life. Two 3D FEM models were created in ANSYS 10.0 program [21] with 3D hexahedral elements, one for structural analysis and the other for thermal analysis regarding plane symmetry. FEM thermal model is shown in Figure 2 and feeds the FEM structural model with temperatures for each point. The mechanical and thermal properties were modeled as a function of temperature for all the steels and claddings, in the safe end, reactor shell, thermal sleeve and blend radius. The next step is to obtain the influence functions for the critical points and for this reason several sections are analyzed in the 3D structural model. The critical point in this case is identified in the inner part of the safe end. In Figure 3, the principal stresses and the stress intensity of the influence function for a 100 ºC ascending temperature step at the critical point are shown.

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Figure 2

Figure 3

Essentially, the next points are taken into account to obtain the influence functions:

Models: 3D models (both, thermal and structural) with variable size element, adjusted to geometry.

Material properties: function of temperature. Fluid saturation: saturation temperature is considered not to be exceeded. Thermal step sign, both possibilities, positive and negative are regarded. Thermal step range and mean: 100 ºC is selected, and a mean value of 221 ºC close to

operational reactor temperature (289 ºC) was also considered. Flow: 100% nominal flow is selected; consequently, flow conditions include turbulent flow

and natural convection.

Additionally, for the calculation of type I stresses, transfer functions are obtained. Transfer functions represent the instantaneous reaction to mechanical external loads and pressure loads. Several transfer functions are needed to obtain membrane, bending, peak and total stresses for all the stress tensor components. Flexural moment and axial force applied to nozzle connection to piping system are linearly proportional to temperature. Once the influence and transfer functions are calculated, it is possible to analyze a complete transient. A design transient including a fast depressurization event of

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the reactor corresponding to the analyzed nozzle is studied herein. Temperature vs. time plot is showed below in Figure 4. The algorithm for fatigue monitoring developed in MATLAB programing language [22] is capable to classify the ramps and steps of the transient. The stresses are calculated for the six tensor components in all the stresses, using numerical methods applied to Duhamel Integral. In Figure 5, stress intensity is observed for membrane (SIM), bending (SIB), peak (SIP) and total (SIT) for the studied transient at nozzle’s critical point. This result shows a delay in the response for bending stress related to peak stresses. For comparison purposes, the transient thermal stresses were also calculated with the FEM models in ANSYS© used for the calculation of influence functions. The result shows good agreement between both methods (See Figure 6, SI MATLAB obtained only with influence functions). Hence, Cumulative usage factors (CUFs) are obtained from stress intensity using Rain-Flow Counting Method and ASME S-N Curves for each cycle or half-cycle. The total number of cycles and half-cycles for this transient is seven. Table 1 summarizes the cycles (or half-cycles) related to turning points. Turning points are represented by letters (from A to K) in schematic plot of the Figure 7. The damage ratios per cycle are obtained, however only four cycles (3, 5, 6 &7) have stress amplitudes too low to produce fatigue damage according to ASME code.

Figure 4

Figure 5

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Figure 6

Figure 7

Table 1

Cycle Rain-flow Cycle

Number Initial Time (s) Final Time (s)

C-D 1 1 22 24 E-F 2 1 31 33 A-B 3 0.5 0 5 H-I 4 1 179 180 B-G 5 0.5 5 69 G-J 6 0.5 69 185 J-K 7 0.5 185 400

The results of Miner’s sum are shown in Figure 8 for the three Ke estimation methods and for two

forementioned options of environmental factor calculation (options A & B). From these results, it is

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observed that there is relevant effect when using different estimates for Ke. Besides, in the case study, the different options (A & B) in Fen calculation show no effect in environmentally affected fatigue. This is probably due to a short stress history of the studied transient. However, it is also shown that environmental effect is relevant for fatigue life prediction of the studied component.

0,00E+00

1,25E-03

2,50E-03

3,75E-03

5,00E-03

6,25E-03

7,50E-03

8,75E-03

Ke method 1 Ke method 2 Ke method 3

Tota

l CU

FCUF

CUFen Option A

CUFen Option B

Figure 8

CONCLUSIONS

The methodology of fatigue monitoring has been applied to a case study. The results of the case study have been compared to a FEM simulation. Environmental effect is a relevant issue in fatigue life prediction of the studied nuclear component.

The contrast of the results for the case study and the results of the FEM simulation shows that the

methodology used for fatigue monitoring presents good correlation.

REFERENCES

[1] Chopra O.K., and Shack W.J., “Effects of LWR Coolant Environments on Fatigue Design Curves of Carbon and Low-

Alloy Steel,” NUREG/CR-6583, ANL-97/18, U.S. Nuclear Regulatory Commission, 1998.

[2] Chopra O.K., and Shack W.J., “Effects of LWR Coolant Environments on the Fatigue Life of Reactor Materials”, Final Report, NUREG/CR-6909 (ANL-06/08), U.S. Nuclear Regulatory Commission, February 2007.

[3] Strömbro J., and Dahlberg M., “Evaluation of the Technical Basis for New Proposals of Fatigue Design of Nuclear Components”, Swedish Radiation Safety Authority, 2011.

[4] ASME Boiler and Pressure Vessel Code Section III, Rules for Construction of Nuclear Power Plant Component, 2001, The American Society of Mechanical Engineers, New York, USA.

[5] U. S. Nuclear Regulatory Commission. Regulatory Guide 1.207. Rev.1, March 2007.

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[6] IAEA Technical Document 1470: Assessment and Management of Ageing of Major Nuclear Power Plants Components Important to Safety: BWR Pressure Vessels, October 2005.

[7] IAEA Technical Document 1361: Assessment and Management of Ageing of Major Nuclear Power Plant Components Important to Safety: Primary Piping in PWRs, July 2003.

[8] EPRI, Materials Reliability Program (MRP): “Guidelines for Addressing Fatigue Environmental Effects in License Renewal Applications”, MRP-47 Rev.1, September 2005.

[9] Rudolph J., Bergholz S., Heinz B., and Jouan B., “AREVA Fatigue Concept- A Three Stage Approach to the Fatigue Assessment of Power Plant Components”, Chapter 11, Nuclear Power Plants, Ed. Chang H.S., 2012.

[10] NRC Regulatory Issue Summary 2008-30.

[11] Cicero R., Gorrochategui I., Cicero S. and Álvarez J.A., “On the fatigue stress range calculation with on-line monitoring systems in nuclear power plants,” 17th European Conference on Fracture, Brno, Czech Republic, 2008.

[12] ASTM E 1049-85 (Reapproved 2005), Standard practices for cycle counting in fatigue analysis, ASTM International.

[13] Nieslony A., “Determination of fragments of multi-axial service loading strongly influencing the fatigue of machine components”, Mechanical Systems and Signal Processing, Vol. 23(8), pp. 2712-2721, 2009.

[14] Jhung M.J., “Fatigue Analysis of a Reactor Pressure Vessel for SMART”, Nuclear Engineering and Technology, Vol 44 (6), pp. 683-688, August 2012.

[15] Palmgren A., “Die Lebensdauer von Kugellagern”, Zeitschrift des Vereins Deutscher Ingenieure, Vol. 68, pp. 339-341. 1924.

[16] Miner M.A., “Cumulative damage in fatigue”. Journal of Applied Mechanics, Vol. 12, pp.159-164. 1945.

[17] ASME Boiler and Pressure Vessel Code, Section II, Part A, “Ferrous Materials Specifications”, 2001 Edition plus 2003 Addenda, the American Society of Mechanical Engineers, New York.

[18] JNES, “Nuclear Power Generation Facilities, Environmental Fatigue Evaluation Method,” JNES-SS-1005, 2011.

[19] Cases of ASME Boiler and Pressure Vessel Code, Case N-792, “Fatigue Evaluations Including Environmental Effects, Section III, Division 1”, The American Society of Mechanical Engineers, NC-Supp. 6, 2012.

[20] EPRI, “Stress-Based Fatigue Monitoring: Methodology for Monitoring Class 1 Nuclear Components in a Reactor Water Environment”, November 2011.

[21] ANSYS Computer Program Release 10.0, ANSYS Inc.

[22] MATLAB & Simulink version R2012a. Mathworks, 2012.

CONTENT OF TEXT

BWR: Boiling water reactor. CUF: Cumulative usage factor. DO: Dissolved oxygen. FEM: Finite element method. LWR: Light water reactor. PWR: Pressurized water reactor.

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OECD/NEA CSNI WGIAGE; Fourth International Conference on Fatigue of Nuclear Reactor Components

28th September-1st October, 2015, Sevilla, Spain

Alternative Approaches for ASME Code Simplified Elastic Plastic Analysis

Nathan A. Palm Electric Power Research Institute, USA, npalm@epri.com

Sampath Ranganath

XGEN Engineering, USA, sranganath@sbcglobal.net

SUMMARY

Subsection NB, Section III of the ASME Code provides rules for the fatigue evaluation of nuclear pressure vessel and piping components. The stress analysis in ASME Code evaluation is generally based on linear elastic analysis. Simplified rules using an elastic-plastic strain correction factor, Ke, are provided in Section III to account for plastic yielding when the stress range exceeds the 3Sm limit. While the simplified elastic plastic analysis rules are easy to apply and do not require nonlinear analysis, the application of the Ke correction factor can produce extremely conservative results. This paper investigates different analytical methods that are available for simplified elastic plastic analysis and proposes an alternative, less conservative, and more realistic approach to simplified elastic plastic analysis. Use of this alternative approach has the potential for significant reductions in calculated fatigue usage in ASME Section III fatigue analysis. Background

Subsection NB, Section III, ASME Code [1] provides rules for the fatigue evaluation of nuclear pressure vessel and piping components. The general methodology for evaluation of vessel components is provided in NB-3200 and simplified rules for piping are specified in NB-3600. The stress analysis in ASME Code evaluation is generally based on linear elastic analysis. Use of linear elastic analysis is reasonable as long as the stress range is within 2Sy or 3Sm in terms of the ASME Code design stress intensity (Sm). When the stress range exceeds 3Sm there is continued plastic yielding and the strain range calculated assuming elastic analysis can under-predict the actual strain range. The ASME Code allows the use of nonlinear elastic-plastic analysis when the 3Sm range is exceeded. Nonlinear analysis is typically expensive and time-consuming, especially for piping. Thus, simplified methods for elastic-plastic analysis are prescribed in NB-3228.5.

The simplified elastic plastic analysis rules are easy to apply and most ASME Code structural

analyses include some use of the NB-3228.5 rules. While the rules are easy to apply, using results based on elastically calculated stresses, the resulting Ke value can be extremely conservative. This conservatism could result in an overestimate of the calculated usage factor (CUF) by a factor of 10-30 depending on the magnitude of the stress amplitude The fact that there has been virtually no field experience of fatigue crack initiation due to low cycle fatigue (which is the range for which the

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simplified elastic plastic analysis rules are applied), even in cases of high calculated CUF, confirms the conservatism in the ASME Code analysis procedures.

While it was possible to show acceptable CUF using the conservative NB-3228.5 rules in the

original analysis, the combination of license renewal, potential second license renewal, peak loading and environmental fatigue can result in unacceptable CUF values. Some plants have used refined calculations and finite element elastic plastic analysis to address this, but these options are time consuming and are expensive. Alternative rules are needed that preserve the simplicity of the NB-3228.5 simplified elastic plastic analysis rules, but reduce the excessive conservatism in the methodology. This paper describes the basis for the current existing rules, alternative rules in structural codes in other countries, and ASME Code Cases related to simplified elastic plastic analysis. New analysis methods are also recommended. Basis for the current ASME Code methodology

The technical basis of the ASME Code simplified elastic plastic analysis was originally developed by Langer [2]. The following quote from [2] describes the circumstances when elastic analysis can under predict the actual strains:

Strain concentration can occur in any structural member with stress gradients as soon as the loading exceeds the point at which the highest-stressed region becomes plastic. If the plastic zone is highly localized, the surrounding elastic material controls the strain in the plastic material and no strain concentration occurs. When the plastic zone is large enough to become a significant factor in the stress distribution, however, the strains in the plastic zone become larger than those which would be calculated by the theory of elasticity and strain concentration must be considered. Langer defined the strain-concentration factor, Kε

1 as the actual peak strain divided by the peak

strain calculated for completely elastic behavior on the assumption that the maximum deflections are the same in the two cases. He looked at two configurations for the determination of the strain concentration factor: a) a tapered flat bar in tension; and b) cantilever beam. Both are evaluated using a nonlinear elastic analysis model assuming a stress strain curve given by:

(1)

where is the applied stress, is the associated strain, A is a constant (with units of stress) and

n is the typical strain hardening parameter. The exponent n is typically the true strain at maximum load ( ). For n=0, the stress strain relationship becomes rigid-perfectly plastic and for n=1, the relationship becomes linear elastic.

As previously stated, the strain concentration factor, is defined as the actual peak strain divided by the peak strain calculated for completely elastic behavior on the assumption that the maximum deflections are the same in the two cases. In other words, two structures I and II which are geometrically identical when unloaded. Structure I remains elastic throughout, and structure II follows the plastic stress-strain relationship, . For the tapered bar, is a function of the area ratio, ρ = b1/b0 where b1 is the primary width of the bar and b0 is the width at the narrowest

                                                            1 Langer expressed the strain concentration factor as Kε, but the ASME Code uses Ke, they are the same.

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point of the taper. is the ratio of the peak strain in bar II to the peak strain in bar I and is given by:

(2)

The second case considered by Langer was the case of a cantilever beam of rectangular section

with a concentrated end load. As before, defining as the actual peak strain divided by the peak strain calculated for completely elastic behavior on the assumption that the maximum deflections are the same in the two cases results in the following expression for :

(3)

ASME Code simplified elastic plastic analysis

Langer’s initial proposal was to bound the prediction for the two cases by setting =1/n. Except in the cases where the area ratio, ρ is large, the 1/n proposal provides a reasonable but very simple bounding prediction. Langer also provided values for the strain hardening coefficients for different materials. Essentially, there is no Ke factor for Stress Range P+Q < 3Sm, but the full Ke value of 1/n will be reached when P+Q > 6Sm.

Tagart [3] suggested a modification to Langer’s proposal stating that the generic “m” value of

2 (used by Langer to establish the upper limit of 6Sm) should not necessarily apply for all materials. He suggested different values based on the B31.7 rules that essentially specified m values for stainless steel, low alloy steel and carbon steel. This resulted in the following expression for Ke.

1forS 3S

1 1 for3S S 3 S (4)

1/ forS 3 S

where, S is the range of primary plus secondary stress intensity, generally stated as P+Q range. Figure 1 shows the Ke factor as a function of Sn/Sm (i.e. ratio of the P+Q range and the ASME

Code design stress intensity, Sm. This was incorporated into Section III, but with one additional provision: P+Q-Thermal Bending should be less than 3Sm. This assures that the contribution to P+Q range from primary loads and secondary membrane (e.g. thermal membrane stress) is still restricted to the3S limit. The application of the Ke methodology is essentially the same for both the vessel component analysis (NB-3200) and piping analysis (NB-3600).

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 Figure 1 – Ke Factors from the ASME Code

The advantage of the ASME Code Simplified Elastic Plastic Analysis is its simplicity; it can be used with conventional results (e.g. P+Q range) already available from elastic analysis. A major disadvantage is that the Ke values may be conservative by as much as a factor of 2 especially where the thermal stresses due to temperature transients may contribute to much of the P+Q range. This is almost always true in reactor vessel components.

Available alternative methods for simplified elastic plastic analysis

Several papers suggesting improvements to the ASME Code rules for simplified elastic plastic analysis have been published in the literature. The objectives of these papers have been twofold: i) reduction of some of the excessive conservatism especially for thermal transients; ii) adding conservatism in some cases where notch effects have not been addressed. These are described in the following subsections:

WRC-361 improvements for fatigue analysis methods based on the RCC-M Code

WRC-361 [4] provided the technical basis for several suggested changes to the ASME Code rules. It suggested separate consideration of thermal bending stress range from the other parts of the P+Q range e.g. primary and secondary stresses due to mechanical loading such as pressure and seismic loads. Separate Ke factors considering Poisson’s ratio effects in thermal bending are proposed. The ASME Code rules for other stress transients are retained, but the final proposed rule for Ke (referred to as ∗later in this paper) in WRC-361 uses the weighted average of the Ke for thermal loads (referred to as later) and the ASME Code Ke value for other loads. Finally, consideration for notches based on Neuber analysis is included.

Consideration of Poisson’s ratio effects

The Poisson’s ratio effect of strain interaction is most significant under conditions of a local thermal stress state that is characterized by having two principal stresses approximately equal. Under elastic plastic behavior conditions, the interaction becomes stronger and elastic results must be adjusted through a Poisson’s ratio correction. For elastic analysis the appropriate value of ν is the usual value of 0.3. For complete plastic behavior (where the elastic component is small in

0

1

2

3

4

5

6

0 1 2 3 4 5 6 7 8 9 10

Ke

Sn/Sm

Carbon Steel

Low Alloy Steel

Stainless Steel/Ni‐Cr‐Fe

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comparison with the plastic component) the effective Poison’s ratio, ν*, is used and the corresponding value is approximately 0.5. This is because the volume change under fully plastic behavior is zero. For conditions in between, the equivalent ν* is determined by equating the volume change for the elastic case (Poisson’s ratio ν and elastic modulus, E) and the elastic-plastic case (ν* and Es, the secant modulus that represents the elastic plastic condition). The resulting equivalent Poisson’s ratio ν* is given by:

ν*=0.5 0.5 ν (5)

Assuming the strain contributing to stress (i.e., constrained strain as it would be for a

thermal stress), the stress intensity is given by:

1

(6)

The stress intensity for elastic plastic behavior can be determined by substituting ν* in place

of ν. The additional factor considering Poisson’s ratio effects is essentially the multiplier that is used to correct the elastically calculated stress intensity to account for the higher Poisson’s ratio ν* for plastic behavior. It is the ratio of the plastic and elastic stress intensities. If the bounding value of the equivalent Poisson’s ratio is used (ν*=0.5 for extreme plasticity), the maximum value is:

∗

.

.1.4. (7)

Combination of Thermal Bending and Mechanical Loads

The previous discussion addresses the effects of thermal stresses and justifies a smaller strain concentration factor than the ASME Code Ke value. It shows that for thermal cycling only, the correction factor for plastic behavior (or in other words, the correction from the higher effective Poisson’s ratio as a result of plasticity) can be limited to the maximum value of 1.4. It essentially means that Ke for thermal cycling is at most, 1.4, well below the value in NB-3228.5 of the ASME Code. For mechanical loading (pressure, seismic load) the ASNE Code Ke value is assumed to apply. For the combination of thermal and mechanical stresses, WRC-361 recommends a weighted average as shown below:

∗

(8)

Consideration of notch effects based on Neuber analysis

WRC-361 also describes the use of Neuber notch analysis to determine the local strain concentration factor in the presence of a notch. Geometric notches such as that in a counterbore in a pipe or the notches associated with the K index in piping fatigue analysis are examples of notches. KT is included in the elastic stress analysis, but for plastic analysis the strain concentration (based on Neuber notch analysis) may be somewhat higher than that given by KT alone. Therefore, a notch plasticity factor is applied on top of the factor with the Poisson’s ratio correction. The notch plasticity factor is defined as:

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(8)

Some of the considerations in applying the Neuber notch factor are described here:

The Neuber notch strain factor described above could apply even when the stress intensity

range is less than 3Sm. The notch factor is typically applicable to one stress component (e.g. axial stress in a pipe

with a circumferential notch) and need not be applied to other stress components in determining the stress intensity. A simpler, but more conservative approach is to apply it on the final stress intensity (i.e. apply on all stress components).

The notch factor in Equation 9 would apply in addition to the theoretical stress concentration factor, ,which is used to determine the peak stress amplitude for fatigue analysis.

Although not explicitly stated in WRC-361, the effective strain concentration is determined by

combining the correction factor, ∗, for Poisson’s ratio effects for plasticity and for notch effects (i.e. Equations 8 and 9):

∗ (10)

There are several additional alternate methodologies for simplified elastic plastic analysis in the literature, but almost all of them use some parts of the WRC-361 methodology. EPRI/SIA methodology for simplified elastic plastic analysis

Deardorf and Pan [5] described an improved approach and proposed a Code Case for performing simplified elastic-plastic analysis. It is largely based on the WRC-361 methodology. In their proposed procedure, the EPRI/SIA methodology called for the effective to be equal to the product of the factor (similar to that in Equation 9) and the ∗factor (similar to that in Equation 8). It is simple and easy to apply. It incorporates the effect of Poisson’s ratio and the notch factor correction. It uses the weighted approach for the effective Ke suggested in WRC-361 and replaces Ke with Ke

’.

An important contribution in the EPRI/SIA report is the validation of the conservatism of the proposed rules by comparing the predicted Ke results with those from detailed elastic plastic analysis on stainless steel components. Three finite element models of axisymmetric structures under varying pressure and thermal loads were analyzed using ANSYS finite element models and elastic-plastic analysis. The three models were: i) straight pipe, ii) a tapered transition pipe with inner radius transition (with change in thickness where the OD is the same) and iii) a pipe with outer radius transition (similar to a nozzle where the ID remains the same, but the OD changes). The calculated Kν based on elastic-plastic analysis was below the bounding Kν value of 1.4 in all cases of thermal loading only. It was well below the Ke based on the ASME Code. For most of the elastic plastic analyses (three pipe configurations, 4 thermal only cases and 4 thermal and pressure cases), the effective Ke value was in the range 1.6-1.7, almost half the limit of the maximum ASME Code Ke value of 3.33 for stainless steel.

One issue that is left unclear in the proposed Code Case is the dependence of ′ as a function of /3 . While the ASME Code Ke varies from 1 to 1/n continuously as /3 varies from 1

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to m, the proposed Code Case may have a discontinuity at /3 =1 where there is a step change from 1 to Kν. Any discontinuity at /3 is without a physical basis and results in ambiguity for users; however this is not unique to the EPRI/SIA methodology. It is inherent in the WRC-361 formulation and in other models. The EPRI/SIA methodology also uses the von Mises criterion for the plastic evaluation. While this is reasonable, it is inconsistent with the rest of the ASME Code which is based on the Tresca shear criterion. Finally, the EPRI/SIA methodology requires calculation of new parameters, Sp,t and Sn,m which are not available in conventional ASME Code stress reports. ASME Code Case N-779

A more recent development was ASME Code Case N-779 [6] which was approved in 2009. As in other cases, the general methodology was similar to that described in WRC-361. While the corrections in the Code Case for Poisson’s ratio and notch effects are similar to that described in WRC-361, the value of Sa used in entering the fatigue curve is a combination of three terms: i) P+Q range without thermal bending and local thermal stress multiplied by the Code Ke, ii) local thermal stress multiplied by and iii) the linear thermal bending stress range multiplied by . The equations are somewhat complicated to use. Although the Code Case was approved by the ASME, the NRC has not included it in the list of approved Code Cases and there are no known instances of plant-specific use. Simplified elastic plastic analysis in regulatory codes in other countries

Regulatory codes in several countries have developed simplified elastic plastic analysis rules that preserve some of the features of the ASME Code NB-3228.5 simplified procedures, but account for the Poisson’s Ratio and notch effects. The discussion below on the French and Japanese Codes is based on papers published in the literature. French Code (RCC-M)

The French RCC-M Code [7] follows the ideas in WRC-361 including consideration of Poisson’s Ratio and notch effects. The alternating stress amplitude (Sa or Salt) used to determine the allowable number of cycles from the fatigue curve is:

0.5 (11)

where is the same as the ASME Code Ke factor from NB-3228.5 and

1.86 1. /

but not less than 1 (12)

Based on these equations, the factor is greater than 1 for ≅ 0.5 which means that the

Ke penalty kicks in in many cases, even when the Sn value well below 3Sm. Figure 2 shows the comparison of the Ke from RCC-M with the results of the ASME Code as well as finite element evaluation. Several conclusions are clear: i) the Ke values from RCC-M for stainless steel are well

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below those from the ASME Code (i.e. ≅ 2 for RCC vs. 3.33 for ASME); ii) the values from elastic plastic analysis are ≅ 1.5, well below both the RCC-M and ASME codes.

 Figure 2 - Comparison of the Ke from FEA with ASME, RCC-M Code (Values Sn in MPa)[7]

Japanese Code

The earlier Japanese codes (MITI 501) followed the ASME Code (with slight modifications) but significant changes were made by the Thermal and Nuclear Power Engineering Society (TENPES) in Japan. The revised rules are described in [8] but the technical justification is not included in the paper.

Comparison of the different codes

Comparisons of the Ke factors by Gurdal and Xu in [9] based on elastic plastic analysis and the Ke factors from the ASME code, the RCC-M code, the JSME code and the B31.7 piping code are shown in Figure 3. The comparison was made for the analysis of the Bettis stepped pipe test documented in [10]. Several conclusions can be made from the comparison:

The ASME Code Ke factors are extremely conservative, well above the Ke values from other regulatory codes.

The Ke value based on the results of the elastic plastic analysis is below 1.5 in most cases.

The French Code came closest to the elastic plastic analysis, but is conservative relative to the current Ke rules for Sn values less than 3Sm.

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 Figure 3 - Comparison of the Ke by FEA, ASME, B31.7, RCC-M and JSME Codes [9]

Alternative proposal for simplified elastic plastic analysis

As can be seen from the discussion above, a number of improvements have been proposed to the Code procedures and alternatives exist in other Codes. While the proposed improvements and alternate procedures generally provide reduced conservatism for Ke, the proposals or alternatives all have some drawbacks. A method is still needed that reduces the conservatism of the current Ke approach, takes Poisson’s ratios and notch effects into consideration, and maintains the simplicity of the current ASME Code approach. Preferably, it should be possible to use existing stress report information (vessel or piping) to determine the new revised Ke factors. In other words, the use of the new Ke methodology should not require new analysis or require modification of existing analysis software (such as the computer codes used for piping analysis). Additionally, there should not be a discontinuity in Ke as a function of Sn.

The proposed methodology applies to both vessel and piping components, but for simplicity, separate descriptions are provided for piping and vessel components. It should be noted that other requirements of the ASME Code, such as those for ratcheting, must continue to be met. New proposal for vessel components (NB-3200)

The newly proposed Ke factor (referred to hereafter as ∗) starts with the WRC-361 proposal

which is reflected in Equation 8 of this paper. Since P+Q and P+Q-thermal bending (TB) are known, TB is also essentially known (the difference between P+Q and P+Q-TB). Substitution can be made as follows:

. (13)

It is conservatively assumed that the remaining stress, P+Q-TB is all mechanical i.e.

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. (14)

Since thermal stress can be both membrane and bending, it is conservative to treat the thermal membrane stress as a mechanical stress. In Equation 8, the Code Ke is applied to the thermal membrane stress as well as the stresses due to the mechanical loading. The ASME Code requirement P+Q-TB < 3Sm is maintained in the new proposal. The ratio of P+Q-TB and P+Q=Sn is defined as:

= (15)

Rewriting this:

1 (16)

An additional parameter R* is defined, which is the value of R when P+Q=3mSm:

∗ (17)

Furthermore, it is conservatively assumed that has the maximum value of 1.4 based on

Tresca analysis. Substituting Equations 15 and 16 in Equation 8 and assuming to be 1.4, results in the following equation for ∗:

∗ 1.4 for3 3 or

∗ 1.4 1 for3 3 (18)

This is just the weighted average of the K factors for the thermal and mechanical stresses. This

results in a step change in Ke at Sn = P+Q= 3Sm. In order to eliminate the step change, the following modification is proposed:

∗ 1 for Sn = P+Q< 3Sm

∗ Smaller of and {1.4 1 for 3Sm <Sn=P+Q<3mSm (19)

Equation 18 reaches the maximum value at P+Q=3mSm (e.g. P+Q=5.1Sm for stainless steel)).

This is because increases with P+Q, but reaches the maximum value of 1/n at P+Q =3mSm. Similarly, ∗ reaches the maximum value at P+Q=3mSm. Substituting for = 1/n at P+Q=3mSm in Equation 18 results in the following:

∗ 1.4 1 1.4 ∗ 3 (20)

Since the ASME Code limits P+Q-TB to 3Sm, the ∗values are calculated for different values of P+Q-TB up to 3Sm. Figure 4 shows the proposed ∗ for different values of P+Q-TB for stainless steel, carbon steel and low alloy steel respectively. For P+Q-TB=0 (i.e. the entire stress range is due to thermal bending), the maximum ∗is 1.4. For other values of P+Q-TB, the maximum value is that determined by Equation 20. The alternating stress used in entering the fatigue curve is:

0.5 ∗ (21)

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where is the peak stress range without the Ke factor. The stress should also be corrected for the E corresponding to the value used in the ASME Code fatigue curve.

 Figure 4 - Proposed Ke* Factor as a Function of Sn for Stainless, Carbon, and Low Alloy

Steels

New proposal for piping components

For piping analysis, the stress inputs needed to apply the new proposal is confined to Equations 9 to 13 in NB-3600 of the ASME Code. In a way, the procedure is simpler. The P+Q and P+Q-TB values are already in the NB-3600 equations:

Sn = P+Q = Equation 10 of NB-3653 P+Q-TB = Equation 13 of NB-3653 TB = Difference between the left hand side of Equations 10 and 13 of NB-3653. Rewriting,

=

(22)

As before, R* is defined as:

∗

(23)

∗ is calculated using equations identified above for vessel components. The ∗ values

shown in Figure 4 can be used for piping components also. The only difference is that R and R* are based on Equations 13 and 10 in NB-3600. The alternating stress is calculated per equation 21. Consideration of the notch effect

The proposal described above does not consider the Neuber notch effect. Several arguments could be made that the notch effect does not need to be explicitly considered. Even with proposal above, the resulting Ke is conservative with respect to finite element evaluation results. Furthermore, the use of a stress concentration factor, KT, is still required and the ASME Code KT values themselves are inherently conservative. To be consistent with WRC-361 and the alternative

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procedures discussed in this paper, the notch effect could be considered provided that a discontinuity at 3Sm is not introduced, the simplicity of the approach is maintained, and the alternative procedure still reduces the conservatism in the current ASME Code procedure for Ke. One such approach would be to define Kn as follows:

1 for Sn =3Sm

for Sn = 3mSm (24)

Linear interpolation would be performed for values between 1 and the maximum value of Kn. An example of the resulting value of Ke* including this provision for consideration of the notch factor is shown in Figure 5 for low alloy steel.

 Figure 5 – Example of Ke including Kn for Low Alloy Steel and KT=1.5

Summary and conclusions

This report describes the technical basis of the current ASME Code NB-3228.5 rules for simplified elastic plastic analysis. It also describes available alternate methods in the literature for calculating the Ke factors. All the new methods consider indirectly the Poisson’s ratio and notch effects. One disadvantage of the alternate methods is that they are somewhat complex (e.g. N-779) and require new stress calculations in order to apply the methods. This is a disadvantage when the methodologies are used for current operating plants for license renewal and use of peak load following or for addressing environmental effects.

The procedures proposed in this report are simple, easy to apply and do not require information that is not already available in existing stress reports. The proposal is intended to be general and applicable to stainless steel, carbon steel and low alloy steel. Whether or not consideration of the notch effect is included, the proposal will reduce the conservatism of the existing ASME Code approach, while remaining conservative with respect to finite element analysis methods. Use of the proposed approach will ultimately reduce CUF values and allow challenges with respect to license renewal, load follow operation, and consideration of environmental effects to be addressed.

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REFERENCES

1 ASME Boiler and Pressure Vessel Code, Section III, Division 1, 2013 Edition.

2 B. F. Langer, “Design Basis for Pressure vessels,” The William M. Murray Lecture 1970,

Published in Experimental Mechanics 1971.

3 S. W. Tagart, Jr. “Plastic Fatigue Analysis of Pressure Components,” ASME Paper 68-PVP-3, presented at the Joint Petroleum/PVP Joint Conference, Dallas, TX, Sept 1968.

4 Grandemange, J. M., Heliot, J., Vagner, J., Morel, A., and Faidy, C., “Improvements on Fatigue Analysis Methods for the Design of Nuclear Components Subjected to the French RCC-M Code,” Welding Research Council Bulletin 361, February, 1991.

5 An Improved Approach for Performing Simplified Elastic-Plastic Fatigue Analysis, EPRI, Palo Alto, CA: 1998. Report TR-107533.

6 ASME Code Case N-779, “Alternative Rules for Simplified Elastic-Plastic Analysis,” Class 1 Section III, Division 1.

7 C. Faidy, Tutorial on C&S ASME - PVP 2006 - July 24-28, 2006 Vancouver – Canada.

8 I. Saito and T. Shimakawa , “Outline of the JSME Rules on Design and Construction for Nuclear Power Plants,” Proceedings of the 2004 ASME Pressure Vessels and Piping Division Conference, July 25-29, 2004, San Diego, California, USA, PVP-Volume 480, Pages 197-204.

9 R. Gurdal and S. Xu, “A Comparative Study of the Ke factor in Design by Analysis for Fatigue Evaluation,” ASME PVP 2008-61222.

10 D.P Jones, J.E. Holliday, T.R. Leax and J.L. Gordon, “Analysis of a Thermal Fatigue Test of a Stepped Pipe,” PVP Paper No. 2004-2748, PVP Volume 482, Computer Technologies and Applications, San Diego, California, July 2004.

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OECD/NEA CSNI WGIAGE; Fourth International Conference on Fatigue of Nuclear Reactor Components

28th September-1st October, 2015, Sevilla, Spain

Low Cycle Fatigue Behavior of Modified 9Cr-1Mo Steel at Elevated Temperature

Preeti Verma Department of Metallurgical Engineering, Indian Institute of Technology, Banaras Hindu University,

Varanasi - 221005, India. preeti.rs.met12@itbhu.ac.in

P. Chellapandi

Nuclear & Safety Engineering Group, Indira Gandhi Centre for Atomic Research, Kalpakkam, Tamilnadu - 603102, India.

N.C.Santhi Srinivas

1Department of Metallurgical Engineering, Indian Institute of Technology, Banaras Hindu University, Varanasi - 221005, India.

Vakil Singh

Department of Metallurgical Engineering, Indian Institute of Technology, Banaras Hindu University, Varanasi - 221005, India. drvakilsingh@gmail.com

ABSTRACT

In this investigation low cycle fatigue behaviour of modified 9Cr-1Mo steel was studied in terms of cyclic stress response, deformation, and fracture behaviour; at RT, 300 and 600 °C, at different strain amplitudes from ±0.25% to ±0.50%, at a strain rate of 10-2 s-1. Irrespective of the strain amplitude and temperature, cyclic stress response of the material exhibited cyclic softening, following nearly stable response during the initial few cycles. At high strain amplitudes of ±0.375% & ±0.5%, the initial stability of stress up to a few cycles, was followed by continuous softening till failure. On the other hand, at the lowest strain amplitude of ±0.25%, there was stabilized stress response during larger number of initial cycles, followed by mild hardening and subsequent continuous softening. Coffin-Manson relationship was observed at all the test temperatures. Fracture surface revealed distinct striations, secondary cracking at all the strain amplitudes and temperatures. Oxidation of the alloy was observed at 600 °C and there was significant effect of it on crack initiation and propagation. TEM examination revealed high interaction of dislocations at second phase particles and lath boundaries. There was formation of dislocation cell/sub-grains in all the conditions, with appreciable difference in size of the cells. The size of the cell was found to increase with increase in temperature, at constant strain amplitude. The cell walls were not quite distinct at the lower strain amplitudes in respect of those at the high strain amplitudes. The observed cyclic softening is attributed to formation of dislocation cell structures.

Keywords: Modified 9Cr-1Mo steel, Low cycle fatigue, Cyclic softening, Oxidation, Dislocation cells.

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Introduction

Modified 9Cr-1Mo steel is a prominent material used in fast breeder reactor and very high temperature reactors for components like pressure vessel, steam generator components and reactor internals (fuel wrapper tubes) due to its high strength at elevated temperature and its good resistance against corrosion, irradiation embrittlement as well as irradiation void swelling [1,2]. The components of steam generators are often subjected to repeated thermal stresses, as a result of temperature gradients resulting during heating and cooling in start-ups and shut-down operation or during temperature transients [3-5]. This leads to low cycle fatigue (LCF) damage of the component. High temperature phenomenon of dynamic strain ageing accelerates the process of fatigue crack propagation and drastically reduces the fatigue life [3-5].

Various investigations have been carried out on LCF behavior of the 9Cr-1Mo steel at elevated

temperatures, mostly at 500 – 600 °C, at strain rates of 10-3 s-1 & 10-4 s-1 [1-9, 13-15]. Effect of temperature on low cycle fatigue behavior of modified 9Cr-1Mo steel, in the regime of high strain amplitude (±0.7% to ±1.2%) at strain rate of 10-3 s-1 was studied by Krishna et al [6] and found to be more pronounced at lower strain amplitudes. There was rapid initial softening, followed by gradual softening till failure. A similar trend was noticed at all the test temperatures and strain amplitudes. Softening at elevated temperatures was attributed to disappearance of most of the microstructural sub boundaries; characteristics of the tempered martensite and to decrease in density of dislocations. At 600 °C, the softening effect was directly related to decrease in kinematic stress (back stress) [7]. The cyclic softening at 500-600 °C, at strain amplitude of ±0.4% and the lowest strain rate of 10-4 s-1 was attributed to coarsening of precipitates [3]. Extensive crack branching and formation of secondary cracks was reported at high strain amplitude [5]. The steel was found oxidized at 600 °C; and the LCF life was reduced due to oxidation enhanced crack initiation and propagation. Secondary hardening in the cyclic stress response was reported at 600 °C at a strain amplitude of ±0.6% due to precipitation of very fine secondary precipitates of probably V(C, N) [4].

Effect of environment on low cycle fatigue behavior of this material was also studied in

normalized and tempered condition [8]. There was nearly a 2.5 times increase in fatigue life in vacuum in comparison to that in air, reflecting the detrimental role of oxidation on fatigue life at 600 °C. The rates of softening were found to be similar, both in vacuum and air. This suggests that the softening rate was independent of presence/absence of surface oxides and confirmed that the softening was caused by the internal phenomena of annihilation and rearrangement of dislocations and coarsening of strengthening carbides. Kim et al. [9] also studied the effect of environment on fatigue life and examined coarsening of carbides, using small angle neutron scattering. A sharp drop in scattered intensity was observed at high scattering angle in the fatigued samples, as compared to that in the normalized and tempered condition and it was attributed to disappearance of fine carbides in the cycled specimens.

This paper deals with LCF behavior of the modified 9Cr-1Mo steel at different temperatures (RT,

300 & 600 °C), in the regime of low strain amplitudes from ±0.25% to ±0.5%, at a higher strain rate of 10-2 s-1. The LCF results are discussed in terms of cyclic stress response, fatigue life, deformation, and fracture behavior.

Materials and experimental methods

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Modified 9Cr-1Mo steel was supplied from the Indira Gandhi Center for Atomic Research, Kalpakkam, India, in normalized & tempered condition. Normalising treatment had been given at 1060 °C for 1 h followed by air cooling and tempering was done at 780 °C for 1 h followed by cooling in air. The chemical composition of the steel is given in Table.1.

Table 1. Chemical composition of the modified 9Cr-1Mo steel (wt%)

LCF samples with gage length of 15mm, gage diameter of 5.5 mm, were fabricated from the heat

treated blanks. Schematic of the LCF specimen with dimensions is shown in Fig. 1. Low cycle fatigue tests were conducted in total strain controlled mode, in fully reversed triangular waveform (Fig. 2), using servo-hydraulic fatigue testing machine (Model: MTS 810), at different strain amplitudes, from ±0.25% to ±0.5%, at different temperatures (RT, 300 & 600 °C), at a strain rate of 10-2 s-1. Fracture surfaces of the tested samples were examined by scanning electron microscope (Model: FEI Quanta 200 FEG). Samples for TEM study were sectioned transversely from the region close to the fractured end, using slow speed diamond cutter. Thin discs of 3 mm diameter were electrolytically thinned down using twin jet electropolisher (Struers Tenupol-5) in 6% HClO4

and 34% n-butanol in methanol, at 20V, at temperature of -40 °C. Deformation behavior of the tested samples was examined by TEM (FEI Tecnai 20 G2).

Figure 1. Schematic of low cycle fatigue specimen.

Figure 2. Schematic of fully reversed strain cycle waveform used for low cycle fatigue tests.

Results and discussion

Microstructure

Transmission electron micrograph and corresponding diffraction pattern of the modified 9Cr-1Mo

steel in normalized and tempered condition is shown in Fig. 3. It is obvious from the micrograph that

Elements C Si Mn P S Cr Mo Ni Al Nb N V Fe

Wt. % 0.1 0.26 0.41 0.018 0.002 9.27 0.95 0.33 0.013 0.074 0.044 0.21 Bal.

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the steel has tempered lath martensite structure inside the prior austenite grains. Second phase precipitates may be seen along the lath boundaries, prior austenite grain boundaries, and also within the laths. These precipitates were characterized and identified as M23C6 & MX (X=C, N) [10], in agreement with earlier observations [3,7].

Figure 3. (a) TEM micrograph of the modified 9Cr-1Mo steel in normalized and tempered condition, (b) corresponding diffraction pattern.

Cyclic stress response

Effect of temperature on cyclic stress at different strain amplitude from ±0.25% to ±0.5% at strain

rate of 10-2 s-1 is shown in Fig.4. It may be seen that there was decrease in the cyclic stress and increase in the rate of cyclic softening, with increase in temperature. Irrespective of the test temperature there was stabilized stress response up to 10 initial cycles, followed by mild hardening and subsequent continuous softening till fracture, at the lowest strain amplitude of ±0.25% (Fig.4 a). At high strain amplitude of ±0.5% at 600 °C cyclic softening was observed from the first cycle till failure, while at room temperature and 300 °C there was stabilized stress response up to 20 initial cycles, and was followed by continuous softening. The softening was more pronounced and rapid when the strain amplitude was high.

At lower strain amplitude the initial hardening was mainly from the interaction between

dislocation and precipitates. It may be seen from fig.3 that there was lath marteniste inside the prior austenite grains. High density of dislocation may also be seen in some of the laths. Due to fatigue testing at room temperature at strain amplitude of ±0.25%, the lath martensite was transformed into dislocation cell subgrain structure (Fig. 5). Similarly transformation of lath structure in to dislocation cell/ subgrains is evident also at both 300 and 600 °C. Formation of dislocation cell structure at 600 °C may be seen from Fig 5(c,d). The cell size was found to increase with increase in temperature. Figs. 5 (c & d) also confirm coarsening of precipitates inside the grains, tested at 600 °C. The continuous cyclic softening may thus be understood in terms of transformation of lath structure in to cell structure and coarsening of precipitates accompanied by cell sub grain formation at 600 °C.

a b

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Figure 4. Effect of temperature on cyclic stress response at a strain rate of 10-2 s-1 at different strain amplitude (a) ±0.25% & (b) ±0.5%.

Cyclic softening in this steel has been ascribed also to different phenomena like coarsening of

dislocation cell structure, precipitate coagulation, significant decrease in dislocation density, coarsening of both M23C6 and MC type of precipitates, and dissolution of fine precipitates [3-6], and these are in line with the present investigation.

The softening in this steel at elevated temperature of 600 °C may be correlated to decrease of the

kinematic stress as reported by Founier et al. [7]. This stress arises from ‘directional and long-range obstacles to the movement of dislocations. Therefore, grain and subgrain boundaries (through a dislocation pile-up mechanism), more generally all the microstructural heterogeneities (microstructure of dislocations, precipitates, etc.) are sources of kinematic hardening. The decrease in kinematic stress suggests that the softening arises from the disappearance of microstructural heterogeneities [7].

a b

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Figure 5. TEM micrograph of the fatigue tested sample at a strain amplitude of ±0.25% at a strain rate of

10-2 s-1 at different temperatures (a, b) RT, (c, d) 600 °C.

Low cycle fatigue life

Low cycle fatigue behavior is shown by ∆εp/2 vs 2Nf plot, based on Coffin–Manson relationship

(Fig. 6). The fatigue life at all the test temperatures was found to obey the Coffin- Manson relationship [11]. At high strain amplitude fatigue life was observe to decrease with increase in test temperature, from RT to 600 °C, while at the lowest strain amplitude of ±0.25% fatigue life was decreased at 300 °C. A decrease in the plastic strain amplitude with increase in temperature from 500-600 °C was observed at a strain rate of 10-3 s-1 by Nagesha et al [5] and was attributed to occurrence of dynamic strain ageing. However, in the present investigation the plastic strain amplitude was found to increase with increase in test temperature. This may be due to higher strain rate than that required for the occurrence of dynamic strain ageing.

Figure 6. Coffin-Manson plots corresponding to different temperatures, at strain rate of 10-2 s-1.

c d

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Fracture behavior

Fracture surfaces of the fatigue samples tested at different temperatures of RT, 300 & 600 °C at

strain amplitude of ±0.25% are shown in Fig. 7. It may be seen from these fractographs that there was cracking at all the test temperatures. Oxide layer is non-conducting in nature and metallic specimens with oxide may show charging. No charging was observed from fracture surface of the specimen tested at RT whereas there was significant charging from fracture surface of the specimen tested at 600°C (Fig. 7c). Thus it is obvious that there was considerable oxidation at 600 °C. Oxidation is known to have detrimental effect on the process of crack initiation and propagation during fatigue at elevated temperatures [3,5,12]. The oxides formed at the crack tip accelerate the process of crack propagation at 600 °C. The drop in the fatigue life at 600 °C may thus be attributed to the oxidation phenomenon.

Figure 7. Fracture surface of the specimens fatigue tested at strain amplitude of ±0.25% at a strain rate of 10-2 s-1 at different temperatures: (a,) RT, (b) 300 °C, & (c) 600 °C.

Conclusions

The following conclusions may be drawn from the present investigation:

Modified 9Cr-1Mo steel, showed lath martensitic structure along with M23C6 precipitates along the prior austenite grain boundary and at lath boundaries in the normalized and

b

c

a

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tempered condition. Distribution of fine precipitates MX (X=C, N) was observed also within the lath martensite.

At high strain amplitudes of ≥ ±0.375% there was stabilisation of cyclic stress during the initial cycles and was followed by continuous softening till failure. On the other hand, at the lowest strain amplitude of ±0.25% there was stabilized stress response during large number of initial cycles, followed by mild hardening and subsequent continuous softening till failure.

Cyclic stress level was decreased with increase in test temperature. The observed cyclic softening may thus be attributed to formation of dislocation cell

structures. Oxidation was observed at 600 °C and it had detriment effect on fatigue life.

References

1. D.W. Kim, S.S. Kim, Int. J. Fatigue 36 (2012) 24–29. 2. R.L. Klueh, A.T. Nelson, J. Nucl. Mater. 371 (2007) 37. 3. A. Nagesha, R. Kannan, G.V.S. Sastry, R. Sandhya, V. Singh, K.B.S. Rao, Mater. Sci. Eng. A 554 (2012) 95–104. 4. V. Shankar, M. Valsan, K.B.S. Rao, R. Kannan, S.L. Manna, S.D. Pathak, Mater. Sci. Eng. A 437 (2006) 413–422. 5. A. Nagesha, M. Valsan, R. Kannan, K. Bhanu Sankara Rao, S.L. Mannan, Influence of temperature on the low

cycle fatigue behaviour of a modified 9Cr–1Mo ferritic steel, Int. J. Fatigue 24 (2002) 1285–1293. 6. K. Guguloth, S. Sivaprasad, D. Chakrabarti, S. Tarafder, Low-cyclic fatigue behavior of modified 9Cr–1Mo steel at

elevated temperature, Mater. Sci. Eng. A 604 (2014) 196–206.

7. B. Fournier, M. Sauzay, A. Renault, F. Barcelo, A. Pineau, Microstructural evolutions and cyclic softening of 9%Cr martensitic steels. J. Nucl. Mater. 386–388 (2009) 71–74.

8. V. Shankar, V. Bauer, R. Sandhya, M.D. Mathew, H.J. Christ, Low cycle fatigue and thermo-mechanical fatigue behavior of modified 9Cr–1Mo ferritic steel at elevated temperatures. J. Nucl. Mater. 420 (2012) 23–30.

9. S. Kim, J.R. Weertman, Metall. Trans. A 19A (1988) 999-1007. 10. P. Verma, R.G. Sudhakar, P. Chellapandi, G.S. Mahobia, K. Chattopadhyay, N.C. Santhi Srinivas, V. Singh,

Dynamic strain ageing, deformation, and fracture behavior of modified 9Cr–1Mo steel. Mater. Sci. Eng. A 621 (2015) 39–51.

11. G.E. Dieter, Mechanical Metallurgy, McGraw-Hill Book Company (1988) pp. 295‒301. 12. V. Chawsal, G. Sashikala, S.K. Ray, S.L. Mannan, B. Raj, Mater. Sci. Eng. A 395 (2005) 251–264. 13. B. Fournier, M. Sauzay, A. Pineau, Micromechanical model of the high temperature cyclic behavior of 9–12%Cr

martensitic steels, Int. J. Plasticity 27 (2011) 1803–1816 14. B. Fournier, M. Sauzay, C. Caes, M. Noblecourt, M. Mottot, Analysis of the hysteresis loops of a martensitic steel

Part I: Study of the influence of strain amplitude and temperature under pure fatigue loadings using an enhanced stress partitioning method, Mater. Sci. Eng. A 437 (2006) 183–196

15. B. Fournier, M. Sauzay, C. Caes, M. Mottot, M. Noblecourt, A. Pineau, Analysis of the hysteresis loops of a martensitic steel Part II: Study of the influence of creep and stress relaxation holding times on cyclic behavior, Mater. Sci. Eng. A 437 (2006) 197–211.

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OECD/NEA CSNI WGIAGE; Fourth International Conference on Fatigue of Nuclear Reactor Components 28th September-1st October, 2015, Sevilla, Spain

Analysis and Impact of Recent Thermal Fatigue Operating Experience in the USA

Mike McDevitt Electric Power Research Institute, U.S.A, mmcdevitt@epri.com

Terry Childress

Duke Energy, U.S.A., terry.childress@duke-energy.com

Mike Hoehn Ameren, U.S.A., mhoehn@ameren.com

Robert McGill

Structural Integrity Associates, U.S.A., rmcgill@Structint.com

SUMMARY

Certain thermal fatigue mechanisms were not original considerations for LWR design and in-service inspection programs. By the mid 1980’s, these mechanisms had resulted in several through wall cracking events worldwide. Early thermal fatigue management programs focused on the specific events. However, by the mid 1990’s predictive models had been developed. Over the next two decades there were only three part-through wall thermal fatigue cracking events in the US. However, in the period between 2013 and 2015 the frequency of US events increased from less than two per decade to five per year. In response to this change, EPRI established a panel of utility and engineering representatives to analyze each event, and establish actions to ensure thermal fatigue cracks are detected well before exceeding ASME code allowable limits. This paper provides an overview of recent operating experience, the approach used to analyze these events, and the recommended thermal fatigue management program modifications. Key Words: Thermal Fatigue, Fatigue Operating Experience, Fatigue Management Background Thermal fatigue events of the 1980’s prompted the NRC to issue Bulletin 88-08 and other communications that established Licensee actions to ensure appropriate degradation management [1-5]. In the years since NRC Bulletin 88-08, the international nuclear industry invested substantial effort into better understanding thermal fatigue mechanisms and to produce additional guidance to assist utilities with identifying potentially susceptible piping and components [6-15]. By the mid 1990’s predictive models had been developed and the incidence of through wall thermal fatigue cracking events had decreased. In the two decades since establishment of Industry guidance, there were only three part-through wall thermal fatigue cracking events in the US. Thermal fatigue appeared to be adequately understood and well managed. Application of current thermal fatigue management guidance in the US is shown in figure 1.

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Figure 1. Application of EPRI-MRP Thermal Fatigue Management Guidelines In late 2013, two cracking events occurred in the US, including one forced outage due to through wall leakage. In 2014 and 2015 this trend continued with an additional eight fatigue cracking events including two that resulted in through wall leakage. In response to this abrupt change in frequency and severity of operating experience, the US Industry ‘Emergent Issue Protocol’ [16] was activated and a panel of utility and engineering representatives was established. The objectives of this panel were to analyze each of the recent events, identify knowledge and program gaps that precluded timely crack detection, and establish prompt actions to ensure thermal fatigue cracks are detected well before exceeding ASME Code allowable limits. Near term objectives of the panel did not include prevention of thermal fatigue. In general, susceptibility of a component to thermal fatigue is a property of the system design and operation. In many cases, cost effective measures for mitigation have not been developed and fatigue management relies on conservative prediction, timely detection and repair or replacement. The panel was also tasked with identifying the research necessary to better understand and effectively mitigate or manage the causal factors underlying the recent events. This longer term effort may reduce the occurrence of future thermal fatigue events. Description of Recent Thermal Fatigue Operating Experience in the US

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The following table summarizes recent fatigue operating experiences. All locations were subject to thermal stratification fatigue management programs. Each event offers insight into fatigue management program effectiveness; however not all events were fully attributed to thermal fatigue. Additional details for each event are discussed below.

Table 1. Summary of Recent US Fatigue Operating Events Event Date

Plant Design Event Method of

Discovery Learning Point

Nov 2013

B&W 2600 MWth

Cold Leg Drain Elbow weld 35% t-w

Circumferential (DH)

MRP-146 [11] Program

Examinations

Repeat event. Caused by a combination of fatigue and vibration modes

Nov 2013

B&W 2600 MWth

Cold Leg HPI Nozzle weld (H) 100% t-w

On-line Through-wall Leak

Vibration contributed to this event.

NDE failed detection

Apr 2014

Westinghouse 4-Loop

3400 MWth

Cold Leg HPI Nozzle weld (H)

85% t-w Axial

MRP-146 Program

Examinations

NDE program weaknesses prevented timely detection

Sep 2014

Westinghouse 4-Loop

3400 MWth

B-Loop Cold Leg HPI Nozzle weld (UH)

50% t-w Axial

Extent of Condition

Investigation

Location of crack was not anticipated by guidance

Sep 2014

Westinghouse 4-Loop

3400 MWth

C-Loop Cold Leg HPI Nozzle weld (UH)

50% t-w Axial

Extent of Condition

Investigation

Location of crack was not anticipated by guidance

Oct 2014 Westinghouse

4-Loop 3400 MWth

RHR Mixing Tee ~20% t-w various

MRP-192 [14] Program

Examinations

Cracking outside of current inspection zone guidance

Oct 2014 G-E BWR-6 3700 MWth

Through-wall cracking in RWCU regen heat exchanger mixing tee

On-line Through-wall Leak

Repeat leakage event Ineffective Maintenance

Program

Nov 2014

B&W 2600 MWth

Cold Leg drain elbow ~20% t-w (DH)

MRP-146 Program

Examinations

Repeat event caused by undiscovered mitigation

failure

Dec 2014

Westinghouse 3-Loop

2900 MWth

Through-wall cracking in CL drain elbow (DH)

On-line Through-wall Leak

Cyclic outflow operations not accounted for in

management

May 2015

Westinghouse 4-Loop

3400 MWth

RHR Thermal Mixing Tee Shallow circ.

Cracks to 2 inches long

MRP-192 Program

Examinations

Confined to areas of grinding during fabrication

Note: (UH), (H) and (DH) refer to the location of branch line attachment to main loop piping as upper (U), side (H) and Lower (DH) respectively

Detailed Description of fatigue operating events

November 2013 During planned examinations at this 2600 MWth, B&W designed plant, a circumferential indication was found in the Loop-B, Schedule 160, 316 stainless steel, cold leg drain (expanding) elbow to pipe weld. The indication was on the top of the pipe side weld between the elbow and the downstream horizontal pipe. The indication was determined to be a crack that initiated on the elbow intrados ID

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surface and progressed to approximately 35% through wall and 19 mm in length. The root cause was due to cyclic stress from plant heatup, cooldown, and thermal fatigue focused by weld geometry and a lack of fusion weld defect. Propagation of the crack was enhanced by static tensile stresses. Finite element analyses were performed on the Loop–B drain line piping, including details of the 1 ½ inch to 2-inch expanding elbow, the LOF defect, thermal stratification fatigue and piping supports. That analysis concluded that thermal fatigue would not have initiated and propagated the crack without other stress contributions. The plant is planning additional temperature and strain monitoring to identify all fatigue contributors. November 2013 This 2600 MWth PWR was forced off-line due to 0.3 lpm through-wall leakage in the Loop-B High Pressure Injection nozzle to pipe weld. The leak was found to be from a through wall circumferential crack approximately 38 mm long rotated slightly from the top of the safe end to pipe butt weld. The base materials are schedule 160 type 316 stainless steel joined by an ER308 butt weld. The cause of this crack was concluded to be vibration fatigue; however, this weld fell within the management guidance of MRP-146 and had been volumetrically examined in 2012 with no rejectable indications detected. Subsequent reviews of radiography performed in 2011 confirmed that the crack had gone undetected in the 2012 volumetric examinations. In this event, improvements in thermal fatigue NDE systems could have prevented component failure and the forced outage. As a result, volumetric examination process weaknesses were identified and procedure improvements were implemented by the Utility. As part of the Extent of Condition assessment, other susceptible components examined using the previous procedures were scheduled for reexamination at other sites owned by this Utility. April 2014. While performing planned Extent of Condition examinations using the improved NDE procedures, an 85% part through-wall axial crack approximately 1.1 inches in length was identified in the Loop-D, 1 ½ inch 304 stainless steel, Schedule 160 High Pressure Injection pipe to nozzle weld at this 3400 MWth Westinghouse 4-loop plant. The transgranular fatigue crack was located approximately at the bottom of the ID surface. The corrosion on the crack face indicated that it was not currently growing. The cause of this crack was determined to be thermal fatigue caused by cold in-leakage that had been occasionally present in the 1989 – 2005 timeframe. This is consistent with the stable appearance upon destructive examination. This weld had been examined as required by MRP-146 during the previous refueling outage with no rejectable indications detected. The improved volumetric examination is likely to have prevented an on-line leakage and forced outage event if cold in-leakage re-occurred. The utility decided to perform Extent of Condition exams of all like-kind HPI nozzle geometries regardless of MRP-146 susceptibility guidance. September 2014 (two different components with similar cracking) While performing Extent of Condition ultrasonic examinations on this 3400 MWth 4-loop Westinghouse plant, a 55% through wall, 19 mm long circumferential crack was discovered in the 1 ½ inch, 316 stainless steel, schedule 160 Safety Injection connection to the Loop-B cold leg, and three 53% through wall axial indications were detected in a similar connection to the Loop-C cold leg. These HPI nozzles are located on the top side of the cold legs. Cracking was identified in the weld between the vertical piping and the injection nozzle safe end, and extended into the safe end base metal. These locations were not considered susceptible to swirl penetration fatigue using the MRP-146 methodology. That assumption was based on test loop observations that swirl penetration and thermal cycling will not be sustained in piping less than 2-inch nominal pipe size. Furthermore, the indications in both HPI injection lines were located at the lower extension of vertical pipe weldment. This is outside of the MRP-146 examination volume for UH oriented branch lines. MRP-146 had failed to anticipate the potential interaction at this location in small diameter piping attached to the top of the main reactor coolant loop. The Utility’s rigorous Extent of Condition plans prevented component failure and forced outages, and

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revealed a latent gap in the US Industry’s Thermal fatigue management program. The cause of these indications was determined to be thermal fatigue due to the interaction of known cold in-leakage and primary coolant in the main loop. A significant contributing factor was the field conversion from a socket weld to a butt weld. October 2014 Multiple ID connected axial and circumferential cracks were detected during planned MRP-192 thermal fatigue examinations of the 8 inch, Schedule 20, type 304 stainless steel RHR mixing tee in a 3400 MWth 4-loop Westinghouse PWR. Broad areas of craze crack indications were also identified. Cracking was identified in the mixing tee base metal, and welds joining downstream as well as upstream branch piping. The maximum crack depth from the NDE was approximately 22%, which is consistent with an inspection based management program goal. Previous examination in 2008 did not detect degradation. However, the estimated fatigue usage in the period since 2008 was very low. Analyses of this event determined the cause to be from thermal fatigue. Cracking of upstream piping welds had not been previously reported in US mixing tee examinations, and was not included in the examination requirements of MRP-192. The operating conditions necessary to create upstream cracking have not been characterized and it is unknown whether it is possible to have upstream cracks without detectable cracking in the required MRP-192 examination volumes [17]. The 2014 examination employed improved NDE methods which may have contributed to detection. It is unclear whether these shallow cracks had arrested. October 2014 The Reactor Water Clean Up (RWCU) system of this 3700 MWth BWR-6 plant was secured due to a 75 mm long, through wall circumferential crack and leakage in the downstream weld of the 6-inch system mixing tee. This was a repeat of a previous through-wall leak in the same weld 6 years earlier. This RWCU mixing tee connects flow from the regenerative heat exchanger outlet with bypass flow around the heat exchanger. Under normal full power operation, mixed flow streams are prevented by an isolation valve. However, known isolation valve leakage permitted cold bypass to continuously enter the heated cleanup return at the tee connection. The 160°C temperature differential between these fluids is sufficient to result in an aggressive thermal fatigue mixing condition. The cause of this through-wall leakage event concluded that bypass isolation valve leakage resulted in thermal fatigue failure of the mixing tee weld. This event has characteristics in common with both MRP-192 governing fatigue usage at mixing locations in Residual Heat Removal systems and MRP-146 addressing cold in-leakage into hot fluid streams. In this instance, application of thermal fatigue management concepts would have promptly repaired isolation valve leak-by and prevented this leakage event. November 2014 While performing planned MRP-146 thermal fatigue examinations on a 2600 MWth B&W designed plant, several predominantly axial transgranular cracks ranging up to 11 mm in length and up to 17% through wall were detected in the extrados of a cold leg drain line elbow. Discontinuous, ID-initiated, circumferential cracks were also found along both edges of the elbow to horizontal pipe butt weld. The cracking was predominantly found along the bottom half of the pipe, and the cracks tended to be located in regions where the weld root pass geometry likely created some additional stress intensification. The elbow material is 1½ inch, Schedule 160 stainless steel with a nominal wall thickness of 0.281 inch (7.1 mm). Analysis of this event concluded the cause to have been thermal fatigue due to cyclic swirl penetration of reactor coolant into the normally stagnant horizontal branch line section. The cracking characteristics in this event were generally consistent with a previous leak event of this same elbow in 2000. Following that 2000 forced outage event, downstream piping was insulated to reduce differential cyclic temperatures and significantly reduce accumulation of fatigue usage. Inspection of the piping revealed that during the period since 2000, the mitigative insulation had been compromised. The compromised insulation was determined to have had a significant role in the event reoccurrence. Had the

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degraded insulation been identified to the thermal fatigue program owner, minor maintenance might have prevented this pressure boundary damage. December 2014 This 2900 MWth 3-loop Westinghouse plant was forced off line due to 0.2 lpm through wall leakage in the Loop-B cold leg drain line elbow. The 2” drain line is schedule 160 A376 Type 316 stainless steel pipe which is butt welded to the RCS nozzle and then drops 35 cm down to a 2” 90° schedule 160 A403 WP 316 stainless steel butt welded elbow. The 50 mm long, through wall crack was located on the side (face) of this elbow. Circumferentially oriented cracks approximately 5 mm in depth and 19 mm in length were identified in both the pipe and elbow sides of the circumferential weld toe. The cause of this through-wall leak was a thermal fatigue failure of the elbow. This component had been inspected 5-years earlier with no relevant indications detected. This line is used as an alternate source for drawing RCS chemistry samples. Sample flow rates are on the order of 4 lpm, and are insufficient to establish fully mixed flow in the horizontal 2-NPS piping. Periodic stratified laminar flow in the horizontal piping can introduce significant stresses in the area of observed cracking. MRP-146 does not account for fatigue usage contributions other than cyclic swirl penetration. This forced outage might have been prevented by improved NDE requirements and/or a more comprehensive assessment of operational fatigue contributions. May 2015 Shallow cracking was identified near the RHR thermal mixing tee downstream piping weld at this 4-Loop 3400 MWth Westinghouse PWR. An approximate 2 inch long circumferential indication was identified within ¼ inch of the weld root. The indication was located at approximately 70-degrees from the top of the downstream pipe. The cracking was transgranular with prevalent fatigue striations. The striation were typically less than one micron in depth. The cracking was limited to, and tended to be aligned with, the localized grinding marks associated with original construction. The cause of these cracks was from thermal fatigue. The shallow depth and broad area of cracking is consistent with craze cracking and may have been arrested. There is a potential that high resolution ultrasonic examinations may detect shallow, benign craze cracks and result in components being unnecessarily replaced. Overall Event Trend One concern that is distinct from the individual events is the possible indication of an emerging, upward trend in thermal fatigue failures caused by plant aging. The apparent trend upward is partially a result of improved detection. Measures that improve detection may temporarily increase the rate of crack detection, but don’t necessarily reflect an increased initiation rate. In addition, several recent events were repeat failures. Repeat failures are part of the historical trend and are not indicative of a new population of aging components. The trend in cracking events should decline as mitigation methods are implemented to prevent repeat failures. However even with these event groups removed from the trend, several recent cracking events remain as potential indications of an increasing trend of original plant components that are reaching fatigue life limits. Further evaluation of these events may reveal design and operational changes that can be used to reduce fatigue usage in similar components. An appropriate response to the potential of an increasing event trend is to elevate awareness and plant staff knowledge. Summary of recent event crack locations

Cracking due to thermal stratification fatigue has been identified and confirmed in a wide range of components that are subject to thermal fatigue management guidelines. Some cracking events occurred in components where initial corrective actions failed to prevent recurrence. Many cracks were detected at a relatively shallow and benign stage, while a number of cracks were undetected long after exceeding ASME Code allowable limits. The following figure shows locations of cracking since 2013 in the context of management guidelines (note that in several events, multiple cracks were observed in the identified

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location). As can be seen from this figure, no single design factor appears to underlie the cause of these events.

Figure 2. Summary of confirmed crack locations from October 2013 to October 2015

Analysis of Recent Operating Experience Each operating event was reviewed in detail by the Industry panel. The panel review included identification of the conditions that deviated from what is expected from an effective thermal fatigue management program. By further examining these deviating conditions, the panel identified potential causes of the inappropriate outcomes. The panel then identified candidate program changes that would have prevented the unwanted outcome. This process was repeated for each of the events. At the conclusion of this event level analysis, the panel selected the candidate changes necessary to prevent all of the unacceptable outcomes observed in the operating experience. In many cases, a single program change is expected to prevent unwanted outcomes of several events. These program changes were then proposed and vetted to broad cross section of the Materials Reliability Program (MRP) management team where refinements were made and implementation dates established. Revised program requirements were then published for US utility program implementation. The scope of these program changes are discussed below.

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In parallel with determining necessary fatigue management program changes, the panel also compiled a list of practices that may be used by plant staff to increase their program effectiveness. These practices are not at the level of program requirements, but are expected to contribution to strong program performance. The panel communicated these pant staff performance enhancements along with the revised program requirements. Finally, the panel identified areas where additional research and development would benefit thermal fatigue management programs. These recommendations are described below.

A. Improvements to thermal fatigue management programs

The following changes to US thermal fatigue programs will be implemented no later than fall 2016 refueling outages. These changes should minimize the potential for cracks exceeding allowable limits.

1) In one recent operating event, RHR mixing Tee cracks were observed in upstream mixing tee

welds. These cracks were also associated with widespread crazing, but were not expected in this location. Based on these observations, the recommended mixing-tee examination scope has been expanded to include upstream welds.

2) Recent operating experience has identified at least one through wall cracking event involving a

drain line where the fatigue failure was likely to have been accelerated by thermally stratified, cyclic chemistry sampling in the DH branch line. Program requirements were expanded to require examination of all lines subject to cyclic outflow operations except when explicit analyses of the combined fatigue effects demonstrate negligible fatigue usage.

3) Up Horizontal (UH) piping with NPS of 2-inches or less was previously exempted from

examination requirements. This was based on observed resistance to turbulent swirl penetration in mockup testing. Recent operating experience identified cracking in vertical pipe sections of these small diameter lines. Program requirements have been changed to require examination of small diameter UH lines that may be subjected to cold in-leakage. (Branch piping of diameters 1-inch NPS and less are exempted from examination).

4) Several recent operating events involved failure of NDE to detect cracks prior to exceeding

ASME Code allowable crack dimensions. In some cases ineffective NDE resulted in plant shutdown and outage extensions. New NDE process requirements have been established to increase communication between engineering program owners and examination personnel and to ensure adequate examination coverage and quality. In cases where physical limitations prevent full examination in accordance with approved procedures, corrective action items are required to be created in owner quality assurance programs. These items ensure that deficiencies are properly evaluated and appropriate steps are taken to maximize coverage.

B. Plant staff performance enhancements

The following observations are provided for consideration by engineers responsible for management of thermal fatigue:

1) Fatigue contributions due to periodic operations such as operating alignments and vibration,

must also be identified and assessed by fatigue program owners in the determination of appropriate inspection requirements.

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2) In several of the recent operating events, cracking re-occurred after modifications had been made to mitigate thermal fatigue. The potential for reoccurrence of cracking caused by degraded mitigation or unrecognized causal factors can be reduced by performing follow-up nondestructive examinations (NDE) and system inspections to validate effectiveness of mitigation and cause diagnoses.

3) Key assumptions made in determining component fatigue life and inspection requirements may

be impacted by design and operational changes. Responsible engineers should be aware of key assumptions and ensure they remain valid.

4) Repairs performed during original construction may increase local stresses and increase the likelihood of crack initiation and growth compared to the conditions assumed in the design. Responsible engineers can utilize repair history to identify locations of increased susceptibility.

5) Several recent operating events were caused by leakage through isolation valves. Fatigue

program owners should be aware of degradation in valves that function to prevent thermal mixing, and ensure prompt maintenance when needed. This practice is beneficial to any plant system.

6) Engagement between engineering staff and examiners in preparing for examinations, evaluation

of examinations results and debriefing of examination findings can improve NDE performance and reduce operating risks. Evaluation of indications by a Level III examiner can reduce risk of detection errors.

7) Piping and supports were initially designed without recognizing the potential effects of thermal

stratification fatigue. Consequently, thermal movement of these lines may be different than was anticipated in the original design. Engineering inspections can reveal evidence of excess load conditions by assessing pipe support condition and indications of pipe contact with the fixed environment.

C. Industry level research initiatives

The following recommendations were made to perform research that will improve future management program effectiveness and increase fundamental understanding of thermal fatigue.

1) Development of thermal fatigue management programs in Asia, Europe and the US were largely independent. Research is recommended to evaluate recent operating experience against international thermal fatigue management programs, compare management guidelines, and evaluate technologies used to develop and support international practices.

2) Develop simulation technology by constructing a physical model of a component that

experienced unexpected thermal fatigue. Employ the mockup to investigate the unexpected fatigue mode. Include sufficient instrumentation to provide high resolution benchmark data necessary to validate a Computational Fluid Dynamic (CFD) models.

3) Develop a CFD and piping heat transfer model of a reactor coolant system branch line

connection where thermal fatigue cracking was known to occur. The computational model may be used to investigate other thermal fatigue susceptibility factors and refining of examination requirements.

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4) Perform analyses and/or modeling to investigate the conditions leading to thermal cycling in upstream portions of thermal mixing tees. Use this information to refine future mixing tee examination requirements and better understand the significant hydraulic sensitivities.

Summary

Thermal fatigue management guidelines have been historically effective in preventing pressure boundary leakage. Recent operating experience in the US has revealed an increase in the frequency and severity of thermal fatigue related events. None of these events resulted in plant operation outside of component functional requirements, but a number of cracks exceeded allowable limits for continued operation. Analysis of these events by a panel of utility and engineering firm representatives have identified a recommendations and required actions to mitigate event significance. Full implementation of these actions is expected to commence with 2016 refueling outages. These near term actions will minimize the potential for exceeding allowable crack dimensions and prevent future leakage and forced outages. Research initiatives designed to reduce fatigue crack initiation were also identified. References

1. USNRC Bulletin 88-08: Thermal Stresses in Piping Connected to Reactor Coolant Systems, June 22, 1988

2. USNRC Bulletin 88-08, Supplement 1: Thermal Stresses in Piping Connected to Reactor Coolant Systems, June 24, 1988

3. USNRC Bulletin 88-08, Supplement 2: Thermal Stresses in Piping Connected to Reactor Coolant Systems, August 4, 1988

4. USNRC Bulletin 88-08, Supplement 3: Thermal Stresses in Piping Connected to Reactor Coolant Systems, April 11, 1989

5. USNRC Bulletin 88-11: Pressurizer Surge Line Thermal Stratification, December 20, 1988 6. Thermal Stratification, Cycling, and Striping (TASCS), EPRI, Palo Alto, CA, March 1994, TR-

103581 7. Interim Thermal Fatigue Management Guideline (MRP-24), EPRI, Palo Alto, CA, January 2001,

1000701 8. Materials Reliability Program Development of a Thermal Cycling Model for Un-isolable Piping

Configurations (MRP-97), EPRI, Palo Alto, CA, December 2003, 1003209 9. Material Reliability Program Thermal Cycling Screening and Evaluation Model for Normally

Stagnant Non-Isolable Reactor Coolant Branch Line Piping With a Generic Application Assessment (MRP-132), EPRI, Palo Alto, CA, December 2004, 1009552

10. User Manual MRP-170: EPRI Thermal Fatigue Evaluation per MRP-146, EPRI, Palo Alto, CA, March 2006 1013270

11. Material Reliability Program: Management of Thermal Fatigue in Normally Stagnant Non-Isolable Reactor Coolant System Branch Lines (MRP-146, Revision-1), EPRI, Palo Alto, CA, June 2011 1022564 (Revision 0 published in 2005)

12. BWRVIP-155:Evaluation of Thermal Fatigue Susceptibility I BWR Stagnant Branch Lines, EPRI, Palo Alto, CA, June 2006, 1013389

13. Material Reliability Program: Management of Thermal Fatigue in Normally Stagnant Non-Isolable Reactor Coolant System Branch Lines – Supplemental Guidance (MRP-146S), EPRI, Palo Alto, CA, January 2009, 1018330

14. Material Reliability Program: Assessment of Residual Heat Removal Mixing Tee Thermal Fatigue in PWR Plants (MRP-192, Revision 2), August 2012, 1024994

15. BWR Vessel & Internals Project, Assessment of Mixing Tee Thermal Fatigue Susceptibility in BWR Plants, (BWRVIP-196 Revision 0), EPRI, Palo Alto, CA September 2008, 1016570

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16. Guidance for Management of Materials Issues, Nuclear Energy Institute, Washington DC: May 2003. NEI, 03-08

17. Utanoharu, Nakamura, Miyoshi and Kasahara, “Numerical Simulation of Long-period Fluid Temperature Fluctuation Downstream from a Mixing Tee”, Proceedings of the 10th International Topical Meeting on Nuclear Thermal-Hydraulics, Operation and Safety (NUTHOS-10), NUTHOS10-1059, Okinawa, Japan, December 14-18, 2014”

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OECD/NEA CSNI WGIAGE; Fourth International Conference on Fatigue of Nuclear Reactor Components

28th September - 1st October, 2015, Sevilla, Spain

Study and Methodology Development for Cyclic Loading Application toFatigue Analyses

AuthorVTT, Finland, otso.cronvall@vtt.fi

SUMMARY

This study concerns collection, review and development of cyclic loading methods applicable to bothdeterministic and probabilistic fatigue crack growth analyses of nuclear power plant (NPP) pipingcomponents. The scope of this study concerns mainly thermal high-cycle loading. A representativecase of this is turbulent mixing of two water flows having different temperatures in NPP piping Tees.This study reviews the most relevant application methods for cyclic thermal loading given in nuclearcodes and rules as well as most promising methods found from fitness-for-service procedures andscientific literature. The developed new application method for cyclic loading is compared to acorresponding existing one in a computational example concerning fatigue induced crack growth in arepresentative NPP piping Tee.

Keywords: Fatigue, high-cycle, thermal loading, NPP piping.

1. Review of application methods for thermal cyclic loading in fatigue analyses of NPPcomponents

A review of application methods of thermal cyclic for fatigue analyses of NPP components ispresented in the following. The most significant application methods are covered, thus the scope is notexhaustive. The considered methods are from the following sources:

national rules, codes and standards; U.S. ASME code [1, 2, 3, 4], German KTA rules [5, 6],British standard BS 7910: 2005 [7], and French Approach in RCC-M code [8, 9],

fitness-for-service procedures; FITNET procedure [10], SSM handbook [11], and API 579procedure [12],

research results; developments in U.S. [13, 14, 15, 16, 17, 18], developments in Japan [19, 20,21, 22, 23, 24, 25], THERFAT project [26, 27], Extended THERFAT approach [28, 29, 30,31], and developments in VTT this far [32].

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The comparison of the above mentioned loading application methods has certain limitations. Nationalrules, codes and standards as well as most of the fitness-for-service procedures present fatigue designprocedures, which contain conservative assumptions concerning cyclic loading. This is because in thedesign phase there are no measured data on loading. On the other hand, the covered researchdevelopments and some of the fitness-for-service procedures provide methods for cyclic thermalvariable amplitude loading which are less conservative. However, they require prior information onloading as they concern the operational phase, when there already are measurement data onexperienced loads.

1.1. National rules, codes and standards

The fatigue loading application methods in the U.S. ASME code Article NB-3000 [1], German KTA3201.2 [5], British standard BS 7910: 2005 [7] and French RCC-M code Paragraph 3200 [8] do notconsider the chronological order of the load cycles. Instead, the computation of the cumulative fatigueusage factor is a simple algebraic sum covering all considered load cycles. In addition, the load cyclesare to be conservatively summed up in the most severe order. These fatigue dimensioning procedurescontain also other conservative features, through incorporation of safety factors and conservativedefinition of the fatigue strength curves. Thus, these procedures are not suitable for realisticapplication of cyclic thermal variable amplitude loading involving crack growth up to pipe leak/break,because in such cases the chronological order of the load cycles should be preserved and the avoidanceof unnecessary conservatism is important.

1.2. Fitness-for-service procedures

Of the fatigue loading application methods described in the FITNET procedure [10], the time historysequences description does consider the chronological order of the load cycles, whereas the histogramdescription and the power or energy density spectrum descriptions do not. The applicability of thelatter two methods for application of cyclic thermal variable amplitude loading involving crack growthup to pipe leak/break is questionable, because in such cases the chronological order of the load cyclesshould be preserved and the avoidance of unnecessary conservatism is important. However, in case ofpower or energy density spectrum approach, if the load cycles are picked randomly, whichcorresponds to loading conditions in NPP piping mixing points, it would make this method applicableto associated variable amplitude fatigue analyses. The time history sequences description appearssuitable as such for application of cyclic thermal variable amplitude loading.

As for the fatigue analysis procedure in the SSM handbook [11], even though it takes into account thecrack growth up to pipe leak/break, it omits the application of cyclic thermal variable amplitudeloading. On the other hand, the procedure does not limit or restrict the choice for application of thecyclic loading.

Like in most national rules, codes and standards, the application methods in API 579 [12] do notconsider the chronological order of the load cycles. Instead, the computation of the cumulative sum ofthe usage factors is a simple algebraic sum covering all considered load cycles. In addition, the loadcycles are to be conservatively summed up in the most severe order. This fatigue dimensioningprocedure contains also other conservative features, through incorporation of safety factors and

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conservative definition of the fatigue strength curves. Thus, this procedure does not apply for realisticapplication of cyclic thermal variable amplitude loading involving crack growth up to pipe leak/break.

1.3. Research developments

In the U.S., Pirson and Roussel [16] present an evaluation approach for thermal cyclic loading.According to it, this loading is controlled by several parameters. Screening criteria and evaluationmethods are proposed. These methods primarily deal with the thermo-hydraulic loading problems. Thelocation, magnitude and frequency of thermal load cycling are determined along with heat transferproperties. These load descriptions are intended for input to stress models. However, computationalapplication methods for thermal variable amplitude loading are not provided. More recently, a finalthermal fatigue management guideline was published in 2005, see ref. [18]. It providesrecommendations for evaluation, monitoring, inspection, and mitigation of thermal fatigue. This workis a continuation of the TASCS work [14]. The guideline recommends using monitoring/modelling togenerate loads to perform cumulative usage factor analyses. However, the guideline does not provideany computational application method for thermal variable amplitude loading.

In Japan, the Japan Society of Mechanical Engineers (JSME) has published a set of guidelines toaddress high-cycle thermal fatigue of NPP piping [20, 21, 22, 23]. Therein, two specific cases aredescribed in detail, namely thermal striping in a mixing Tee with hot and cold water, and thermalstratification in a branch pipe with a closed end. The reduction effect on the fluctuating temperaturedue to heat transfer at the surface of the pipe wall shall be taken into consideration. The frequency ofthe thermal loading is conservatively assumed to be that causing the most severe fluctuating thermalstress. Thus, these guidelines do not apply for realistic application of cyclic thermal variable amplitudeloading involving crack growth up to pipe leak/break, because in such cases the chronological order ofthe load cycles should be kept and the avoidance of unnecessary conservatism is important.

The THERFAT project [27] resulted in proposing a 4 level approach for application of thermal cyclicloading in NPP Tees. Level 1 is a simple temperature fluctuation range screening criterion. In theLevel 2 approach, also called the SIN-method, the loading history consisting of load cycles withvarying amplitudes is replaced with a constant amplitude loading. Thus, SIN-method does not reallyconsider the chronological order of the load cycles. Then, the computation of the cumulative sum ofthe usage factors is a simple algebraic sum covering all considered load cycles. In addition,conservatively only the most severe load cycle is to be used in the computations, i.e. that giving thehighest fatigue usage factor value as based on the fatigue strength curves. Thus, the suitability of thismethod for realistic application of cyclic thermal variable amplitude loading involving crack growthup to pipe leak/break is questionable. As for levels 3 and 4, their detailed development was left as afuture research issue.

The extended THERFAT approach [28] presents 5 levels for application of thermal cyclic loading inNPP Tees. As for Level 1 and 2 methods, they are the same as those by the THERFAT project [27].The part in Level 3 method corresponding to the application of the thermal loading is the same as thatin Level 2 method. As for Level 4 and 5 methods, which are the most advanced ones, the powerspectral density (PSD) procedure is used for application of thermal loading. This appears as a feasibleapproach, because it takes into account the varying of both the frequency and amplitude of the thermalcyclic loading. As the method is probabilistic, it does not really consider the chronological order of theload cycles. But this is not a drawback, as in NPP piping mixing points the behaviour of thermal

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loading is more or less random by nature. However, the application of this procedure is quitelaborious, involving several steps of computation. Moreover, to reach sufficient accuracy and to beable to apply the approach at all, quite detailed input data are needed, from actual measurementsand/or from computational fluid dynamics (CFD) analysis results. Thus, the feasibility of thisprocedure for application of cyclic thermal variable amplitude loading involving crack growth up topipe leak/break is good in terms of correspondence with reality, but limited because of its complexityand due to large amount of required detailed input data.

The strength of the VTT approach by Hannink and Timperi [36] for application of thermal loading atNPP piping mixing points is that it delivers continuous and time dependent thermal loads fromdiscrete data. On the other hand, it is limited to consider only one component surface point. Theapproach is based on reproducing the fluid-temperature statistics from actual measurements or CFDsimulations at locations near the component wall. The basic concept relies on the approximation oftemperature fluctuation fields with linear superposition of wave functions. Thus, to reach sufficientaccuracy and to be able to apply the approach at all, quite detailed input data are needed.Consequently, the feasibility of this method for application of cyclic thermal variable amplitudeloading involving crack growth up to pipe leak/break is good in terms of correspondence with reality,but limited due to large amount of required detailed input data.

1.4. Summary of application methods for thermal cyclic loading

A summary of the review of the application methods for cyclic loading used in thermal fatigueanalyses of NPP components is presented in Table 1.4.1.

Table 1.4.1. The suitability of the covered methods for application of cyclic thermal variableamplitude loading in NPP piping mixing points. Notations: CUF is cumulative usage factor, NA

is not applicable, LA is limited applicability, AP is applicable, and LC is load cycle.

Reference Approach/model ApplicabilityASME NB-3000 [1] CUF as algebraic sum conservative, no LC chronology: NAKTA 3201.2 [5] CUF as algebraic sum conservative, no LC chronology: NABS 7910: 2005 [7] CUF as algebraic sum conservative, no LC chronology: NARCC-M Paragraph 3200 [8] CUF as algebraic sum conservative, no LC chronology: NAFITNET procedure [10] time history sequences realistic, LC chronology: AP

histogram description conservative, no LC chronology: NApower/energy density spectrum realistic, random order of LCs: AP

SSM handbook [11] user providesAPI 579 [12] CUF as algebraic sum conservative, no LC chronology: NADevelopments in US [13, 15] user providesJSME Guidelines [24] most severe constant amplitude conservative, no LC chronology: LATHERFAT project [27] SIN-method conservative, no LC chronology: LAExtended THERFAT [28] Level 3 conservative, no LC chronology: LA

Level 4 realistic, random order of LCs: APLevel 5 realistic, random order of LCs: AP

Developments in VTT [32] power spectral density realistic, based on simulated or measuredorder of LCs: LA

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2. New method for probabilistic application of cyclic loading

The new method for probabilistic application of cyclic thermal loading is described in the following.The development of the method presented in the VTT report [33] by the author of this article.

The numerical analyses required to solve the stress distributions through the piping component wallscaused by turbulent mixing of waters of differing temperatures are very complex and computationallylaborious to perform. Firstly, advanced CFD analyses are required to solve the time dependenttemperature and pressure distributions of the flow, as well as the distributions of the heat transfercoefficient values between the flow and the surface of the component wall. With efficient modernpersonal computers (PCs) having large memory capacities such analyses still take several weeks ofcalendar time, but the actually simulated time typically results in less than a few minutes. Secondly,advanced finite element analyses (FEAs) are required to solve the time dependent stress distributionsthrough the piping component walls. The transfer of the CFD results to be used as a part of the inputdata needed in the following FEAs has its own difficulties as well, as the CFD and FEA elementmeshes typically differ considerably from each other.

The uncertainties concerning the estimation of the thermal load cycles in NPP piping mixing pointsinclude:

difficulties and inaccuracies in modelling correctly the turbulent mixing phenomena,

difficulties in defining the heat transfer factor values between the fluid and the pipe wall.

2.1. Steps of developed method for application of cyclic thermal loading

A more robust but still realistic method for application of the cyclic thermal loading in the NPPmixing points has been developed due to two reasons. Firstly, in practical fatigue analyses it iscomputationally too costly and time consuming to carry out detailed 3D CFD and FEAs. Secondly, allexisting more straightforward and/or analytical fatigue application methods are overly conservative forhigh-cycle thermal loading in NPP mixing points. Due to this the cracks grow through wallunrealistically quickly in the computations.

The steps of the developed new method for probabilistic application of cyclic thermal loading are:

Step 1 The range of the thermal loading is taken as 80 % of the total temperature difference ofthe two mixing fluids.

Step 2 Screening of the range of thermal loading by checking does it exceed the thresholdvalues.

Step 3 The shape of the temperature load cycles against time is assumed as sinusoidal.

Step 4 The longest possible duration of a load cycle is assumed to be the turn over time, ascomputed according to Chapuliot et al. [34], and the shortest possible duration of a loadcycle is assumed to be 0.1 s.

Step 5 To produce a discrete approximation of the load cycle duration range obtained in Step4, five (or more) representative fluctuation frequencies are selected so that they coverthis range from almost start to almost end.

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Step 6 The heat transfer coefficient values are computed with the Colburn correlation [35].

Step 7 Computation of temperature distribution through component wall for each selectedrepresentative fluctuation frequency.

Step 8 Computation of stress cycles through component wall for each selected representativefluctuation frequency.

Step 9 Assembly of a long enough loading sequence by adding to consecutive orderrepresentative load cycles (as corresponding representative fluctuation frequencies)otherwise at random, but when the load cycle causing the most severe stress range ispicked, adding that twice in a row.

2.2. Reasoning behind developed new application method

The reasoning behind the steps of the new method is described in the following.

As there is no simulated or measured data on the varying of the temperature fluctuations, it is assumedthat it corresponds to 80 % of the total temperature difference of the two mixing fluids, as according toTHERFAT [27] project recommendations. This is still a conservative assumption, as it concerns allthermal load cycles, while in reality for part of them the temperature range is less than this maximumvalue.

To see if it is necessary to conduct the fatigue analysis in the first place, it is screened whether therange of thermal loading exceeds the threshold values given in THERFAT [27] projectrecommendations or not. The screening criterion for austenitic materials in turbulent mixing in Tees is

T = 80 ºC. The screening criterion for ferritic steels in turbulent mixing in Tees is T = 50 ºC,reflecting the lower endurance limit of such steels and the greater uncertainty concerning theenvironment effect on fatigue strength.

The shape of the temperature load cycles against time is assumed as sinusoidal, as according toTHERFAT [27] project recommendations. This is more realistic than to conservatively assume that theload cycles have a box shape, with vertical rises and drops, or nearly that shape, with very steep risesand drops.

The longest possible duration of a load cycle is assumed to be the turn over time, as computedaccording to Chapuliot et al. [34], and the shortest possible duration of a load cycle is assumed to be0.1 s, which is physically a short duration, but still possible.

As the distribution of the cyclic thermal fluctuation frequencies is not known, it is assessed to be evenwithin the specified range, which range was assessed in the previous step. To produce a discreteapproximation of this, five (or more) representative fluctuation frequencies are selected so that theycover the frequency range from almost start to almost end, this meaning that the start and end pointsare not included. This is because in reality the end point frequencies would occur much more seldomthan those in between them.

The values heat transfer coefficient, HT [W/(m2ºC)] are computed with the Colburn correlation [35].This correlation applies to fully developed turbulent flow in a smooth circular tube, e.g. NPP pipe.

Analysis code DIFF developed by VTT [36] is used for computing the stress distributions for straightNPP pipes. In DIFF, these computations are linear-elastic. The temperature distributions in the

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structure induced by thermal load transients are computed as a function of time with finite differencemethod. All material properties can be time dependent. The values of flow temperatures and heattransfer coefficients can be freely defined as a function of time. The effect of inner pressure is alsoadded to the resulting stress distributions.

A less conservative approach for assembly of a long enough loading sequence is applied. It consists ofadding to consecutive order representative load cycles (as corresponding to representative fluctuationfrequencies) picked otherwise at random, but when the load cycle causing the most severe stress rangeis picked, it is added twice in a row.

3. Computational analysis

The structure examined in this study is a typical Tee in a boiling water reactor (BWR) plant. Turbulentmixing of two water flows having different temperatures is assumed to occur in this Tee. It isconservatively assumed that a circumferential similar weld in the Tee run pipe is located in the mixingzone, in reality such welds are located away from that zone. Part of the needed input data here aretaken from an earlier VTT report [37]. To get a more distinctive model response, exaggerated loadingwas used. In reality, CFD analysis results have shown that during normal operation the thermal mixingloads are mostly of moderate scale in typical NPP piping Tees.

The computational analyses concern the following two application methods:

developed new method for application of cyclic loading [33],

SIN-method from THERFAT project [27].

The input data for the computational analysis are as follows:

for dimensions of BWR pipe cross-section, see Table 3.1,

base material is austenitic stainless steel SA-403 304, for material property data see Table 3.1,

considered flaw postulate is a circumferentially oriented semi-elliptic crack in the basematerial and opening to inner surface,

high-cycle fatigue is the considered degradation mechanism,

the Paris equation [38] is used for crack growth rate [mm/cycle] computations, for necessaryparameter values see Table 3.1,

for applied load data, see Table 3.2, and for load induced stress data, see Table 3.3,

fracture mechanics based crack growth computations are performed with VTTBESIT code,which comprises parts developed by the Fraunhofer-Institut für Werkstoffmechanik (IWM),Germany, and by VTT [39, 40, 41, 42, 43],

the assumed yearly time in operation is 8000 hours, corresponding to approximately 11months, thus leaving for the yearly maintenance outage and other possible times under shut-down approximately one month.

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Table 3.1. Main part of input data used in fatigue crack growth analyses.

Pipe cross-section Outer diameter [mm] Wall thickness [mm] ReferenceBWR Tee run pipe 405 20 [33]Material property At temperature of 20 C At temperature of 285 C Reference

yield strength 207 MPa 132 MPa [44]tensile strength 517 MPa 437 MPa [44]elastic modulus 195 GPa 176 GPa [44]thermal conductivity 14.8 W/m C 19 W/m C [44]specific heat 483 J/kg C 554 J/kg C [44]coeff. of thermal expansion 15.3 (1/ C) 1E-06 17.5 (1/ C) 1E-06 [44]VTT distribution 7850 kg/m3 7850 kg/m3 [44]Crack growth model Coefficient C Exponent n ReferenceParis equation 1.1025E-80 3.33 [11]

Table 3.2a. Assumed exaggerated temperature, pressure and flow rate load data concerningstationary operational conditions for the Tee.

Pipe Temperature [ C] Pressure [MPa] Nominal flow rate [kg/s]run 186 7.0 640branch 276 7.0 35

Table 3.2b. Computed thermal load fluctuation frequencies and load cycle durations within theassessed range of possible frequencies for the Tee run pipe.

Case name Position in the frequencyrange [%]

Frequency [Hz] Load cycle duration [s]

f1 10 3.361 0.298f2 30 1.444 0.693f3 50 0.919 1.088f4 70 0.674 1.483f5 90 0.533 1.878

Table 3.3. Axial stress ranges through wall for the five temperature load fluctuation frequenciesfor the Tee run pipe, with origin of radial coordinate at the inner surface.

Radius [mm] Axial stress ranges [MPa] for the five fluctuation frequency casesf1 f2 f3 f4 f5

182.5 81.9 88.8 93.8 116.0 153.5185.0 6.1 8.8 12.7 20.0 31.3187.5 5.1 5.6 6.2 6.7 6.9190.0 5.0 5.1 5.5 6.0 5.9192.5 5.1 5.2 5.4 5.8 5.5195.0 5.1 5.2 5.4 5.7 5.4197.5 5.1 5.2 5.4 5.7 5.4200.0 5.1 5.2 5.4 5.6 5.4202.5 5.1 5.2 5.4 5.6 5.4

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The results from the fatigue induced crack growth analyses are presented in Figures 3.1 and 3.2. Ascan be seen from the analysis results, the new VTT method is considerably less over conservative thanthe SIN-method. The crack growth rate through wall is more than twice faster with the SIN-methodthan with the VTT method.

Figure 3.1. Crack growth in through wall direction as a function of the number of load cycles[33]. Here twall [mm] corresponds to wall thickness.

Figure 3.2. Crack growth along the component surface direction as a function of the number ofload cycles [33].

4. Conclusions

This study concerns collection, review and development of cyclic loading methods applicable tofatigue crack growth analyses of NPP piping components.

The covered existing methods for describing cyclic thermal loading in NPP piping are taken fromnational rules, codes and standards, fitness-for-service procedures, and scientific literature. In them,only a few procedures are provided for realistic application of high-cycle fatigue loads.

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A more robust but still realistic method for applying the high-cycle thermal loading in the NPP mixingpoints was developed due to two reasons. Firstly, in practical fatigue crack growth computations it iscomputationally too costly and time consuming to carry out detailed 3D CFD and FEAs. Secondly, allexisting more straightforward and/or analytical application methods appear overly conservative forhigh-cycle thermal loading cases. Due to high frequency of this loading type, the cracks grow throughwall unrealistically quickly in the computations. As the distribution of the cyclic thermal fluctuationfrequencies is not known, in the new method it is assessed to be even within the possible range, whichrange is assessed separately.

The analysis results for the BWR Tee mixing point show that the VTT approach is considerably lessover conservative than the SIN-Method, as the crack growth rate through wall is more than twicefaster with the latter method. However, still the cracks grow in the computations through wall toorapidly, even though the loading was to some extent exaggerated. In reality, typical BWR Tees withmixing loads last in use without damage for several years, even decades. One reason for this is thethermal shields that are used in some Tees, which in addition to taking the thermal mixing loads alsodecrease their range and distribute them forward so that they are directed away from the inner surfacesof the branch and run pipe inner surfaces. The effect of such shielding components can be included inthe CFD analyses, but not by such straightforward methods as used in the presented analysis example.Thus, at least for the application of the high-cycle thermal loading in NPP piping mixing points, thenew VTT method still appears too conservative, though much less conservative than the SIN-methodand other similar straightforward procedures. On the other hand, the new VTT method could be moreapplicable to other types of thermal cyclic loading, such as thermal striping and thermal stratification.This remains as a future research issue.

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40. Busch, M. et al. KI-Factors and Polynomial Influence Functions for Axial and Circumferential Surface Cracks inCylinders. IWM-Report T 18/94, Fraunhofer-Institut für Werkstoffmechanik (IWM), October 1994. 41 p.

41. Busch, M. et al. Polynomial Influence Functions for Surface Cracks in Pressure Vessel Components. IWM-Report Z11/95, Fraunhofer-Institut für Werkstoffmechanik (IWM), January 1995. 88 p.

42. Vepsä, A. Verification of the stress intensity factors calculated with the VTTBESIT software. Technical ResearchCentre of Finland (VTT), Research Group Structural Integrity, Research Report TUO72-044578. 40+2 p.

43. Cronvall, O., Vepsä, A. Further development and validation of probabilistic analysis application VTTBESIT. VTTReport VTT-R-01837-12, Technical Research Centre of Finland (VTT), March 2012, Espoo, Finland. 49 + 7 p.

44. ASME Boiler and Pressure Vessel Code, Section II. 2005 Update of 2004 Edition.

CONTENT OF TEXT

BWR Boiling water reactor

CFD Computational fluid dynamics

FEA Finite element analysis

IWM Fraunhofer-Institut für Werkstoffmechanik

JSME Japan Society of Mechanical Engineers

NPP Nuclear power plant

PC Personal computer

PSD Power spectral density

VTT Technical Research Centre of Finland

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Mean Stress Effect on Fatigue Life and Dislocation Microstructures of 316L Austenitic Steel at High Temperature in Air and Water

Environment

P. Spätig, H.-P. Seifert

Laboratory for Nuclear Materials, Nuclear Energy and Safety Department, Paul Scherrer Institute, 5232 Villigen-PSI, Switzerland, philippe.spatig@psi.ch, hans-peter.seifert@psi.ch

M. Heczko, T. Kruml

Institute of Physics of Materials, Academy of Sciences of the Czech Republic, Zizkova 22, 616 62 Brno, Czech Republic, heczko@ipm.cz, kruml@ipm.cz

SUMMARY

The influence of mean stress effects on the fatigue behavior of 316L austenitic stainless steel was studied at 288 °C in air and light water reactor (LWR) environments characterized by high-purity, neutral water with 150 ppb dissolved hydrogen. Load-controlled experiments were performed to select mean stresses precisely. The results of the fatigue tests in air showed that the application of a positive or negative mean stress increases the fatigue life Nf. The effects of positive mean stresses in the water environment are much less pronounced. The mean stress effect in water appears somewhat different than in air, with a life reduction at low positive mean stress (< 20 MPa), followed by an increase at higher positive as well as at negative mean stresses. It was found that the so-called Fen factors, defined as Fen=Nf,air/Nf,water, are not constant when a positive mean stress is applied, in opposition to the zero mean stress case. This arises from the fact that the fatigue endurance is not the same in air and water in the presence of non-zero mean stresses. The TEM observations of the dislocations arrangements showed that with zero mean stress, planarity of slip prevails for specimens with small plastic strain amplitudes while a transition from planar to spatial dislocation structures occurs when plastic strain amplitude increases. The dislocation arrangement in samples with a positive mean stress of 50 MPa is clearly different from that in the other specimen with zero mean stress. In particular, no spatial structures and no dislocation-free regions were observed.

Keywords: load-controlled fatigue, mean-stress, air and light water reactor environment, dislocation microstructures 1. Introduction It is now well established that, when tested in light water reactor environment, a fatigue life reduction of the austenitic stainless steels can occur in comparison to the fatigue life in air [1,2]. The fatigue life decrease depends in particular on strain rate, temperature, strain amplitude and dissolved oxygen level, and is observed only if three threshold conditions are met simultaneously, namely when both the strain range and the temperature are above their respective threshold, and when the loading strain rate was below a minimum value [3,4].

Cyclic loading on pressure boundary components of light water reactors stems from changes in the overall configuration of the mechanical and thermal loading. As a rule, the design life of components should not exceed 105 cycles but is usually even less than several thousand, which requires testing in the low cycle regime in strain-controlled mode. Therefore, most available data were obtained with fully reverse strain-controlled uniaxial tests of constant strain amplitude,

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constant temperature, constant strain rate, with well-polished specimens and without the application of a mean stress or mean strain. Such ideal conditions are evidently quite different from those experienced by components in operation in nuclear power plants. These components can undergo cyclic deformation during service due to thermal stratification that can induce thermal fatigue [5], or to flow-induced vibrations [6]. In addition, the effect of mean stress on fatigue life in water environment has been identified as one of the issue that is not sufficiently documented and that needs to be addressed.

The activities undertaken in this study were designed to gain insight into the influence of mean stress on fatigue life of austenitic stainless steels both in air environment and boiling water reactor/hydrogen water chemistry environment. While the data and analysis presented constitute the first preliminary results of an on-going project, they are numerous enough to demonstrate general trends and interpretations.

2. Material The investigated material was a non-stabilized 316L austenitic stainless steel pipe with an outer diameter of 219 mm and a wall thickness of 23 mm. The seamless pipe was manufactured and processed according to the requirements of the ASME BPV Code. The processing sequences of the seamless pipe material consisted of hot working, solution annealing, water quenching to room temperature, pickling and grinding. The chemical composition of the material in the as-received condition is given in Table 1. The material had an average grain size of 35 m.

Table 1: Chemical Composition of the Investigated Austenitic SS (in wt.%).

Steel C Si Mn P S Cr Mo Ni N Nb Ti

316L 0.021 0.26 1.69 0.033 0.003 17.5 2.15 11.14 0.0601 0.012 0.003

3. Experimental Procedures 3.1. Fatigue testing

All the fatigue specimens were fabricated with a gauge length oriented along the axis of the pipe. The tests in air were carried out with round bar specimens of 8 mm diameter and 18 mm gage length. However, for the tests performed in high-temperature water environment, hollow specimens with a wall thickness of 2.5 mm and an outer diameter of 10 mm were used. The detailed specimen geometry can be found in [7]. The tests were run in load-controlled mode using a triangular waveform at a frequency of 0.17 s-1. With such a frequency, the testing was focused on the low-cycle regime, namely below Nf = 105, essentially for two reasons. First, from a practical point of view, a test performed at a frequency of 0.17 s-1 needs one week to reach 105 cycles, which basically precludes testing at conditions leading to Nf >> 105. Second, it is well known that for the austenitic stainless steels three concomitant threshold conditions need to be met for environmental effects on fatigue to occur. These conditions are a minimum strain amplitude of 0.1% - 0.15%, a strain-rate lower than 0.4 % s-1, and a testing temperature greater than 150 °C. As it will be shown below, the fatigue limit of the investigated material at 288 °C was estimated around 140 - 150 MPa. For load-controlled experiment, a stress amplitude of 150 MPa corresponds to a strain amplitude lower than 0.125% after several thousands of cycles. Therefore, to have the strain range condition for environmental effects well fulfilled, the testing was focused at stress amplitude larger than 150 MPa that were found to result in Nf

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smaller than 105. Typically, the strain-rates at Nf/2 were in the range 0.1 to 0.3 % s-1. The strain was measured with an extensometer attached to the specimens. Moderate mean stresses of few tens of MPa were selected.

In this work, Nf represents the number of cycles to break the specimens in two parts. For the test in water, in few cases, the experiment was automatically stopped with the occurrence of a leakage leading to a quick pressure drop in the loop. However, for load-controlled experiments, the number of cycles between the occurrence of leakage and the final failure is quite small, typically smaller than 100.

3.2. Water Loop Facility and Simulated Boiling Water Reactor/Hydrogen Water Chemistry

A detailed description of the water loop facility employed for this study can be found in [8]. The load-controlled fatigue tests were performed at 288 °C in air and in pressurized water environment characterized by high-purity, deoxygenated (nitrogen purging) water with 150 ppb dissolved hydrogen which is representative of boiling water reactor/hydrogen water chemistry. The conductivity in the inlet and outlet water was 0.055 S/cm and smaller than 0.07 S/cm, respectively. The hollow specimens were heated by the pressurized water, which circulates through them. Three different internal pressures were used: 80, 100 and 200 bars. These hollow specimens have a wall thickness of 2.5 mm and an outer diameter of 10 mm.

3.3. Transmission Electron Microscopy

The internal dislocation microstructures of the material were investigated by means of transmission electron microscopy (TEM). The spatial arrangement of dislocations in grains was determined using the technique of oriented foils. Thin plates were cut from the gage length of the bulk specimens by electric-discharge machining parallel to the loading axis. The samples were mechanically grinded to produce thin plates of 0.08 mm in thickness, which were then punched out to produce discs having a diameter of 3 mm. These were marked to indicate the loading direction. The discs were then electrolytically polished using a double jet device TenuPol2. The electrolyte was composed of 95% of acetic acid and 5% of perchloric acid. The polishing conditions were 90V-95V, 0.2 mA and temperature of 13°C to 16°C. Thereafter, samples were observed on the TEM Philips CM12 at 120 kV with a double tilt holder. The mark of the loading direction was aligned with respect to the holder axis in order to preserve the loading axis during observations. Dislocation structure was analyzed using different diffraction vectors. The Burgers vectors and the types of dislocations were determined using zero contrast conditions. Diffraction patterns and Kikuchi lines were used to determine the crystallographic orientation of the stress axis in individual grains. The Miller´s indexes were permutated so that the strain axis vector lay in or on the border of the basic stereographic triangle defined by the apexes [001], [011], [1̅11].

4. Results and Discussion

4.1. Fatigue test results

Figure 1 compares the fatigue behavior in load-controlled conditions at 288 °C, as obtained in air with round bar specimens and in water with hollow specimens. The red arrows in this plot of the stress versus life (-Nf) refer to runout tests. No apparent and systematic difference was observed between the round and hollow specimens tested in air. As far as the data obtained with the hollow

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specimens tested in water with 80, 100 and 200 bars are concerned, they also fall practically all along the same curve. At a =170 MPa, three tests were carried out at different internal pressure. As can be seen, the fatigue life appears quite insensitive to this last parameter. Therefore, the two trend lines in Figure 1 were respectively calculated by considering all the data in air without distinction between massive and hollow specimens, and all the data in water independently of the internal pressure. These fits through the experimental data were determined with a Langer equation of the type:

(1) b

a f fsB N

a stands for stress amplitude andfs for fatigue strength. The use of Eq, (1) is rather empirical and merely justified by the fact that it usually yields an acceptable fit to the experimental data. However, it is clear that the two datasets are not large enough to determine the three parameters (B, b and fs) of the equation accurately.

Figure 1: Stress-Life in Air and Water at 288 °C, without a

Mean Stress

Parameters of the fits: Air: a=58247 (Nf)-0.8+155 Water: a=34996 (Nf)-0.8+155

In order to get reasonable estimates of the Eq. (1) parameters, we used the following procedure. The three parameters were not determined simultaneously but they were adjusted one after the other. First, an approximation of fs, was simply done by a careful look at the data points in Figure 1, where one can easily conclude that decreasing the stress amplitude slightly below 160 MPa raises the number of cycles to failure in the range 106 or even higher. Hence, fs were arbitrarily taken at a fixed value of 155 MPa with an uncertainty of ± 5 MPa. The exponent b was determined in the second place by rearranging Eq. (1) as:

(2) a fs flog log B b log N

and by fitting log(a – fs) versus log(Nf), without taking into account the runout data. The fit was performed with the least squares method using the Levenberg-Marquardt algorithm. The results of these fits are shown in Figure 2 with fs = 155 MPa. The slope of the air-data (bair = -0.67) appears somewhat lower than that of the water-data (bwater = -0.86) and the standard error for bair and bwater is 0.13 (i.e. 20%). So it can be correctly argued that the difference between bair and bwater is irrelevant due to insufficient data. Indeed, more data are necessary to conclude that the

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environment has an effect on b, but the current data do not suggest a strong effect of environment on b. In addition, the same fits were also calculated for fs = 150 and 160 MPa to assess the effect of the fs uncertainty on b. From the six fits (air and water with fs = 150, 155 and 160 MPa), it was found that b -0.8 ± 0.2. Therefore, the fits to the data presented in Figure 1 were obtained by calculating B from Eq. (1) with b = 0.8 and fs = 155 MPa, assuming that bair = bwater.

Figure 2: Stress-Life in Air and Water at 288 °C, without a Mean Stress in the

log(a–threshold) versus log(Nf) Representation, with threshold = 155 MPa.

The influence of mean stress on fatigue life in air is illustrated in Figure 3 where moderate mean stresses were considered. The application of relatively modest positive mean stresses, 20 and 50 MPa, increases the fatigue life, in opposition to most proposed standard models characterizing the effect of mean stress. The unusual response of this material to a positive mean stress has been rationalized in terms of the primary and secondary cyclic hardening on the one hand, and on the cyclic softening on the other hand [9,7]. The effect of a positive mean stress of 20 MPa is relatively small and within the usual scatter observed in fatigue results. Nonetheless, the trend appears systematic and is confirmed by the data with a 50 MPa mean stress that shifts the fatigue life to even higher Nf. Thus, it can be concluded that the application of tensile mean stresses at 288 °C increases the fatigue life and fatigue strength. This finding is in line with results reported by Solomon et al. on 304L austenitic steel, where they showed that the application of a 100 MPa mean stress increases both the fatigue life and the fatigue strength by several MPa at 107 cycles for tests performed at 300 °C [10]. In order to determine the increase of the fatigue strength on our data, we assumed that the shape of the S-N curve is not affected by the effect of the mean stress, at least within the range of the available data. Thus fs was deduced from Eq. (1) by fixing the pair of parameters B-b to the same values as those obtained in air with m = 0 MPa, i.e. B = 58247 and b = 0.8. An increase of fs resulting from a mean stress is seen in Figure 3, where it was found to increase from 155 MPa for m = 0 MPa to 162 MPa and to 173 MPa for m = 20 and 50 MPa, respectively. As expected, a negative mean stress is also beneficial in terms of fatigue life. Even if only a single test was performed with a = 190 MPa and m = -20 MPa, an increase of the fatigue life by one order of magnitude was found indicating a strong effect of a compressive mean stress.

The results of the fatigue tests in water environment with mean stress are presented in Figure 4. The fits were constructed in the same way as those in air with mean stress. The shape of the S-N curve in water was also assumed to be unaffected by the mean stress by fixing the pair of

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parameters B-b to the same values as those obtained in water with m = 0 MPa, i.e. B = 34996 and b = 0.8. Only the fatigue limit fs was adjusted in Eq. (1). The datasets with m = 10, 20 and 50 MPa show a trend: the fatigue life is slightly reduced by the application of m = 10 MPa and 20 MPa while it increases for m = 50 MPa. Hence, qualitatively the fatigue response of the hollow specimens tested in water environment to the application of a mean stress is different from that determined with the massive specimens tested in air, where the fatigue life was found to increase for all mean stresses considered, either positive or negative. For the time being, the underlying physical reason for such a behavior is not completely clear. Nonetheless, we recently proposed that the life reduction at small positive mean stress arises from a small tension/compression asymmetry of the plastic strain accumulation in pressurized hollow specimens [9], owing to the triaxial stress state existing in the specimen wall.

Figure 3: Stress-Life in Air at 288 °C, with a

Mean Stress.

Figure 4: Stress-Life in Air and Water at

288 °C, with a Mean Stress.

In any case, the data shown in Figure 3 and in Figure 4 allows quantifying the environmental effect on fatigue for three different values of the mean stress: 0, 20 and 50 MPa. In oligo-cyclic strain-controlled fatigue conditions, Fen factors have been proposed and are commonly used for that quantification [11]. They are defined by the ratio of the fatigue life in air at room temperature to the fatigue life in water reactor environment. The Fen factors were found to depend on temperature, strain-rate, and dissolved oxygen content [12,13,14]. In this work, we calculated the Fen factors for the three cases mentioned above. We emphasize that the Fen factors reported in this work are defined differently because they were determined by the ratio of the fatigue life in air and environment taken at the same temperature, namely 288 °C. By expressing Nf from Eq. (1), one derives readily that:

(3) 1/b 1/b1/b 1/b

f ,air a fs,water a fs,waterair air

f ,water a fs,air water water a fs,air

N B BFenN B B

Interestingly, this equation shows that the Fen factor is constant only if fs,air = fs,water but depends on the stress amplitude otherwise. In particular, Fen diverges when the stress amplitude a approaches fs,air , if fs,air > fs,water. We found that the fatigue strengths were different in water and air environments for the two cases of positive mean stresses while they were equal with a zero mean stress. In Figure 5, the Fen factors were calculated according to Eq. (3) with the values of B and fs obtained from the corresponding fits presented in Figure 3 and

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Figure 4. With zero mean stress, the fatigue life reduction is about 2 (calculated Fen = 1.89). The application of a positive mean stress reduces more the fatigue life: the Fen factors are clearly above 2 over the stress range where the tests were carried out, becoming larger with the mean stress.

Figure 5: Fen Factor, without and with Positive Mean Stress.

A word of caution needs to be done here. Even if the fits in Figure 3 and Figure 4 look quite reasonable and reproduce well the trend of the experimental data, one has to recognize that they are based on a small number of data points. Thus, additional testing and experimental results may slightly modify the shape of the fits or the estimated fatigue strength, and consequently the dependence of the Fen factors presented here is subjected to future adjustments.

4.2. Transmission Electron Microscopy Observations

Characterization of dislocation arrangement was done on three tested fatigue specimens in water environment at the very end of their fatigue life. The name of the specimens and their respective fatigue testing conditions are given in Table 2. One specimen (BA111) was selected for a stress amplitude close to the fatigue limit, a = 150 MPa with zero mean stress. Note that specimen was fatigued for 106 cycles but did not fail. For the other two specimens a larger stress amplitude was chosen a = 190 MPa without mean stress (BA116) and with a positive mean stress, a = 50 MPa, (BA135). This selection of specimen was made to highlight possible difference in the evolution of the dislocation microstructure for well-distinct fatigue conditions

Table 2: TEM of Investigated Specimens with Fatigue Testing Conditions

Sample code Stress amplitude σa [MPa]

Mean stress σmean [MPa]

# of cycles to failure [-]

BA111 150 0 > 106 BA116 190 0 5711 BA135 190 50 9743

Characteristic dislocation structures observed in the sample BA111 are shown in Figure 6 where a planar arrangement of dislocations in an austenitic grain is apparent. One system of parallel bands

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of high dislocation density corresponds to localized slip on the primary slip plane. These individual dislocation-rich sheets are separated by areas free of dislocations. The distance between slip planes with high dislocation density is typically several micrometers. It is important to notice that the sheets are not distributed homogeneously and the dislocation density in the sheets varies appreciably.

Figure 6 shows the dislocation structure in a grain oriented favorably to double slip. Therefore, the dislocation bands produced by activity of two intersecting slip systems can be clearly distinguished in the image. It is obvious that the dislocations of two slip systems participate but the slip in one of these is more intensive. It is also visible that the dislocations from the two systems keep gliding on their slip planes and does not form dislocation walls. Planar dislocation structures, which correspond to this slip system (e.g. regular arrays of dislocations, stacking faults), are typical for low loading levels. Thus, dislocation arrangements as those presented in Figure 6 and Figure 7 were characteristic for all observed grains in the sample BA111.

Figure 6: Planar Dislocation Structure, a = 150 MPa and m = 0 MPa. Localized Slip on the Primary Slip System.

Figure 7: Planar Dislocation Structure, a = 150 MPa and m = 0 MPa. Localized Slip on Activated Two Slip Systems.

A series of images were obtained from the BA116 specimen deformed with a larger stress amplitude, a = 190 MPa, in order to clearly reveal differences in dislocation arrangements in comparison with those observed in the sample BA111. Detailed observations showed that the planar structure is also present, especially in the interiors of large grains (approx. 40 µm and larger). However, along with planar arrangement, several spatial dislocation structures were observed. For instance, characteristic dislocation structure observed in the area near grain boundary is shown in Figure 8. In the left side of the micrograph one activated slip system is clearly visible. In the center of image, almost at the grain boundary, 3-dimensional arrangement of dislocation structure originates. Dislocation-rich walls separate areas free of dislocations and form a structure which resembles the beginning of formation of so called cell structure. This type of structure is probably responsible for cyclic plastic strain localization.

In smaller grains where the influence of neighbor grains is more significant in the terms of stress, spatial dislocation arrangements such the one showed in Figure 9 were observed. Origin of dislocation structure reminiscent of so called wall/channel subdomains is present. It is clearly visible that the localization is not that well distinctive as in the bottom left of the micrograph

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where the transition into the cellular dislocation structure is observed. Again it is obvious that the cells are formed by dislocation-rich walls surrounding small areas with almost zero dislocation density. Place marked by the letter A in Figure 9 is shown in details in Figure 10 and in Figure 11. Localization of dislocations into the walls/veins is evident. In Figure 11, a section of a dislocation wall is well recognizable (marked by the letter B) in the left side of the micrograph.

Figure 8: Dislocation Arrangement, a = 190 MPa and m = 0 MPa, with Nascent 3D Structure.

Figure 9: Dislocation Structure, a = 190 MPa and m = 0 MPa in Small Grain.

Figure 10: Detailed View on Dislocation Structure, from Region A in Figure 11, a = 190 MPa and m = 0 MPa.

Figure 11: Localization of Dislocations into Spatial Arrangements, a = 190 MPa and m = 0 MPa.

The third typical dislocation structure analyzed corresponds to the specimen BA135 mechanically tested with a = 190 MPa and m = 50 MPa. This allowed a direct investigation of effect of non-

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zero mean stress on dislocation structure formation. Characteristic dislocation structures of that sample are shown in Figure 12 and Figure 13. Several differences between dislocation arrangement in samples BA116 and BA135 were observed. Firstly, it is important to notice that no spatial structures as walls, cells and veins were found in BA135. In Figure 12 one activated primary slip system could be clearly identified and is marked by “(111) trace” label. Secondary slip system is also partly visible in the center of micrograph where it intersects with primary system. The main difference compared to previous samples is that no dislocation free regions/bands are present and dislocations are distributed quite homogeneously in the grains. It is obvious that the dislocation density in the areas between slip planes is relatively high. A similar situation is observable in Figure 13 where the planar slip of dislocations in single slip system is present with relatively high dislocation density between the slip planes.

Figure 12: Homogeneous Distribution of Dislocations with Tendency to Planar Slip, a = 190 MPa and m = 50 MPa. Slip Localized on Two Activated Slip Systems.

Figure 13: Homogeneous Distribution of Dislocations with Tendency to Planar Slip, a = 190 MPa and m = 50 MPa. Localized Slip on the Primary Slip System.

TEM observations to investigate the formation of dislocation structures in austenitic stainless steels following cyclic plastic response are numerous, e.g. [15,16]. These dislocation structures are classified in two main groups: i) planar structures and ii) spatial or 3D structures. The formation of low-energy dislocation structures arranged in 3D (e.g. ladder structure, labyrinths or cells) necessitates the movement of dislocations on other planes than on the primary slip plane only. For lower loading levels when only primary dislocations are moving, cross-slip is required; the secondary slip systems participate for high loading levels. However, the stacking fault energy (SFE) in austenitic steels is quite low (lower than 0.020 Jm-2), consequently the dissociation distance between Shockley partial dislocations is large. According the Friedel-Escaig model [17], the cross-slip necessitates the recombination of Shockley partials but this is less probable when the dissociation is large. Therefore, dislocations in fcc metals with low SFE tend to slip on the same plane, without interaction with other dislocations moving on parallel slip planes resulting in planar structure [18].

Typical dislocation structures which are formed in 316L in symmetric tension-compression cycling with a wide interval of plastic strain amplitudes are described in [15]. In [15] it is shown that at low loading levels, only planar structures appear in 316L steel. This is also the case of BA111 specimen. Plastic strain amplitudes are relatively small and strain localization is negligible. A mixture of planar and spatial dislocation arrangements is formed in an intermediate

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interval of loading levels (specimen BA116) and at high loading levels, mostly spatial dislocation arrangements are present. Based on our observations it could be stated that dislocation structures in BA111 and BA116 follow a similar trend those studied in [15].

On the contrary, an almost homogeneous distribution of dislocations with very high density as that in the sample BA135 has not been observed in symmetric cycling loading. Significant effect of the non-zero mean stress probably leads to formation of new type of dislocation arrangements. In terms of understanding deformation mechanisms in material after environmental thermo-mechanical testing it could be worth to focus on further investigations of non-zero mean stress effect during this testing conditions.

5. Conclusions

This work was undertaken on a non-stabilized 316L austenitic stainless steel to investigate the mean stress effects on fatigue life in air and LWR environment at 288 °C, and to examine the development of the dislocation structures by TEM. Load-controlled fatigue experiments were performed. In air, positive (+20 and +50 MPa) and negative mean stresses (-50 MPa) were found to increase the fatigue life notably. This rather unusual effect of tensile mean stress was attributed to a primary and secondary cyclic hardening effect. The tests run in water with pressurized hollow specimens revealed a somewhat different behavior, where positive stresses of 20 MPa or less, reduced the fatigue life moderately, while an increase was observed for a mean stress of 50 MPa, as well as for compressive mean stress. All S-N curves were obtained by data fitting using Langer equation in both environments. With zero mean stress, the curvature of the S-N curves was shown to be affected by the water environment while the application of a mean stress induced a change in the fatigue strength. These two effects, changes of curvatures and of fatigue strength, were explicitly considered in the determination of the Fen factors for three cases, namely zero mean stress, and +20 and +50 MPa mean stress. It was outlined that, when the fatigue strength is modified by the mean stress, the Fen factors will become strongly dependent on the stress amplitude.

The preliminary TEM observations of the dislocation arrangement in 316L austenitic stainless steel after fatigue led to the following main conclusions. Regarding the zero mean stress, planarity of slip prevails for specimens with small plastic strain amplitudes while a transition from planar to spatial dislocation structures occurs when plastic strain amplitude increases. The dislocation arrangement observed in a sample with a positive mean stress of 50 MPa is clearly different from that in the other specimens with zero mean stress. In particular, a very high density of homogenously distributed dislocations was observed without spatial structures and without dislocation-free regions.

Acknowledgments

This work was realized within the frame of SAFE research project, for which the financial support of the Swiss Federal Nuclear Inspectorate (ENSI) is gratefully acknowledged. The financial support from Grant Agency of the Czech Republic, project 15-08826S is also gratefully acknowledged. The technical assistance and contribution to the mechanical testing of R. Schwenold at Paul Scherrer Institute is warmly appreciated.

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[16] Pham M.S., Solenthaler C., Janssens K.G.F., Holdsworth S.R., "Disloction structure evolution and its effects on cyclic deformation response of AISI 316L stainless steel", Materials Science and Engineering, A528, (2011) 3261.

[17] Friedel J., Dislocations and Mechanical Properties of Crystals, Wiley, NY, (1957), 330. [18] Wang B., Gon Z.G., Wang, "Cyclic deformation behavior of Cu±30 wt% Zn single

crystals oriented for single slip - I. Cyclic deformation response and slip band behavior", Acta Mater., 47, (1999), 307.

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Experimental and numerical analyses of turbulent mixing of coolant streams in a mixing tee

P. Karthick Selvam, Rudi Kulenovic, Eckart Laurien

Institute of Nuclear Technology and Energy Systems (IKE), University of Stuttgart

Pfaffenwaldring 31, 70569, Stuttgart, Germany

Abstract

High cycle thermal fatigue (HCTF) induced piping degradation caused by turbulent mixing of coolant streams at significant temperature differences in a mixing tee is a challenging scenario in the context of operational safety and structural integrity of components in a nuclear power plant (NPP). The difficulty lies, among other things, in determining the local thermal loads in the vicinity of T-junction, which could not be monitored adequately using plant instrumentation due to the complex nature of the underlying flow mixing phenomenon. To study the flow behavior in the vicinity of a mixing tee, an experimental facility named Fluid Structure Interaction (FSI) test facility was commissioned in University of Stuttgart. Hot and cold fluids flow in main and branch pipes, respectively. Flow mixing is also studied numerically using large eddy simulation (LES) approach to gain more insight into the nature of the underlying flow. This paper deals with the analyses of flow mixing for three cases with increasing mass flow rate ratio (main/branch) of 3, 4 and 5, respectively, having temperature differences (∆T) between fluids in the range 87 - 93 K. Flow mixing is incomplete in all the investigated cases due to the low velocity of cold fluid coming from branch pipe (Reynolds number: 3200 - 3500). This results in a thermally stratified flow behavior throughout the downstream region with an oscillating stratification layer. Temperature fluctuations, an important factor contributing to the risk of thermal fatigue, have the highest amplitudes near stratification layer ranging from 5.2 – 6.6 % of ∆T in all the cases studied. LES predictions of mean and fluctuating temperatures are in good agreement with experimental data. LES is performed using the CFD software ANSYS CFX 14.0.

Keywords: Mixing tee, Thermal fatigue, Turbulent mixing, Temperature fluctuations

1. Introduction

Structural damage in the piping material produced as a result of thermal loading imposed by the underlying fluid flow, termed as thermal fatigue, is a safety related issue in operating nuclear power plants (NPPs). Flows in certain piping configurations, such as the mixing tees, are difficult to monitor using standard plant instrumentation systems due to the complex turbulent nature of the flow occurring in its vicinity. The problem was investigated initially in the context of liquid metal fast breeder reactors (LMFBRs) [IAEA, 2002]. After the accident at Civaux-I NPP (Chapuliot et al., 2005), a whole host of research activities were initiated to study this problem in the context of light water reactors (LWRs) [like FATHER (Courtin et al., 2013); FATHERINO (Braillard and Edelin, 2009); THERFAT (Metzner and Wilke, 2005); NESC (Dahlberg et al., 2007); VATTENFALL (Smith et al., 2011)]. With the rapid progress in computing technology over the past decade, numerical investigation efforts using computationally intensive scale-resolving simulation (SRS) models were employed to study flow behavior in the vicinity of mixing tees. A compilation of experimental and numerical efforts devoted to studying flow involving different mixing tee configurations and inflow conditions over the past three decades are available in existing literature [Ming and Zhao, 2012; Nimbalkar et al. 2010].

In terms of experimental investigations being validated with numerical data and the corresponding description of thermo-hydraulic factors affecting thermal fatigue (amplitude of temperature fluctuations and their corresponding frequency distribution), very few studies [Selvam et al., (2014,

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2015) Kim et al., 2013] are available in existing literature about mixing tee studies involving temperature differences (∆T) greater than 80 K between the coolant streams. The objective of the present study, therefore, is to perform numerical investigations of mixing tee flows at ∆T > 80 K using the large-eddy simulation (LES) turbulence model and validate the numerical predictions with measurement data. Three test cases with increasing mass flow rate ratios (main/branch) are discussed in this study. The inflow conditions result in temperature differences in the range of 87 – 93 K between mixing fluids.

2. Experimental Setup

The Fluid Structure Interaction (FSI) test facility at University of Stuttgart is a horizontal piping system with main and branch pipes intersecting at a sharp edged T-junction. In accordance with German Nuclear Safety Standards Commission (KTA 3201.1) reactor grade austenitic stainless steel (X6 CrNiNb 18-10) with reduced carbon content is used as the piping material. The main and branch pipes have inner diameters of 71.8 mm (D) and 38.9 mm (d), respectively. The working fluid is deionized water and the facility is designed to perform investigations at a maximum operating pressure of 75 bar and temperature difference (∆T) between the coolant streams can be as high as 260 K. A detailed description of the FSI test facility is described in Kuschewski et al. (2013, 2014). The schematic of FSI test facility along with a view of the mixing tee is shown in Fig. 1.

Fig. 1 Schematic of FSI T-junction test facility along with a view of T-junction Table 1 – List of experiments performed at the FSI test facility

𝑚𝑚* (kg/s) 𝑚𝑏

* (kg/s) 𝑇𝑚 (K) 𝑇𝑏 (K) 𝑅𝑒𝑚 𝑅𝑒𝑏

Test 1 (T1) 0.3 0.1 380 293.5 15340 3100

Test 2 (T2) 0.4 0.1 383 294 27740 3340

Test 3 (T3) 0.5 0.1 386 293.4 35680 3260

* Suffixes m and b denotes main and branch pipes respectively Table I shows the list of tests performed in the present study. A total of 24 thermocouples are used (8 at each cross-section) during experiments to record near-wall temperatures in the mixing zone. Fluid flowing in the main pipe is heated using ceramic heating pad elements attached to the outer surface of

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the pipe. Nominal temperature was set to 393 K. But the measured inflow temperatures are lower than the set nominal temperature. The 8 PID (Proportional-Integral-Derivative) controllers used in FSI test facility are programmed to deliver increased supply of heat at higher mass flow rates and slightly reduced supply of heat in proportion to the prevailing lower mass flow rate explaining why test 3 has a higher inlet temperature as compared to tests 1 and 2.

3. Approach to numerical analysis

3.1 Mesh

The geometry of the mixing tee and its vicinity in the FSI test facility is meshed using the ICEM CFD software of ANSYS. The mesh is unstructured with hexahedral elements and the geometric dimensions of the computational domain are as follows: (i) Hot inflow length – 4D; (ii) Cold inflow length – 5d; (iii) Mixing zone length – 20D. The mesh comprises about 7 million nodes (Fluid domain ≈ 4.5 million nodes; Solid domain ≈ 2.5 million nodes). The schematic of the computational domain, along with angular thermocouple positions is shown in Fig. 2. A view of the mesh along with different cross-sections are shown in Fig. 3.

Fig. 2 Schematic of LES computational domain (left); Angular position of thermocouples (right)

Fig. 3 (a) Computational domain; (b) View of mesh at mixing tee and (c) Cross-sectional region

Fluid temperature fluctuations in the near-wall region are an important factor contributing to thermal fatigue. Because of the no-slip boundary condition (zero fluid velocity at the wall) flow gradients are higher near the wall. The mesh, therefore, must have adequate number of nodes placed near the wall to reasonably resolve the flow scales in the near-wall region. The non-dimensional parameter used to assess the mesh resolution in the vicinity of wall is y-plus (y+). Viscous stress dominated laminar sublayer is defined as y+ < 5. The buffer layer, a transition region between viscosity dominated and turbulence dominated regions, is defined as y+ < 30. The contribution of viscosity to wall shear stress

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diminishes beyond y+ > 50 through y = 0.05D (Hu and Kazimi, 2006; Pope, 2000). In the present study, the thickness of the first grid near the wall is 0.025 mm, which corresponds to 0.02 < y+ < 6 for all the test cases. The non-dimensional grid spacing [Jayaraju et al., 2010] in the streamwise (∆𝑥+), spanwise (∆𝑦+) and wall-normal (∆𝑧+) directions are 18 – 25, 10 – 15 and 10 – 15 for all the investigated cases in the present study. The average cell size of the mesh is about 1.2 mm.

3.2 Large-Eddy Simulation

Large Eddy Simulation represents larger three dimensional unsteady turbulent motions directly, whereas the effects of smaller scale motions are modeled. As stated in Pope (2000), there are four conceptual steps in LES: (i) A filtering operation is performed to decompose the velocity 𝑢 (𝑥, 𝑡) into a filtered component �̅� (𝑥, 𝑡) and a residual component 𝑢′ (𝑥, 𝑡). The filtered velocity field �̅� (𝑥, 𝑡), which is three dimensional and time dependent, represents the motion of large eddies. (ii) Navier-Stokes equation is used to derive the equations for evolution of filtered velocity field. Applying filtering operation in Navier-Stokes equation results in an additional term known as residual stress tensor (or sub-grid scale stress tensor) that arises from residual motions. (iii) Closure is obtained by modeling the residual stress tensor, most simply by an eddy viscosity model. (iv) The filtered equations are solved numerically for �̅� (𝑥, 𝑡), which provides an approximation to the large scale motions in one realization of turbulent flow. The sub-grid scales of the flow motion are modeled using wall adaptive local eddy viscosity (WALE) model [Nicoud and Ducros, 1999]. The governing equations of mass, momentum and energy along with the formulation of WALE model are described in Selvam et al. (2015).

Fig. 4 Inlet velocity profile in (a) Main Pipe and (b) Branch Pipe 3.3 Initial and boundary conditions

(i) Single pipe flow simulations were initially performed to obtain a developed velocity profile to be used as boundary condition at both hot and cold inlets (see Fig. 4).

(ii) Steady state mixing tee calculations using 𝑘 − 𝜔 based Shear Stress Transport (𝑘 − 𝜔 SST) turbulence model are subsequently performed. LES cases are then initialized using the previously converged steady state simulation solutions.

(iii) The measurement data indicates slight thermal stratification within the hot fluid (7 – 13 K between the top and bottom pipe region) prior to mixing with the cold fluid. This is implemented in the LES calculations using the “profile boundary condition” feature in ANSYS CFX.

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(iv) The physical properties of water like density and viscosity vary with temperature. This variation is implemented using the IAPWS library [Wagner and Kruse, 1998] functionality, a default feature in ANSYS CFX. Conjugate heat transfer is applied at the fluid solid interface region. Adiabatic heat transfer boundary condition is used at the outer wall region.

The physical time step (Δt) for simulations is chosen to be 0.2 ms for all LES cases to keep the Courant number less than unity. The total physical time simulated is 25 seconds. Last 15 seconds of LES data, being statistically steady, were used for calculating turbulent statistics.

4. Results Fluid temperatures are normalized using temperature difference between the mixing fluids (∆T).

Instantaneous temperature (𝑇∗) Mean temperature (𝑇∗̅̅ ̅) Temperature fluctuation (𝑇𝑟𝑚𝑠∗ )

𝑇∗ = 𝑇 − 𝑇𝑏

𝑇𝑚 − 𝑇𝑏 (1) 𝑇∗̅̅ ̅ =

1

𝑁∑ 𝑇∗

𝑁

𝑖=1

(2) 𝑇𝑟𝑚𝑠∗ = √

1

𝑁∑(𝑇∗ − 𝑇∗̅̅ ̅)2

𝑁

𝑖=1

(3)

Here N is the number of sampled data points.

Fig. 5 Mean temperature distribution along the axial and different cross-sectional positions

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4.1 Description of flow behavior

Fig. 5 shows the flow behavior downstream of the mixing tee along the axial direction and at different cross-sectional positions. The weaker branch flow, combined with the stronger buoyant main flow results in an incomplete mixing behavior throughout the computational domain. The flow is marked by three distinct regions: (i) Unmixed hot flow near the upper region; (ii) Mixed flow in the lower region and (iii) an oscillating stratification layer between the mixed and unmixed region where highest thermal gradients tend to occur. The intensity of mixing behavior could be directly correlated with the mass flow rate of hot fluid flowing in the main pipe (since all other parameters are kept constant during experiments). The mixing area is reduced and the mixing between fluids becomes less intense with increase in hot flow rates as shown in Fig. 5. The evaluation of Richardson number (𝑅𝑖 = 𝑔∆𝜌𝐷 𝜌𝑢𝑚𝑖𝑥

2⁄ ) serves as a suitable indicator in assessing the significance of either buoyancy or forced convection effects in mixed convection flows. A higher Richardson number (> 1) indicates significant buoyancy effects vis-à-vis forced convection effects. The Richardson numbers calculated for tests 1, 2 and 3 are 2.5, 1.9 and 1.5, respectively. This suggests that test 1 is highly influenced by buoyancy and the effect of buoyancy subsequently decreases in tests 2 and 3. This explains why the flow in mixing region stabilizes quickly in test 1 in relation to tests 2 and 3 which exhibit the oscillating behavior for a longer distance (see Fig. 6).

Fig. 6 Isosurfaces of mean temperature (𝑻∗̅̅ ̅ = 𝟎. 𝟕𝟓) for all LES cases

4.2 Comparison of LES and measurement data

4.2.1 Mean temperature distribution

Fig. 7(a-c) shows the comparison of normalized mean temperature (𝑇∗̅̅ ̅) distribution between LES predictions and measurement data. As very little mixing takes place near the upper region, mean temperatures remain close to hot inflow temperature at θ = 35.5 °, 305.5 ° and 350.5 °. The observation that less intense mixing takes place with increase in mass flow rate is validated by comparison of lowest mean temperatures for all the studied cases. It is observed to be 0.25 in T1 (at 6D, θ = 215.5 °), 0.36 in T2 (at 5D, θ = 125.5 °) and 0.46 in T3 (at 5D, θ = 170.5 °), highlighting the effect of higher mass flow rates in the main pipe on temperature distribution in the mixing region. The oscillating stratification layer between the cold mixing zone and the hot unmixed zone is maintained between θ = 80.5 ° and 125.5 ° on one side and between θ = 215.5 ° and 260.5 ° on the other side of the cross-section. LES mean temperature predictions exhibit very good agreement with the measurement data.

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Fig. 7 Mean temperature distribution in (a) T1, (b) T2 and (c) T3; Distribution of RMS temperature fluctuations in (d) T1, (e)

T2 and (f) T3

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4.2.2 Distribution of temperature fluctuations

Fig. 7 (d – f) shows the comparison of temperature fluctuations (𝑇𝑟𝑚𝑠∗ ) obtained from measurements

and their corresponding LES predictions. As discussed above, the occurrence of high thermal gradients in the stratification layer results in highest amplitude temperature fluctuation among the recorded thermocouple data. In test 1, highest 𝑇𝑟𝑚𝑠

∗ is about 6.3 % of ∆T (at 5D, θ = 125.5 °) whereas

Fig. 8 Power Spectral Density (PSD) of thermal fluctuations in fluid and solid for test cases T1 (a,b), T2 (c,d) and T3 (e,f)

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it is attenuated by an order of magnitude to 0.6 % of ∆T in the solid at 5.5D (θ = 80.5 °). This is because the fluctuations in the solid are attenuated by thermal inertia of the wall and also the mode of heat transport is only via conduction in the solid as opposed to both conduction and convection within the fluid. In test 2, highest 𝑇𝑟𝑚𝑠

∗ is about 7.3 % of ∆T (at 6D, θ = 260.5 °) in the fluid and is about 0.6 % of ∆T (at 5.5D, θ = 260.5 °) in the solid. In test 3, maximum 𝑇𝑟𝑚𝑠

∗ amplitude is about 6.7 % of ∆T (at 5D, θ = 125.5 °) and about 0.8 % of ∆T (at 5D, θ = 125.5 °) in the solid. Among thermocouples located in the fluid, lowest amplitude of temperature fluctuations are seen to occur near the upper region (at θ = 350.5 °), with 𝑇𝑟𝑚𝑠

∗ in all tests in the range of 0.2 – 0.9 % of ∆T. 𝑇𝑟𝑚𝑠∗ predictions made

by LES show reasonable agreement with experimental data. There are certain positions (especially near stratification layer) where 𝑇𝑟𝑚𝑠

∗ predictions by LES either overstate or understate measurement data. But the general trend in temperature fluctuations along the circumferential thermocouple positions is well followed by LES data.

4.2.3 Power spectral density (PSD) of temperature fluctuations

Fluid temperature fluctuations in the near-wall region tend to manifest as thermal stresses in the structure. It has been established that there are attenuation factors depending on the frequency range of temperature fluctuations. Very low frequency fluctuations are homogenized in the structure due to thermal diffusivity. The structure cannot respond to high frequency fluctuations due to its time constant of thermal response [Kasahara et al., 2002]. It has been estimated that the critical frequency range that may cause thermal fatigue damage in the structure is in the range of 0.1 – 10 Hz [Chapuliot et al,. 2005]. Existing literature also contain information about the occurrence of a dominant frequency (spectral peak) in the aforementioned frequency range [Smith et al., 2011]. The objective of this section, therefore, is to assess the power spectral density (PSD) distribution of temperature fluctuations in both the fluid and solid to evaluate (i) the possible occurrence of a dominant frequency in the 0.1 – 10 Hz range and (ii) to compare LES predicted spectra with measurement data.

Fig. 8 shows the PSD distribution of temperature fluctuations (only the highest amplitude fluctuations are shown in the figure) among thermocouples located in the fluid and solid domain for all test cases. The general observation is that no dominant frequency is seen in all the investigated cases under the prevailing flow conditions. The power content of fluctuations greater than 10 Hz are greatly reduced in comparison with those in 0.1 – 10 Hz range. Energy of fluctuations are predominantly contained in the frequency range of 0.1 – 2 Hz. LES predictions of the PSD of temperature fluctuations show good agreement with measurement data. The trend of declining power content in thermal fluctuations with frequency is well captured by LES data.

5. Conclusion

Experimental and numerical investigations (using the large-eddy simulation method ) of flow in a mixing tee for three test cases with increasing flow rates in the main pipe were performed. The inflow temperatures and Reynolds numbers in the hot inflow are as follows: Test 1: 380 K, 15340; Test 2: 383 K, 27740; Test 3: 386, 35680. Cold inflow has ambient temperature in the range 293 – 294 K and the Reynolds number of cold flow lie in the range 3100 – 3300. The inflow conditions thus result in temperature differences in the range of 87 – 93 K between the mixing fluids. The weaker cold flow and the relatively stronger and buoyant hot flow result in incompletely mixed thermally stratified flow behavior downstream of the mixing tee throughout the computational domain. The mixing of fluids is limited to the lower cross-sectional region of the pipe and the hot flow near the upper region remains unmixed for all the investigated test cases. Also, the intensity of flow mixing is found to be decreasing with increase in flow rates in main pipe. High thermal gradients are observed at thermocouples located on either side of the stratification layer. Temperature fluctuations, therefore, are observed to be highest among thermocouples located in the vicinity of stratification layer. The highest fluctuation amplitudes are observed to be in the range 6 – 7.5 % of ∆T between mixing fluids in the

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flow and is attenuated to 0.6 – 0.8 % of ∆T in the solid. Power spectral density (PSD) of temperature fluctuations do not exhibit any dominant spectral peaks in the frequency range of 0.1 – 10 Hz, an important factor contributing to thermal fatigue. LES predictions of mean temperature, temperature fluctuations and PSD of temperature fluctuations show good agreement with experimental data.

Acknowledgements

The first author would like to thank German Academic Exchange Service (DAAD) for providing research fellowship during the present work and the authors would also like to thank High Performance Computing Center Stuttgart (HLRS) for providing the necessary computational resources to perform LES. The authors would like to acknowledge the German Federal Ministry of Education and Research (BMBF) for providing funding to commission the FSI test facility under project number 02NUK009B.

References

Braillard, O., Edelin, D., 2009. Advanced experimental tools designed for the assessment of the thermal load applied to the mixing tee and nozzle geometries in the PWR plant. In: Advancements in Nuclear Instrumentation, Measurement Methods and their Applications, ANIMMA 2009, Marseille, France, June 7–10.

Chapuliot, S., Gourdin, C., Payen, T., Magnaud, J.P., Monavon, A., 2005. Hydro-thermal-mechanical analysis of thermal fatigue in a mixing tee. Nucl. Eng. Des. 235, 575 – 596.

Courtin, S., 2013. High Cycle Thermal Fatigue Damage Prediction in Mixing Zones of Nuclear Power Plants: Engineering Issues Illustrated on the FATHER Case. Proceedia Engineering, 66, 240 – 249.

Dahlberg, M., Nilsson, K.F., Taylor, N., Faidy, C., Wilke, U., Chapuliot, S., Kalkhof, D.,Bretherton, I., Church, J.M., Solin, J., Catalano, J., 2007. Development of a Europeanprocedure for assessment of high cycle thermal fatigue in light water reactors.In: Final Report of the NESC-Thermal Fatigue Project, EUR 22763 EN, ISSN 1018-5593.

Hu L, Kazimi M., 2006. LES benchmark study of high cycle temperature fluctuations caused by thermal striping in a mixing tee. Int J Heat Fluid Flow 27, 54–64.

IAEA, 2002. Validation of Fast Reactor Thermomechanical and Thermalhydraulic Codes, Report, International Atomic Energy agency, Vienna, TECDOC-1318.

Jayaraju, S.T., Komen, E.M.J., Baglietto, E., 2010. Suitability of wall-functions in Large Eddy Simulation for thermal fatigue in a T-junction. Nucl. Eng. Des. 240, 2544 – 2554.

Kasahara, N., Takasho, H., Yacumpai, A., 2002. Structural response function approach for evaluation of thermal striping phenomena. Nucl. Eng. Des. 212, 281 – 292.

Kim, S.H., Huh, N.S., Kim, M.K., Cho, D.G., Choi, Y.H., Lee, J.H., Choi, J.B., 2013. Hydro-thermo-mechanical analysis on high cycle thermal fatigue induced by thermal striping in a T-junction. Journal of Mechanical Science and Technology 27, 3087 – 3095.

KTA 3201.1, 1998. Components of the Reactor Coolant Pressure Boundary of Light Water Reactors – Part 1: Materials and Product Forms.

Kuschewski, M., Kulenovic, R., Laurien, E., 2013. Experimental setup for the investigation of fluid-structure interactions in a T-junction. Nucl. Eng. Des. 264, 223 –230.

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Kuschewski, M., Kulenovic, R., Laurien, E., 2014. Experimental Investigation of Stratified Pipe Flow Mixing in a Horizontal T-Junction. Proceedings of the Workshop on Experiments and CFD Code Application to Nuclear Reactor Safety, Zürich, Switzerland, September 9–11.

Metzner, K.-J., Wilke, U., 2005. European THERFAT project—thermal fatigue evaluation of piping system “Tee”-connections. Nucl. Eng. Des. 235, 473–484.

Ming T, Zhao J. Large-eddy simulation of thermal fatigue in a mixing tee. Int J Heat Fluid Flow 2012;37:93–108.

Naik-Nimbalkar, V.S., Patwardhan, A.W., Banerjee, I., Padmakumar, G., Vaidyanathan, G., 2010. Thermal mixing in T-junctions. Chem. Eng. Sci. 65, 5901 – 5911.

Nicoud, F., Ducros, F., 1999. Subgrid-scale modelling based on the square of the velocity gradient tensor. Flow Turbul. Combust. 62, 183 – 200.

Pope, S.B., 2000. Turbulent Flows. Cambridge University Press, Cambridge, United Kingdom.

Selvam, P.K., Kulenovic, R., Laurien, E., 2014. Large eddy simulation of fluid mixing at high temperature differences in a T-junction piping system. In: Proceedings of ICAPP, April 6 - 9, 2014, Charlotte, NC, USA.

Selvam, P.K., Kulenovic, R., Laurien, E., 2015. Large eddy simulation on thermal mixing of fluids in a T-junction with conjugate heat transfer. Nucl. Eng. Des. 284, 238 – 246.

Smith, B.L., Mahaffy, J.H., Angele, K., Westin, J., 2011. Report of the OECD/NEA-Vattenfall T-Junction Benchmark exercise.

Wagner, W., Kruse, A., 1998. Properties of water and steam. The industrial standard IAPWS-IF97 for thermodynamic properties and supplementary equations for other properties. Springer-Verlag, Berlin.

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Corrosion Fatigue Evaluation: Czech Proposal for WWER-440 Nuclear Power Plants

L. Vlcek Institute of Applied Mechanics Brno, Ltd., Czech Republic, vlcekl@uam.cz

M. Ernestova UJV Rez, a.s., Czech Republic, miroslava.ernestova@ujv.cz

J. Ertl

Czech Energy Company, plc., Czech Republic, jakub.ertl@cez.cz

SUMMARY

The Czech proposal of corrosion fatigue assessment for WWER nuclear power plants (NPP) is presented.

Environmental influence of primary cooling is taken into account in actual methodology of low-cycle

fatigue (LCF) assessment. Proposal is based on two R&D projects supported by Czech energy company

CEZ. The first project (year 2010-2012) was focused on base steel materials, which are used in primary

circuit of WWER-440. The second project (year 2013-2015) extended the suggested methodology to the

additional area of welds. Proposed approach of environmental fatigue correction factor was

experimentally verified. LCF strain-controlled tests of austenitic stainless steel 08Ch18N10T and welds in

primary water of WWER-440 were performed. Although experimental results are limited, it is evident that

the real environmental influence on fatigue life of tested materials is not so serious in comparison with

recommendations defined in NUREG requirements. Thus direct application of environmental fatigue

correction factor, originally defined in NUREG approach, is not recommended for WWER NPP.

Keywords: low-cycle fatigue, corrosive environment, base material, welds, WWER NPP

1. Introduction

The procedure of low-cycle fatigue (LCF) assessment and prediction for WWER nuclear power

plants are stated in Czech standard NTD A.M.E. [1]. Approach is based on so called design S-N curves.

So far design fatigue curves were constructed with using experimental data measured in air at different

testing temperatures. Similar like ASME procedure, the design fatigue curves in graphical form up to

maximal allowed temperatures can be used. Four main groups of steels are considered; i) carbon and low-

alloy steels with the ratio Rp0.2/Rm ≤ 0.7, ii) the group (i) with 0.7 < Rp0.2/Rm ≤ 0.8, iii) the group (i) with

0.8 < Rp0.2/Rm ≤ 0.9 and iv) austenitic stainless steels. Design S-N curves for carbon and low-alloy steels

in graphical form are for temperatures ≤ 450°C. The S-N curve for austenitic stainless steels can be used

up to 350°C. In addition the analytical description for S-N curves construction can be used. Due to

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mathematical definitions specific computational design curve can be separately obtained for each steel

type, its welds and operating temperature. Mathematical description for S-N curves is based on Langer’s

relationship between total strain amplitude εat and number of cycles to failure Nf:

ZNE

f

c

at −+=

100

100ln

4

1σε (1)

where σc is the fatigue limit for Rσ = - 1, E is Young’s modulus and Z is reduction of area measured

on tensile test specimens. NTD A.M.E. approaches operate with real total strain amplitude εat. Due to

engineering needs total strain amplitude is formally converted via Young’s modulus E on to fictive elastic

stress amplitude σaF :

σaF = εat .E (2)

Moreover the cyclic hardening or softening of material and the cycle asymmetry are taken into

account. Computational fatigue curves of Langer’s type are constructed by using of minimal guaranteed

mechanical properties, which can be obtained from conventional tensile tests. Such constructed fatigue

curves are more conservative (reduction of area Z ≤ 50% at operating temperature is used) than fatigue

curve constructed on the basis of real fatigue test data. In design fatigue curves the safety factors on

applied stress nσ = 2 and on number of cycles nN = 10 are used. Finally the allowable fictive stress

amplitude or allowable number of cycles are set conservatively, i.e. with using of lower position chosen

from two branches of computational fatigue curve. The cumulative character of fatigue damage D is

considered through hypothesis suggested by Palmgren-Miner. The value D = 1 indicates the moment of

fatigue crack initiation.

For more than 20 years the influence of primary cooling medium corrosive environment on LCF is

research object worldwide. Generally, fatigue initiation and fatigue crack growth can be influenced by

environment, in which the cyclic loading of construction parts is realized. The corrosive environment may

reduce the number of cycles for crack initiation and increases the crack growth rate. The influence of

primary water environment is implemented in new procedures of fatigue evaluations mainly in the USA,

Japan, France, Finland and Russia. It was indicated by LCF results in corrosive environment [eg. 2-6] that

the limitation stated in current standards may be exceeded. In comparison with air environment shorter

fatigue life of laboratory specimens in water was observed in the case of critical combination of some

corrosion and cyclic loading parameters. This discrepancy was addressed (besides new design fatigue

curves construction) through a correction of results obtained with using of original fatigue curves in air

conditions. Correction is realized by application of so called environmental factor Fen. The measure of

correction of results in air is done by a value Fen > 1. The final goal after setting of Fen is its application in

the frame of standardized procedures used in fatigue life evaluation. The environmental factor Fen is

defined eg. in NUREG/CR-6909 document [7] as the ratio of number of cycles in air Nair,RT at room

temperature to number of cycles in water Nwater at testing/operating temperature:

Fen = Nair,RT / Nwater (3)

There are several significant differences between ASME and NTD A.M.E. approaches in fatigue

initiation assessment. The main differences are on the side of applied stresses, safety factors and different

position of fatigue curves in the coordinate of stress (or strain) amplitude vs. number of cycles to crack

initiation [8]. Also the operating temperature is taken into account in a different manner. Due to

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mathematical formulas the effect of temperature and stress asymmetry is directly comprised in a

construction of fatigue design curve. In addition the design curve is directly corrected in the case of welds.

Due to large differences briefly described above the direct application of NUREG approach isn’t possible

in the case of WWER power plants. Thus the alternative way to the international Fen factor assessment is

introduced in this paper. Correction factor FPR is suggested not only for the application on base material,

but also its combination with welding factor is presented. Our suggestion how to apply correction on

fatigue curves due to welding and due to corrosive environment was experimentally verified by LCF tests.

Experiments were carried out on base material of austenitic stainless steel and on its similar metal welds.

Moreover LCF tests on dissimilar metal welds were performed in air and corrosive primary water

environment under WWER-440 normal operational condition (NOC).

2. Environmental factor defined in NTD A.M.E.

Comparing to original definition of an international Fen as a ratio of number of cycles in air at

reference temperature to in water at testing temperature, our new FPR definition is defined by a ratio of

total elastic-plastic strain amplitude in air εat air to in water εat water [9, 10]:

FPR = εat air / εat water FPR ≥ 1 (4)

Schematic illustration of both situations is described in Figure 1. For simplification the influence of

temperatures and safety coefficients on the position of fatigue curves are not considered in Figure 1. But

the Figure 1 matches our FPR correction factor exactly, because it is defined as the ratio between total

strain amplitudes obtained directly from experimental LCF results measured in the same temperature,

strain rate, stress asymmetry, etc. in air and in water. Finally clear effect of only corrosive environment on

fatigue, without secondary influence of testing conditions or any shifting due to safety coefficients can be

described. In general the value of FPR can be equal or unequal to 1, but for fatigue assessment and life time

prediction the value 1 or greater than 1 are used.

Figure 1. The schematic description of Fen and FPR definitions

0,0001

0,001

0,01

0,1

1,E+01 1,E+02 1,E+03 1,E+04 1,E+05

N [-]

εε εεat [-

]

Air

WaterFPR

Fen

CSNI/R(2017)2/ADD1

3. Welding coefficient defined in NTD A.M.E.

Similarly like two ways of incorporating environmental influence on fatigue exist, in NTD A.M.E.

the same general possibilities are in the case of fatigue assessment of welds:

1. fatigue curves for welds

2. correction of fatigue curve for base material by welding coefficient

In most cases the base material fatigue curve is corrected by welding coefficient ϕw. Such welding

coefficient is defined as a ratio of total strain amplitude of weld εat weld to total strain amplitude of base

material εat base mat.l :

ϕw = εat weld / εat base mat. ϕw ≤ 1 (5)

From experimental point of view the welding coefficient can be also greater than 1, but for fatigue

assessment and life time prediction the value can’t exceed 1. LCF data of base material and weld were

obtained in air under the same testing conditions like temperature, stress asymmetry, strain rate, etc. The

typical value of welding coefficient for stabilized austenitic stainless steels is around 0.8. There are several

situations, especially when the welding technology and post weld heat treatment are described well, when

the welding coefficient can be set to 1. Strictly speaking there is no influence of assessed weld on fatigue

results.

4. Allowed (fictive) stress amplitude

As it was written in introduction, in NTD A.M.E. analyses of fatigue crack initiation operate with

total elastic-plastic strain amplitudes, which are for better understanding converted formally to the value

of linear elastic so called fictive stress amplitudes via eq. (2).

With the aim of direct application in the frame of actual mathematical description, which describes

relations of S-N design curves, the coefficient for water corrosive environment ϕPR can be defined as the

reciprocal value of FPR:

ϕPR = 1/FPR ϕPR ≤ 1 (6)

The allowed fictive stress amplitude in the case of base material in water [σaF] water is computed as

allowed fictive stress amplitude of base material in air at operational temperature [σaF] air multiplied by the

coefficient for water corrosive environment ϕPR:

[σaF] water = [σaF] air . ϕPR (7)

The similar procedure is applied in the case of fatigue assessment of welds in air:

[σaF] weld = [σaF] base mat. . ϕw (8)

Generally in NTD A.M.E. standard there is so called generalized coefficient ϕs for defining of all

possible influences on position of fatigue design curve due to welds, environment, multiaxiality etc.

Finally the general form for setting of allowed fictive stress amplitude is written by the formula:

CSNI/R(2017)2/ADD1

[σaF] influence = [σaF] . ϕs (9)

Based on our LCF experiments on base materials and welds at elevated temperatures in air and

primary water environment of WWER nuclear power plants under NOC, we have decided on the formula

for the synergic effect of weld and environmental coefficient:

ϕs = min{ϕPR, ϕw} (10)

The definition (10) is in accordance with the proposal of Russian authors published in work [11].

Correction environmental factor can be set on the base of three options. The simplest is the option 1, when

the correction factor FPR is constant for all levels of total strain amplitude. Than for austenitic stainless

steel type 08Ch18N10T FPR = 1.56, for carbon and low-alloy steels type 22K the value is FPR = 1.3. The

option 2 operates with values of FPR, which are in reality depended on total strain amplitude. Based on our

LCF experiments for base material and welds the next formulas for of FPR computing can be used:

austenitic stainless steel 08Ch18N10T and welds (08Ch18N10T-08Ch18N10T, 08Ch18N10T-22K)

FPR = 0.1706.ln (εat) + 2.2373 FPR = 1 for εat ≤ 0.001 (11)

carbon and low-alloy steels

FPR = 0.0866.ln (εat) + 1.6267 FPR = 1 for εat ≤ 0.001 (12)

Table. 1 Three-optional procedure of correction due to primary water corrosion environment

Option Required parameters Level of conservativeness

0) In air standard requirements for definition

of loading and fatigue curves in air

at operational temperatures

done by reserve between measured LCF data

and minimal guarantied mechanical

characteristics used for design fatigue curve

construction

1) In water maximal value of FPR,max

respectively min. value of ϕPR,min for

DO ≤ 0.01 ppm

for DO ≤ 0.01 ppm very conservative because

higher total strain amplitude is considered for

all loading cycles in comparison with real

loading

2) In water knowledge of all loading spectrum

in a form of total strain amplitudes,

use formulas (11) or (12),

DO ≤ 0.01 ppm

for DO ≤ 0.01 ppm conservative, but real total

strain amplitudes are taken into account, so

different real FPR are computed

3) In water real strain rate and amplitude, mean

strain, stress asymmetry,

temperature, DO, sulfur content: .

ε *, εat,, εm, Rσ, T

*, O

*, S

*

for DO > 0.01 ppm, conservative assessment

describes real values of all selected material,

loading and environmental parameters

CSNI/R(2017)2/ADD1

Option 1 and 2 can be applied when the dissolved oxygen (DO) in primary cooling medium is ≤ 0.01

ppm. Option 1 is very conservative in comparison with option 2. If DO > 0.01 ppm, the option 3 should be

used. The description of option 3 is not so simple as option 1 and 2. In general option 3 converts Russian

approach [11] to the Czech ϕPR methodology. In this case all selected real parameters of corrosive

environment and loading parameters are taken into account. All options in water completed by standard

assessment in air are summarized in Table 1.

5. LCF experiments

During years 2010-2015 two main LCF experimental programs were done at UJV Rez. The object of

the first one was base material research. Austenitic stainless steel stabilized by titanium was used mainly

for primary circuit piping at WWER-440 MW NPP. Its original Russian mark is 08Ch18N10T and the

nearest US equivalent type is AISI 321. The chemical composition and minimal guarantied tensile

properties at reference temperature are in Table 2 and 3. Four sets of LCF experiment were carried out

with using round smooth test specimens; (i) in air at elevated temperature 325°C and strain rate 0.4%/s,

(ii) in water at elevated temperature 320°C and strain rate 0.01%/s, (iii) in water at elevated temperature

320°C and strain rate 0.004%/s, (iv) in water at elevated temperature 320°C, strain rate 0.002%/s. Totally

15 specimens were tested in water so final fatigue curve in Figure 3 marked Base mat. water 320°C

0.002%/s represents the lowest position from three sets of experiments done in primary water corrosive

environment.

Table 2. Chemical composition of 08Ch18N10T and 22K base material, in wt.%

Material C Mn Si P S Ni Cr Mo V Cu Co Ti Al

08Ch18N10T max.

0.08

1.00

2.00

max.

0.80

max.

0.035

max.

0.020

9.0

11.0

17.0

19.0

- - max.

0.25

0.4

0.7

0.005

0.035

22K 0.19

0.26

0.75

1.00

0.20

0.40

max.

0.03

max.

0.03

max.

0.3

max.

0.3

- - max.

0.3

- - -

Table 3. Minimal guarantied tensile properties of 08Ch18N10T and 22K, reference temperature

Material Rm [MPa] Rp0.2 [MPa] Z [%] A5 [%]

08Ch18N10T 490 196 40 38

22K 430 215 40 18

Moreover the second main group of LCF experimental program covered the similar metal welds

(Figure 2a) and dissimilar metal welds (Figure 2b). Chemical composition and minimal guarantied tensile

properties of base materials are in Tables 2 and 3. The chemical composition and minimal guarantied

tensile properties of buttering and filed materials at reference temperature are in Tables 4 and 5.

Considering decreasing number of cycles to failure with slower strain rate measured on base material

CSNI/R(2017)2/ADD1

08Ch18N10T, only strain rate of 0.002%/s at temperature 320°C was applied in the case of LCF tests of

welds. Totally 9 specimens were tested (3 specimen for dissimilar metal weld). It was evaluated, that the

weakest point for similar welds is base material 08Ch18N10T (see Figure 2a). To the contrary, the

weakest material line in dissimilar welds is between the second buttering layer and welding metal (see

Figure 2b). Although different fracture locations have been observed, limited results of LCF test showed

that only one regression line is sufficient for description of fatigue behavior of both similar and dissimilar

metal welds in air as well as one line for water testing conditions.

Figure 2. Similar (a) and dissimilar (b) metal welds

Table 4. Chemical composition of buttering and filed materials, in wt.%

Material C Mn Si P S Cr Ni Mo V Nb Co N2 δFe

EA 359/9 max.

0.12

1.00

2.20

0.03

0.70

max.

0.025

max.

0.018

13.50

17.00

22.00

27.00

4.50

7.50

- - max.

0.05

0.08

0.18

-

EA 400/10T max.

0.10

1.15

3.10

max.

0.60

max.

0.025

max.

0.025

16.80

19.00

9.00

12.00

2.00

3.50

0.30

0.75

- max.

0.05

- 2.0

8.0

Sv04Ch19N11M3 max.

0.10

0.80

2.00

max.

1.00

max.

0.030

max.

0.020

15.00

20.00

9.00

12.00

1.50

3.00

- - max.

0.05

- 2.0

8.0

Table 5. Minimal guarantied tensile properties of buttering and filed material, ref. temperature

Material Rm [MPa] Rp0.2 [MPa] Z [%] A5 [%]

EA 395/9 588 363 40 23

EA 400/10T 539 343 30 25

Sv04Ch19N11M3 442 274 30 25

08Ch18N10T

Sv 04Ch19N11M3

EA 400/10T

08Ch18N10T

a)

22K 08Ch18N10T

Sv-04Ch19N11M3 EA 359/9

EA 400/10T

EA 400/10T

b)

CSNI/R(2017)2/ADD1

0,1

1

10

1,E+02 1,E+03 1,E+04 1,E+05

N [-]

εε εεa

t [%

]

Weld water 320°C, 0.002%/s

Base mat. air 325°C, 0.4%/s

Base mat. water 320 °C, 0.002%/s

Weld air 325°C, 0.4%/s

Figure 3. Experimental fatigue curves, regression lines

6. Example of application

The suggested methodology of fatigue assessment with correction due to primary water environment

was applied to LCF evaluation of real pipe line. Pipe line connects the relief valve with the pressurizer of

WWER-440. The whole line is made from 08Ch18N10T austenitic stainless steel with the primary

medium inside. The object of LCF assessment was the welding joint connecting the T-junction with the

pipe and base material of T-junction. From demonstration reason only one loading block is analysed in

this paper. This loading block consists of heat up to normal operational condition, pressure test and

operational test of relief valves at the end of cool down. Total strain amplitudes were set from linear stress

tensors computed by finite element method. For base material of T-junction the total strain amplitude was

set 0.33%, and for weld joint 0.24%. Because the level of DO was below 0.01 ppm, corrosion correction

done by option 1 and option 2 were taken into account. Fatigue curve of Langer’s type was used. The

welding coefficient was ϕw = 0.8. For comparison the base fatigue evaluation of analyzed areas of base

material and weld in air was done. Due to direct comparison of predicted number of cycles to crack

initiation with experimental fatigue curves in the form of regression lines, the fatigue life prediction was

done with using safety coefficients nσ = nN = 1. All parameters needed for LCF assessment of T-junction

and weld together with results in the form of predicted number of cycles to fatigue crack initiation N and

fatigue damage D (usage factor) are in Table 6. Graphical form of comparison between computed

predictions and experimental data are in Figure 4 and in detail in Figure 5.

CSNI/R(2017)2/ADD1

Table 6. Parameters for LCF assessment

air, option 0 water, option 1 water, option 2 nσ = 1

nN = 1 εεεεat [-]

ϕϕϕϕw ϕϕϕϕPR N [-] D [%] ϕϕϕϕw ϕϕϕϕPR N [-] D [%] ϕϕϕϕw ϕϕϕϕPR N [-] D [%]

base

mat. 0.0033 1 1 4617 0.0216 1 0.64 1288 0.0776 1 0.79 2313 0.0432

weld 0.0024 0.8 1 6763 0.0148 0.8 0.64 3370 0.0297 0.8 0.83 7629 0.0131

0,1

1

10

1,E+02 1,E+03 1,E+04 1,E+05

N [-]

εε εεat [%

]

Weld water 320°C, 0.002%/s

Base mat. air 325°C, 0.4%/s

Base mat. water 320 °C, 0.002%/s

Weld air 325°C, 0.4%/s

Prediction base mat.

Prediction weld

Figure 4. Experimental fatigue curves, regression lines with predicted results

0,1

1

1,E+03 1,E+04

N [-]

εε εεa

t [%

]

Figure 5. Detail from Figure 4

ϕPR = 1 ϕPR = 0.79 ϕPR = 0.64

ϕPR = 0.83 ϕw = 0.8 ϕPR = 0.64

Option 1, def. (10)

min. from two points

Option 2, def. (10)

min. from two points

CSNI/R(2017)2/ADD1

We can see from Figure 4 and 5, that in the case of base material the LCF prediction without

correction on corrosive environment (air, option 0) the predicted number of cycles is nearly two times

higher in comparison with option 2 and more than tree times higher in comparison with option 1. Also a

reserve factor between measured LCF data (regression line base mat., water) and predicted number of

cycles (air, option 0) in base material is near 2. This reserve is done due to taking of minimal guarantied

mechanical characteristics used for design fatigue curve construction besides the measured Manson-Coffin

parameters.

In the case of weld the highest number of cycles was predicted by using simple option 2 in water

environment. For this reason the condition stated in definition (10) was proposed, so the minimum number

of cycles from simple weld evaluation in air and simple evaluation in water environment should be taken

as final result. The same situation appears when the option 1 is taken into account. As it is shown in

Figures 4 and 5, the fatigue prediction based on option 1 is very conservative for base material as well as

for weld. In both evaluated examples the transition from option 1 to option 2 reduces level of

conservativeness very intensively.

7. Conclusion

Czech proposal of fatigue assessment and prediction in corrosive environment of primary water for

WWER-440 nuclear power plants were presented. Principles of LCF evaluation stated in Czech NTD

A.M.E. standard are different in comparison with principles defined in ASME and equivalent codes. Thus

our proposal matches NUREG recommendations on correction due to corrosive environment with fatigue

assessment methodology used in WWER nuclear power plants. Proposed idea of environmental correction

is very similar like original Russian idea of fatigue curve correction in the case of welding joints. Three

optional methodology of environmental coefficient application was suggested not only for base materials,

but also for selected welds. Results of LCF test showed that our proposal of correction leads to

conservative prediction of number of cycles to fatigue crack initiation.

It seems that requirements on environmental correction in the case of normal operational conditions

of WWER-440 nuclear power plants are not so strict. The reason can be seen in the conservative

approach, when the minimal guarantied tensile mechanical properties are taken for fatigue curve of

Langer’s type construction. Due to this fact the computational design fatigue curve of Langer’s type in air

has lower position than real measured data from LCF tests in simulated primary water. From this point of

view the safety margins introduced by safety factors on stress and on number of cycles include also

environmental aspects. Thus the fatigue environmental correction by FPR should be recommended with the

aim to keep the required safety margins.

Acknowledgements

This article is a part of private research fully supported by CEZ Company in the frame of R&D activities.

CSNI/R(2017)2/ADD1

References

[1] NTD A.M.E. standard: Normatively Technical Documentation of Association of Mechanical Engineers, Section III,

Strength assessment of equipment and piping of nuclear power plant type WWER, NTD_AME_Section_III_2013, No. 1 (in

Czech)

[2] Filatov, V. M., Computational and experimental assessment of cyclic corrosion resistance, Zavodskaja Lab 1991, 9:66-8. (in

Russian)

[3] Kanasaki, H., Umehara, R., Mizuta, H., Suyama, T., Fatigue lives of Stainless steels in PWR primary water, SMIRT 14,

Lyon, France, August 1997

[4] Kanasaki, H., Umehara, R., Mizuta, H., Suyama, T., Effect of strain rate and temperature change on the fatigue lives of

stainless steels in PWR primary water, SMIRT 14, Lyon, France, August 1997

[5] Metha, H. S., Gosselin, S R., Environmental factor approach to account for reactor water effects in pressure vessel and

piping fatigue evaluations, NED 1998, 181:175-97

[6] Chopra, O. K., Muskara, J., Effect of light water reactor coolant environments of fatigue crack initiation in piping and

pressure vessel steels. ICONE-8300, Baltimore, MD USA, April 2000

[7] Effect of LWR Coolant Environments on the Fatigue Life of Reactor Materials, Final Report, Argonne National Laboratory,

U.S. Nuclear Regulatory Commission Office of Nuclear Regulatory Research Washington, DC 20555-0001, NUREG/CR-

6909, ANL-06/08, February 2007

[8] Vlcek, L., Fatigue design curves for austenitic stainless steels: comparison between ASME Code and Czech NTD A.M.E

standard, New methods of damage and failure analysis of structural parts, ISBN 978-80-248-2802-2, Ostrava, Czech Rep.,

September 2012

[9] Vlcek, L., Corrosion Fatigue Evaluation of Austenitic Stainless Steels: the New Proposal to the Czech Standard in the Area

of Nuclear Power Plants Type WWER, PVP 2013, July 14-18, Paris, France

[10] Vlcek, L., The current status of new Czech corrosion fatigue evaluation proposal for WWER nuclear power plants, New

methods of damage and failure analysis of structural parts, ISBN 978-80-248-3488-7, Ostrava, Czech Rep., September

2014. The article is prepared for publication in Elsevier Procedia Materials Science

[11] Filatov, V. M., Evropin, S. V., Strength calculation of NPP equipment and pipelines during operation. Low and high-cycle

corrosion fatigue, International Journal of Pressure Vessels and Piping, Vol. 81, 2004

CSNI/R(2017)2/ADD1

Mechanical Analysis for CRDM Upper Canopy Seal with

Weld Overlay Repair

Xiao XU, Dasheng WANG, Pan LIU, Ting JIN

China Nuclear Power Design Company, Ltd., Shenzhen 518172, China

Abstract:

In the past few years, cracks had been found frequently on canopy seal weld zone in control rod drive

machine (CRDM), normally accompanied with the leakage because of the crack growth through the

whole wall. The cracks should be repaired. Considering the confined maintenance clearance of CRDM

and the limited duration of repairing requirement, usually weld overlay repair is chose as one of the

best repairing ways. This paper presents the mechanical analysis for CRDM upper canopy seal with

weld overlay repair, with considering the residual stress during welding process and the impact of

original stress corrosion crack environment, as well as fatigue crack growth.

Key Words:

canopy seal, crack growth, weld overlay repair, stress corrosion crack, fatigue, weld residual stress

1 Introduction

Canopy seal welds (CSWs) commonly used in CRDM of pressure water reactors (PWR). In the past

few years, cracks had been found frequently on canopy seal weld zone in control rod drive machine

(CRDM), normally accompanied with the leakage because of the crack growth. These welds have

been prone to cracking due to pressure water stress corrosion cracking (PWSCC) [1] [2]. Usually

cracks should be repaired via welding process. Considering the confined maintenance clearance of

CRDM and the limited duration of repairing requirement, weld overlay repair (WOR) is always chose

as one of the best repairing ways.

The WOR has been developed that allows utilities to seal the leak and reinforce the weld allowing the

plant to continue operating. The weld overlay design applied to the UCS is in accordance with ASME

BPVC Section XI IWB-3640 [3], ASME Code Case N-504-2[4] and NUREG-0313[5].

In 2006 and 2014 separately, through-wall cracking and leakage of CSWs were found at the UCS zone

located on the CRDM in Ling Ao Phase 1 Nuclear Power Plant. This paper documents the evaluation

performed by China Nuclear Power Design Company (CNPDC) to justify operation safety of this

plant with WOR on CRDM UCS for 40 years service life. The evaluation included the stress analysis,

fracture mechanics and crack growth analyses.

2 Structure and Materials

2.1 Structure

The original design structure of CRDM UCS is shown in Figure 1. The wall thickness of UCS is 2.3

mm. According to the weld overlay design (minimum thickness, number of welding beads and layers),

the 4.06 mm minimum UCS with WOR buildup is comprised of 2 welded layers, each one is 2.03 mm

thick, see Figure 2. And a 45 degree taper angle is assumed between the reinforcement weld and the

surrounding components.

2.2 Material

The structural materials of UCS with WOR zone are as follow:

Surrounding components (rod travel housing, lap and canopy ring) are Z2CN19-10 NC (304L);

Original seal weld is ER 308L (same as the surrounding components);

Welding overlay repair is Alloy 52M.

                                                               Corresponding author. Tel.:+86 755 84438514; fax: +86 755 84434809-129627 E-mail address: xiao.x@cgnpc.com.cn

CSNI/R(2017)2/ADD1

Figure 1 Original Design Structure of UCS

Figure 2 Weld Overlay Design Structure of UCS (Minimum Sizing and Example Bead Placement)

3 Stress Analysis

Stress analysis is including normal stress analyses, mainly about fatigue analysis under the 2nd

category condition and weld residual stress (WRS) analysis.

3.1 Finite Element Model

A two-dimensional axisymmetric model was used to evaluate the normal stress analyses and weld

residual stress analyses, shown in Figure 3. The displacement boundary conditions are shown in

Figure 4. To thread engagement, the Y direction displacements UY of coincidence nodes are coupled.

The loading boundary conditions are shown in Figure 5. Since the external mechanical loads are

assumed by thread engagement bearing, the UCS with WOR is subjected to internal pressure and

thermal loads. And here it is conservatively assumed that the reactor coolant transient temperature was

loaded on inner surface boundary same as pressure loading. Paths in analysis are identified in Figure 6.

Figure 3 Axisymmetric Finite Element Model of UCS with WOR

UCS 

UCS WOR

CSNI/R(2017)2/ADD1

Figure 4 Axisymmetric Finite Element Model with Boundary Conditions

Figure 5 Pressure Loading on Axisymmetric Finite Element Model

Figure 6 Paths Considered in the Analysis

3.2 Normal Stress Analysis

According to the original design, the fact is that the UCS is not to provide structural reinforcement, but

to provide a leakage barrier. According to the ASME NB-3227.7, it is necessary to check the primary

stress under the internal pressure. According to the weld overlay design, the minimum thickness of

WOR buildup is bigger than original wall, so stress limit will be always satisfied. Therefore, the

normal stress analysis is mainly forces on the fatigue evaluation, and to provide input data for the

subsequent fatigue and crack growth calculation.

For the pressure loading, a unit pressure load of 15.5 MPa was used. Figure 7 shows the stress result in

Y direction under the unit pressure.

For fatigue evaluation, it will be determined based on the design cycles. From the list of design

transients, only those that produce a significant change in pressure and temperature are used. Using

reactor heat-up and cool-down transients which are full load and unload cycles to conservatively

envelop other transients. Thus, conservatively adding all these transients together give 2980 full load

P112 P212

P222P415

P430 

P234

CSNI/R(2017)2/ADD1

cycles for 40 years. Figure 8 shows the thermal distribution in static operational status with 291.4 ℃

temperature load. For operating thermal stress with 16.0 MPa internal pressure stress and 291.4 ℃

temperature load, the stress result in Y direction is shown in Figure 9.

The stress result of the UCS with WOR under the pressure and temperature loads is mostly lower than

150 MPa. The bigger stress values are mainly caused by the difference of the thermal expansion

coefficient between UCS basic metal and overlay buildup. For all of the paths on the UCS with WOR,

the fatigue accumulative usage factors on inner and outer position are far less than the limit value 1.

Figure 7 Stress Result in Y direction under the Unit Pressure (15.5 MPa)

Figure 8 Thermal Distribution in Static Operational Status (291.4 ℃)

Figure 9 Stress Result in Y direction under in Static Operational Status (16.0 MPa and 291.4 ℃)

CSNI/R(2017)2/ADD1

3.3 Weld Residual Stress Analysis

The WRS calculation is based on the methodology documented in References [6] and [7]. The residual

stress due to welding is controlled by the welding parameters, temperature-time history, temperature

dependent material properties, and elastic-plastic stress reversals.

The analytical technique uses finite element analysis to simulate the multi-pass weld repair process.

The elastic-plastic nonlinear stress analysis is performed using a bi-linear kinematic hardening model

for the materials.

Welding parameters of the WOR are including:

Environment temperature is 16 ℃;

Interpass temperature is lower than 175 ℃;

Heat input is 650 J/mm for the 1st layer and 980 J/mm for the 2nd layer.

The following additional assumptions are used in the evaluation:

(1) The materials were assumed to be homogeneous and isotropic.

(2) The heat source was modeled as a volumetric heat source in the analytical model.

(3) Yield stress and Young’s Modulus at or above 1371℃ were assumed to be negligible and

assigned small values to provide solution convergence.

(4) The heat transfer coefficients on the inside and outside surfaces of the component were assumed

to be temperature independent.

(5) Heat loss due to radiation was neglected.

(6) No latent heat of weld beads was assumed.

Figure 10 shows the weld residual stress results when the uniform temperature of the structure cooled

down to room temperature (16 ℃). Because of the WRS is associated with the compatibility of

deformations of adjacent parts of the structure, it will change with the structure temperature.

For the path P112, Figure 11 shows the weld residual stress on meridional SY results along with the

path from inner to outer surface under the uniform temperatures of the structure cooled down to

different values.

Figure 12 shows the through wall WRS from inner to outer surface along all selected paths. The

through wall stress of paths P212 and P222 are enveloped by P112.

Figure 10 Weld Residual Stress from WOR (Cool down to 16℃)

CSNI/R(2017)2/ADD1

-50

0

50

100

150

200

250

0 2 4 6 8

Distance From Inner to Outer(mm)

Mer

idio

nal S

tres

s S

y (M

Pa) T= 23.9 ℃

T= 31.9 ℃

T= 100.0 ℃

Figure 11 Weld Residual Stress from WOR with Different Uniform Temperature

-200

-150

-100

-50

0

50

100

150

200

250

300

0 2 4 6 8 10 12 14 16

Distance From Inner to Outer(mm)

Pesidual Stress at Room Temperature

(MPa)

P112 Meridional Sy

P212 Meridional Sy

P222 Meridional Sy

P234 Sx

P415 Sy

P430 Sy

Figure 12 Weld Residual Stress from WOR Through Wall at Room Temperature

4 Fracture Mechanics Evaluation

4.1 Methodology

In order to perform the crack growth analysis for both fatigue and SCC, linear elastic fracture

mechanics analysis was performed to develop the stress intensity factors. For fatigue crack growth, the

important parameter is the K , the stress intensity factor range due to the cyclic stress. For SCC, the

important parameter is the stress intensity factor determined from the sustained stresses. Then the

available expressions of crack growth rate (CGR) will be used for calculating the crack growth depths

of UCS with WOR for 40 years service life and comparison with the allowable flaw sizes.

The selected locations for fracture mechanics evaluation are paths P112, P234, P415 and P430. Path

P112 historically is the location of cracks in PWRs. Paths P234 and P415 are the location which a leak

was detected. Path P430 is also included since the flaw cannot be ruled out to have initiated from the

inner threads. Paths P212 and P222 were enveloped by P112.

For paths P112, P415 and P430, A 360° full circumferential crack on the inside surface of a cylinder is

used, Figure 13.For path P234, a semi-circular in half space is used since the crack grows into the

CSNI/R(2017)2/ADD1

lengthy longitudinal section of the rod travel housing, Figure 14.

Figure 13 Full Circumferential Crack in Cylinder on the Inner Surface

Figure 14 Continuous Surface Crack in Half Space

4.2 Stress Intensity Factor

For a through-wall stress along the path represented by a forth order polynomial: 4

4

3

3

2

210

t

u

t

u

t

u

t

u (1)

Where, u is distance from the flawed surface, t is wall thickness, and i is polynomial

coefficient.

The stress intensity factor K is expressed as following[8]:

at

aI

t

aI

t

aI

t

aIIKI

4

44

3

33

2

221100

(2)

Where, a is flaw depth, iI is magnification coefficients.

It is sated in ASME Section XI that the allowable flaw size is determined by

CIrIbI KKKKK Im (3)

Where, ImK is applied stress intensity due to membrane stress, IbK is applied stress intensity due

to bending stress, IrK is applied stress intensity due to weld residual stress, CK is allowable

fracture toughness.

4.3 Crack Growth Rate

4.3.1 Fatigue Crack Growth Rate

The availability of fatigue crack growth rate (CGR) data for Alloy 52M weld overlay material

somewhat limited. It is shown in Reference [9] that little or no enhancement of CGRs in PWR water is

observed in the existing fatigue CGR data for Alloy 52M welds. Here the fatigue CGR (m/cycle) of

Alloy 690 in air will be used for the Alloy 52M welds.

The fatigue CGR of Alloy 690 in air is expressed as [9]:

2.2 4.1690 (1 0.82 ) ( )A

daC R K

dN (4)

CSNI/R(2017)2/ADD1

Where, max minK K K , min max/R K K ,

14 16 18 2 21 3690 5.423 10 1.83 10 1.72 10 5.49 10AC T T T ,

T is temperature in ℃.

4.3.2 SCC Crack Growth Rate

The crack growth flaw for SCC has the following form:

nCKdtda / (5)

Where, dtda / is the crack growth rate in in/h, K is the stress intensity factor in ksi√in, and C and n are constants that depend on the material and environment. For sensitized Type 304 stainless

steel is[10]: 859.3 eC and 161.2n . It is assumed that the exponent of the power law

remains the same for stainless steel base metal, weld and alloys. Based on this assumption, the value

of C for Alloy 690 is 1095.4 e [11].

The 1st layer of Alloy 52M applied to Type 304 stainless steel canopy seal will be diluted. The stress

corrosion resistivity index (SCRI)[12] of the diluted layer of Alloy 52M is similar to the Alloy 690.

And the CGR curve of the 1st layer of Alloy 52M with a factor of 55 slower than the Type 304

stainless steel curve still bounds the Alloy 690 estimated curve. Thus, the crack growth flaw SCC for

the diluted layer of Alloy 52M estimated as following:

161.21010527.6/ Kdtda (6)

There is ongoing research on the stress corrosion crack growth rate of Alloy 52M weld metals in

BWRs and PWRs[13][14]. For Alloy 52M weld metal, the range of the test CGR is from

sec/101 9 mm to sec/104 9 mm . Thus, for the 2nd layer, it would take 16~64 years to grow

through the second layer using the highest CGR.

4.4 Crack Growth Evaluation

For fatigue crack growth evaluation, it will be determined based on the design cyclic loads. Here, only

those transients that produce a significant change in pressure and temperature are used.For SCC crack

growth evaluation, if the stress intensity factor is tensile, crack growth into the weld overlay and the

different CGRs should be used for different layers.

The through wall stress profiles from paths due to pressure, temperature and weld residual stresses

were curved fitted into a forth order polynomial as shown in equation (1). These paths are identified in

Figure 6.Since the model does not include the thread detail, the stress in FEM correspond to the inside

surface of the rod travel housing would increase by a stress concentration factor of 4 conservatively.

The stress intensity factors for all paths are shown in Figure 15respectively. The results show that the

applied stress intensity factors for Path P234 and P415 are all compressive. For Path P112, stress

intensity factors due to the weld residual stress are tensile and are the highest.

The allowable crack size will be determined according to the ASME Section XI Appendix C for the

hypothetical flaw in the interesting location.

4.4.1 Limit Load Criteria

The allowable flaw sizes using limit load criteria are summarized in Table 1 from Table C-5310 in

Appendix C of ASME Section XI for the calculated stress ratio for all service levels. The flow stress

was calculated as the average of yield strength and tensile strength at temperature, using Alloy 52M

properties. These allowable flaw sizes are for a full circumferential crack.

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Figure 15 Stress Intensity Factor with Weld Overlay

Table 1 Allowable Flaw Size Using Limit Load Criteria

Allowable Full 360° Flaw Size (a/t) Path σm+σb (MPa) σf (MPa) Stress Ratio

Level A Level B Level C Level D

P112 29.82 373.3 0.080 0.75 0.75 0.75 0.75

P234 39.52 373.3 0.106 0.75 0.75 0.75 0.75

P415 41.82 373.3 0.112 0.75 0.75 0.75 0.75

P430 45.39 373.3 0.122 0.75 0.75 0.75 0.75

4.4.2 Linear Elastic Fracture Mechanics Criteria

From Reference [15], the test data shows that ICJ for Alloy 690 is 850 2/ mKJ in the longitudinal

direction and 750 2/ mKJ in the transverse direction. Using the formula as following, the material

fracture toughness ICK is 426 mMPa in the longitudinal direction and 400 mMPa in the

transverse direction:

21

1000/

EJK ICIC (7)

Where ICJ is material toughness due to crack extension, E is Young’s modulus and is

Poisson’s ratio.The lower value of ICK was used for allowable flaw size calculation and a safety

factor of 2.7 was used on this toughness value.

Path P112

-4.00

-2.00

0.00

2.00

4.00

6.00

8.00

10.00

12.00

14.00

16.00

2.30 2.80 3.30 3.80 4.30 4.80 5.30

Flaw depth a （mm）

Str

ess

Inte

nsity

K (

MP

a*m

^0.5

)

Pressure and Temperature

Weld Residual Stress

Path P234

-12.00

-10.00

-8.00

-6.00

-4.00

-2.00

0.00

2.30 2.80 3.30 3.80 4.30 4.80 5.30 5.80

Flaw depth a （mm）

Str

ess

Inte

nsity

K (

MP

a*m

^0.5

)

Pressure and Temperature

Weld Residual Stress

Path P415

-12.00

-10.00

-8.00

-6.00

-4.00

-2.00

0.00

5.20 6.20 7.20 8.20 9.20 10.20 11.20

Flaw depth a （mm）

Str

ess

Inte

nsity

K (

MP

a*m

^0.5

)

Pressure and Temperature

Weld Residual Stress

Path P430

-12.00

-10.00

-8.00

-6.00

-4.00

-2.00

0.00

2.00

5.14 6.14 7.14 8.14 9.14 10.14

Flaw depth a （mm）

Str

ess

Inte

nsity

K(M

Pa*

m^0

.5)

Pressure and Temperature

Weld Residual Stress

CSNI/R(2017)2/ADD1

The total applied stress intensity factor was the sum of the IK due to the pressure, temperature and

weld residual stress. The total applied IK for all paths are shown in Figure 16. It is shown that the

applied IK s for the hypothetical crack on all paths don’t exceed ICK limit values. Thus, the

allowable flaw size could be set at 75% of the all thickness.

For the fatigue crack growth is due to the cyclic loadings by pressure and temperature. The crack

growth due to the fatigue and SCC for path P112 is shown in Figure 17. For the initial flaw depth

assumed to be the original UCS thickness, it takes about 39 years to grow to the weld overlay interface

of 1st and 2nd layers. Once it crosses the interface, it doesn’t reach 75% of the total thickness within an

evaluation period of 40 years.

For the other paths, the total applied stress intensity is mostly compressive with small IK , thus the

crack growth to SCC and fatigue is insignificant.

-40

-20

0

20

40

60

80

100

120

140

160

2.3 4.3 6.3 8.3 10.3 12.3

Flaw depth a （mm）

Str

ess

Inte

nsity

K (

MP

a*m

^0.5

) P112

P234

P415

P430

Limit

Figure 16 Allowable Flaw Size for All Paths

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

8.0

0 10 20 30 40

Year

Fla

w d

epth

a (

mm

)

P112Total Thickness75% of Total ThicknessInterface of 1st and 2nd layers

Figure 17 Crack Growth Result of Path P112

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5 Summary and conclusion

This paper presented a theoretical and simulation method of CRDM upper canopy weld crack growth

analysis, with considering the residual stress during welding process and the impact of original stress

corrosion cracking environment, as well as fatigue crack growth.

The evaluation considered SCC and fatigue to determine the acceptability for operation with UCS

weld overlay.

The results of the analytical evaluation show that the crack growth does occur in Alloy 52M in PWR

environment. In the worst location path P112, it shows that for an initial flaw depth assumed to be the

original UCS thickness, it takes about 39 years to the to grow to the weld overlay interface of 1st and

2nd layers. Once it crosses the interface, it doesn’t reach 75% of the total thickness within an

evaluation period of 40 years using the reference CGR for Alloy 52M.

References

[1] C. M. Pezze and I. L. W. Wilson, “Transgranular Stress Corrosion Cracking of 304 Stainless

Steel Canopy Seal Welds in PWR Systems,” paper presented at the 4th International Symposium on

Environmental Degradation of Materials in Nuclear Power Systems – Water Reactors, August 6-10,

1989, Jekyll Island, GA and published in proceedings of same, NACE, Houston, TX, 1990, p. 4-164.

[2] ZHENG Xiaomin, “The Leakage Proble of CRDM in Ling’ao Station Unit 1,” Nuclear Safety,

No.2.2007, p. 25-29.

[3] ASME Boiler and Pressure Vessel Code, 1989 Edition, Section III and XI up to 2000 Addenda.

[4] ASME Section XI Code Case N-504-2, “Alternative Rules for Repair of Class 1, 2, and 3

Austenitic Stainless Steel Piping,” March 1997.

[5] NUREG-0313, Revision 2, “Technical Report on Material Selection and Processing Guidelines

for BWR Coolant Pressure Boundary Piping,” U.S. NRC, January 1988.

[6] Rybicki, E. F., et al., “Residual Stresses at Girth-Butt Welds in Pipes and Pressures Vessels,” U.S.

Nuclear Regulatory Commission Report NUREG-0376, R5, November 1977.

[7] Rybicki, E. F., and Stonesifer, R. B., “Computational of Residual Stressed Due to Multipass

Welds in Piping Systems,” Journal of Pressure Vessel Technology, Vol. 101, May 1979.

[8] API Standard 579-1/ASME FFS-1, Fitness-for-Service, 2nd Edition, June 2007.

[9] Chopra, O. K. Soppet, W. K. and Shack, W. J., “Effects of Alloy Chemistry, Cold Work, and

Water Chemistry on Corrosion Fatigue and Stress Corrosion Cracking of Nickel Alloys and Welds,”

NUREG/CR-6721, Division of Engineering Technology, Office of Nuclear Regulatory Research, U. S.

Nuclear Regulatory Commission, Washington D. C. April 2001.

[10] W. S. Hazelton and W. H. Koo, “Technical Report on Material Selection and Processing

Guidelines for BWR Coolant Pressure Boundary Piping,” NUREG-0313, Rev. 2, US NRC, January

1988.

[11] H. L. Gustin and S. S. Tang, “Design and Analysis of a Weld Overlay Repair for the Watts Bar

CRDM Lower Canopy Seal Welds,” prepared for Tennessee Valley Authority by Structural Integrity

Associates, San Jose, California, October 1997.

[12] M. Akashi, “Effects of Cr and Nb Contents on the Susceptibility of Alloy 600 Type Ni-base

Alloys to Stress Corrosion Cracking in a Simulated BWR Environment,” paper 407 presented at

Corrosion 95, NACE, Orlando, FL, March 1995.

[13] Materials Reliability Program: Resistance of Alloy 690, 152, and 52 to Primary Water Stress

Corrosion Cracking (MRP-237, Rev. 2): Summary of Findings between 2008 and 2012 from

Completed and Ongoing Test Programs, EPRI, Palo Alto, CA: 2013, 3002000190.

[14] NUREG/CR-7103, “Pacific Northwest National Laboratory Investigation of Stress Corrosion

Cracking in Nickel-Base Alloys,” Vol. 1 and 2, September 2011.

CSNI/R(2017)2/ADD1

[15] Brown, C. M. and Mills, W. J., “Fracture Toughness, Tensile and Stress Corrosion Cracking

Properties of Alloy 600, Alloy 690 and Their Welds in Water,” Corrosion 90, NACE International,

1996.

CSNI/R(2017)2/ADD1

OECD/NEA CSNI WGIAGE; Fourth International Conference on Fatigue of Nuclear Reactor Components

28th September-1st October, 2015, Sevilla, Spain

Short Crack Behavior of Austenitic Stainless Steels in Simulated PWR Primary Water during Fatigue Damage and Monotonic Deformation

Choongmoo Shim Tohoku University, Japan, shim.choongmoo@rift.mech.tohoku.ac.jp

Yoichi Takeda

Tohoku University, Japan, takeda@rift.mech.tohoku.ac.jp

Tetsuo Shoji Tohoku University, Japan, tshoji@fri.niche.tohoku.ac.jp

Xiangyu Zhong

Tohoku University, Japan, xyzhong@fri.niche.tohoku.ac.jp

Shirish Chandarakant Bali Tohoku University, Japan, shirishbali@gmail.com

SUMMARY

Low cycle fatigue tests were performed using type 316 stainless steel at 325°C in a simulated PWR primary water and air at room temperature to evaluate short fatigue crack growth behavior using crack distribution. Some of LCF tests in a simulated PWR primary water were interrupted to evaluate the cumulative damage of short fatigue cracks at given cycles by examining the number of cracks and their depth on cross sections along the gauge length. The results were comapred to LCF test in air and SSRT test in a simulated PWR primary water. The results show that cracks have continued to initiate during the LCF test and most of cracks initiated especially in the early stage in a simulated PWR primary water. Crack initiation and propagation dominant region was also distinguished and defined by using the crack distribution at given cycles.

Keywords: Low Cycle Fatigue Test, Short Fatigue Crack Growth Behavior, Simulated PWR Primary Water.

1. Introduction Various degradations occur in during the operation of nuclear power plant. Especially,

fatigue damage has been cumulated in pressure vessel steels and piping materials for a long operation period, so that reduction in fatigue life occurs. It is important because those of problems are closely linked to structure integrity and safety of nuclear power plants. In general, many researches have been concentrated on fatigue life of structure materials in air and PWR water.

CSNI/R(2017)2/ADD1

Especially, austenitic stainless steels have been widely used in this field because of good mechanical properties and corrosion resistance in high temperature water, however, it is known to exhibit fatigue life in simulated pressurized water reactors (PWRs) primary water by a factor of 20 lower in relative to those in air [1, 2].

Many researches have been performed to know the effect of various mechanical or

environment condition on reduction in fatigue life and crack growth. G.L.Wire et al. [3] and David Tice, et al. [4]. studied the effect of ∆K, stress ratio, hold time rise time, temperature on crack propagation. These tests were performed using compact tension specimen for the long crack behavior which can be explained by Linear Elastic Fracture Mechanics (LEFM), however, it has been found that the short crack growth rate can be significantly greater than the corresponding long crack growth rate [5], so that it is not conservative to apply to short crack behavior [6]. Therefore, it has been very important to know the short crack behavior. Most of researches about short crack growth behavior have been studied to evaluate the regime between short and long crack in air. It has been well known that short crack growth behavior strongly depends on microstructure. In addition, it was found that fatigue cracks initiated along strain localized areas and crack linking was the main mechanism of the early crack growth [7]. Most of studies about short crack growth behavior in air were used by replica. Therefore, it is possible to investigate the path of crack growth, however, there is difficulty using replica investigation in a simulated PWR primary water. Therefore, it has been not enough to understand short crack growth behavior. O. K. Chorpa et al. performed with the LCF test in Light water reactor environments and air to evaluate the formation of fatigue cracks and growth of austenitic stainless steel in various environments were discussed [8]. However, it was limited to investigation of crack frequency to compare crack initiation in various environments.

In this study, by means of the smooth specimen without notch, short fatigue crack growth

behavior in the strain-controlled Low cycle fatigue (LCF) tests was investigated. In order to evaluate short crack growth behavior in a simulated PWR primary water, interrupted LCF tests were performed and cracks were examined at given cycles. The results obtained were compared with the LCF tests in air at room temperature and SSRT (Slow Strain Rate Tensile) tests in a simulated PWR primary water at 325°C. 2. Experimental detail 2.1. Material and test specimen

The material used in the present study was 316 stainless steel which chemical composition

and mechanical properties are shown in table 1 and 2, respectively. Two kind of tubular smooth specimens were used with LCF test and SSRT test in a simulated PWR primary water. During the tests, a simulated PWR primary water was flowed through the inside of the tubular specimen, consequently damage occured from inner surface to outer surface. The inner surface of the tubular specimens was fabricated by drilling process followed by honing process and one specimen was fabricated by only dirilling process for the SSRT test. For the LCF test in air, the smooth cylindrical specimen was used. The outer surface of specimen was polished up to #800 along the loading direction. The geometries and dimensions of specimens were shown in Figure 1.

2.2. LCF Test and SSRT Test

LCF tests and SSRT tests were performed in a simulated PWR primary water (B: 500 ppm

as H3BO3, Li: 2 ppm as LiOH). During the tests, Dissolved Hydrogen (DH), Dissolved Oxygen (DO) and temperature in the present study was controlled with 30 cc STP H2/kg, < 5 ppb, 325°C respectively and those condition were contiuously monitored during tests. Fully reversed strain-controlled LCF tests were performed with strain amplitude of ± 0.6% (Stress ratio, R = -1), saw-

CSNI/R(2017)2/ADD1

tooth waveform which is strain rate of 0.001%/s and 0.04%/s in tension and compression respectively. Strain was controlled by a two point extensometer of 25 mm gauge length attached to the outer surface of the specimen. During the tests, some of LCF tests in a simulated PWR primary water were interrupted to evaluate the crack growth and crack distribution when the number of cycles reached at predetermined cycles, that were 41, 50, 110, 140 cycles. LCF tests were also performed using the smooth cylindrical specimen in air at room temperature to compare short crack growth behavior of those in a simulated PWR primary water. Strain amplitude was the same as that applied for the tests in a simulated PWR primary water and the triangle waveform with strain rate of ± 0.2%/s in tension and compression was applied in the tests. In order to observe the propagation process of a main crack, LCF test was interrupted at a given cyclic loading interval, which is almost every 500 cycles and replica investigation were performed at given cylic loading interval SSRT tests were also conducted with the strain rate of 2×10-7s-1. SSRT tests were interrupted when the load reached the maximum on the the load-displacement cuve.

After tests, longitudinal cross section was cut by using mechanical cutting device and the

surface of the cross section was polished using up to 1 μm diamond paste followed by colloidal silica to observe cracks. The number of cracks and their depth was observed by Scanning Electron Microscopy (SEM, Hitachi, SU-70). The observed place was the surface of longitudinal cross sections with the gauge length of 25 mm, which is cut along the loading direction. These analyses were conducted on four cross sections of the specimen. Hardness test was conducted by Nano indentation (Ficsher, WIN-HCU) with HV 0.01 on the tubular smooth specimen fabricated by honing process before and after LCF tests in a simulated PWR primary water and cylindrical smooth specimen after the test in air. Hardness was measured with every 50 µm between 50 μm and 400 μm from the surface. Hardness of tubular specimen was measured from the inner surface and that of smooth cylindrical specimen in air was measured from the outer surface.

3. Test Result and Discussion 3.1. LCF Test and SSRT Test Results

The fatigue lives (Nf) were obtained by LCF tests in a simulated PWR primary water and air

at room temperautre, where fatigue life (Nleak) was defined as the number of cycles at which water in the tubular smooth specimen leaked from inside to outside in simulated PWR primary water. Those for air environment was denoted as fatigue life (N25) which was defined as the number of cycles at which tensile stress decreased in 25% from the steady-state stress during the test. Figure 2 shows fatigue lives obtained from LCF tests together with ASME (American Society Mechanical Engineers) design fatigue curve in a simulated PWR primary water and Tsutsumi Curve and that shown by Jaske & O’Donnell in air [1, 9-10]. The detail about fatigue lives from the result in this study was also shown in Table 3.

Cyclic stress response in a simulated PWR primary water and air at room temperature about

cycle (a) and life fraction (b) was plotted in Figure 3. The maximum peak stress in both environment is similar as a stress of 350 MPa, however, the behavior for a change in peak stress is different. Once LCF tests started, stress hardening occured immediately and peak stress was decreased by softening in both environment, however, the range of hardening in a simulated PWR primary water was occupied almost half of the fatigue life. In contrast, the range of hardening in air was short. It seems to be influenced by a simulated PWR primary water.

Figure 5 is the stress-strain curves obtained from SSRT test of 316 stainless steel with

different machining in a simulated PWR primary water. The stress-strain curves show that the test

CSNI/R(2017)2/ADD1

with the tubular smooth specimen fabricated by drilling process was shorter than that by honing process. Based on this result, the elongations of the specimens were significantly influenced by machining.

3.2 .Crack Distribtuion

After finishing tests, crack morphorogies on cross sections were observed. Cracks were

initiated at inner surface and propagated to outer surface in a simulated PWR primary water due to the environmental effect, while cracks were initiated at outer surface for the smooth cylindrical specimen in air at room temperature. Figure 6 shows cross sectional images examined by SEM. Cracks were easily observed although very small cracks existed on the cross section. Therefore, it was possible to examine and distinguish most of cracks existing on the cross section with the gauge length of 25 mm to show crack distribution. Crack distribution was obtained by the nmuber of cracks and their depth on longitudinal cross sections in both environments and expressed as a histogram. Figure 7 shows histograms obtained from 4 longitudinal cross sections for the LCF test interuppted at 110 cycles in a simulated PWR primary water. In this result, each crack distribution shows a similar behavior at 110 cycles and most of other crack distribution also had similar behavior at each given cycle. It was thought that the behavior of crack distribution was not different. Therefore, it can be no matter although any cross sections were selected to examine crack distribution. Based on the result, it was possible to use a representative crack distribution instead of those observed from each cross section and compare each crack behavior at given cycles using the representative crack distribution. In this study, average crack distributions examined on two cross sections was used as a representative crack distribtuion. Figure 8 shows histograms as an average crack distribtuion for the LCF test in a simulated PWR primary water. The result indicated that an increase in the number of cycles led the location of crack depth distribution gradually from small size to large size (a-e), however, small cracks still existed in the end of the LCF test in a simulated PWR primary water (e) and air (f). Hisgotrams for SSRT tests (g), (h) also shows that many small cracks exsited in the end of the test. It was thought that cracks were kept initiating during tests although many cracks existed in the specimen.

Figure 9 is the fraction of crack distribution using average crack distributions for LCF tests

(a) and SSRT tests (b). In case of the LCF test, It was found that the fraction for cracks above 50 μm in a simulated PWR primary water was occupied about almost 40% of total fraction, however less fraction for cracks above 50 μm were occupied, by contrast, more fraction for small cracks were distributed in air as compared to that in a simulated PWR primary water. Okazaki et al. studied the effect of grain on crack propagation of 304 stainless steel in air at high temperature and they reported that once the small cracks had grown up to a few grain size, they predominatly propagated with strain cycling, while most of small cracks stopped propagating, when they grew up to one grain size [8]. For this reason, fraction for small cracks can be large in air as compared to a simulated PWR primary water. It can be also supported by histograms as shown in figure 8. There were few cracks which were propagated predominantly and no crack which was propagated in a gap between about 500 μm and 1.5 mm (f) and most of cracks except few cracks were distributed in small size. In contrast, the gap was small in a simulated PWR primary water for the LCF test (e) and SSRT test (g), (h). Based on these results, there was possibility that microstrucure effect was decreased in a simulated PWR primary water, so that more cracks than that in air can be propagated in a simulated PWR primary water.

There was also possibility that crack growth was influenced by hardness effect from honing

process. Figure 10 shows hardness results before the test, after the test in a simulated PWR primary water and in air. Hardness in a simulated PWR primary water was entirely high as compared that in air, especially hardness near the inner surface was higher than bulk material

CSNI/R(2017)2/ADD1

becasue of honing effect and the distance influenced by honing process was about 100 μm from the inner surface. Therefore, it was also thought that hardness may influence crack propagation.

3.3. Crack Initiation and Propagation

Figure 11 shows the three curves for groups, which was seperated by crack size at each given

cycle and curves were comapred with each other using average crack distribution. The average number of total cracks were increased with increasing the number of cycles, especially about 70% of cracks initiated in the region between starting the test and 50 cycles and the average number of cracks below 5 μm was also increased, however, it was decreased after 50 cycles. It indicated that most of cracks may initiate in the early stage. Therefore, it was thought that the region between starting the test and 50 cycles can be defined as a crack initiation-dominant region. Increase rate in the number of total cracks became constant and the number of cracks below 5 μm started to decrease after 50 cycles. In addition, the number of cracks above 50 μm started to increase slightly from 41 cycles followed by increase drastically in the region between 110 and 140 cycles. The result may be explained by cyclic stress response in Figure 4. Above mentioned, Stress hardening was finished at about 110 cycles. While the positive strain has been increased, cracks were propagated and opened, thereby stress to reach peak strain has been gradually smaller than a previous cycle. Based on this result, it was thought that the region between 50 cycles and 110 cycles can be difined as trainsition region and aslo the region after 110 cycles can be defined as a crack propagation-dominant region.

3.4 Crack Growth Rate

Figure 12 represented a propagation of crack length and depth for the LCF test in air and a

simulated PWR primary water respectively. It was shown that crack were slowly propagated in the early stage, while, crack was markedly propagated in the end of the test. Figure 13 shows crack growth rate by crack length and depth in air and a simulated PWR primary water. The crack growth rate of the LCF test can be calculated by using equation (1), where ∆N and ∆a denoted the cyclic interval and crack depth or length respectively, a i is the deepest crack depth or length at Ni cycles.

𝑑𝑎

𝑑𝑁=

∆a

∆𝑁=

𝑎𝑖 − 𝑎𝑖−1

𝑁𝑖−𝑁𝑖−1 (1)

The average crack growth rate of the LCF test can be calculated by using equation (2), where

∆N and ∆aavg denoted the cyclic interval and average crack depth or length respectively. ak is each crack depth of existing cracks on cross sections at given cycle Ni.

𝑑𝑎

𝑑𝑁𝑎𝑣𝑔=

∆𝑎𝑎𝑣𝑔

∆𝑁=

∑ 𝑎𝑘=𝑛𝑖𝑘=1 𝑘

𝑛𝑖 −

∑ 𝑎𝑘=𝑛𝑖−1𝑘=1 𝑘

𝑛𝑖−1

𝑁𝑖 − 𝑁𝑖−1 (2)

Figure 13 (a, b) shows the maximum crack grwoth rate in air and a simulated PWR primary

water. The maximum crack grwoth rate in air had repeated increase and decrease. It has been reported by many researches [11-13]. K. Hussain at al. said that short crack growth rate is affected by the microstructure and it decreases when the crack approaches the grain boundary and increases again when it crosses the grain boundary [14]. After that, it was suddenly increased at almost end of the test in the present study. On the other hand, maximum crack growth rate in a simulated PWR primary water started to increase at about half of the test period. It was thought that the time when crack started to be preominantly propagated was earlier than in air. As above mentioned, it was also shown that propagation of crack can be influenced by a simulated PWR primary water. Figure 13 (c) also shows the average crack grwoth rate. It shows similar behavior

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with maximum crack growth rate, however, it started to decrease after 140 cycles. It was thought that very few cracks can be propagated after 140 cycles. 4. Conclusion

The short fatigue crack growth behavior on 316 stainless steel in a simulated PWR primary water at 325°C and air at room temperature was investigated and compared to SSRT test in a simulated PWR primary water. The following conclusions can be derived from these tests:

(1) Although cracks below 5 μm exsited, cracks can be easily observed by SEM, so that it is

possible to express the histogram using crack distribtution. Crack distribution behavior observed on the surface of the four cross sections shows similar behavior, therefore it was possible to express a representative crack distribution in order to compare crack distribution at each given cycle.

(2) Most of cracks were initiated in the early stage and cracks can be continuted to initiate in

the end of the test although many cracks were predominantly propagated and after 140 cycles very few cracks can be propagated

(3) A simulated PWR primary water may decrease the effect of microstructure on the crack

growth. (4) Crack initiation-dominant region, transition region and crack propagation-dominant

region can be seperated and defined by using a representative crack distribtuion in simulated PWR primary water.

Table 1. Chemical composition of the test material

C Si Mn P S Ni Cr Mo

0.05 0.37 1.46 0.026 <0.001 11.52 16.58 2.08

Table 2. Mechanical properties of the test material

0.2% Proof strength Tensile strength Elongation Reduction of area

261 MPa 544 Mpa 59 % 83 %

Table 3. Fatigue lives of LCF tests

Environment Strain rate (%/s) Temperature N f (cycle)

PWR water 0.001/0.04 325°C 219

Air 1 0.2/0.2 R.T 6259

Air 2 0.2/0.2 R.T 6684

Air 3 0.2/0.2 R.T 6150

Air 4 0.2/0.2 R.T 5750

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(a) Tubular smooth specimen (b) Smooth cylindrical specimenin

(c) Tubular smooth specimen for SSR test

Figure 1. Geometry and dimension of test specimens

Figure 2. Fatigue lives obtained in a simulated PWR primary water and air at room temperature

Figure 3. Cyclic stress response during the LCF test

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Figure 5. Stress-strain curves for 316 stainless steel of SSRT tests in a simulated PWR primary water with different machining process

Figure 6. Observation of crack depth on the cross section at each given cycle

Figure 7. Histograms for crack distribution on each cross section interrupted at 110 cycles in a simulated PWR primary water for the LCF test

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Figure 8. Histograms for average crack distribution observed on two cross sections for all tests

Figure 9. Fraction of crack distribution for (a) LCF tests, (b) SSRT tests

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Figure 10. Hardness test for the tubular specimen before and after the test in a simulated PWR primary water and the smooth cylindrical specimen in air

Figure 11. The representative crack distribution using the average number of cracks

Figure 12. Change in crack size in (a) air and (b) a simulated PWR primary water

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Figure 13. Crack growth behavior (a) crack growth rate in air, (b) crack growth rate, (c) average crack growth rate in a simulated PWR primary water respectively

REFERENCES

[1] O. K. Chopra, “Mechanism and estimation of fatigue crack initiation in austenitic stainless steels in LWR environments.” No. ANL-01/25. Argonne National Laboratory, 2002. [2] JNES-SS report, “Environmental fatigue evaluation method for nuclear power plants.” (JNES-SS-1005), Japan Nuclear Energy Safety Organization, 2011 [3] G. L. Wire, W. M. Evans and W. J. Mills. "Fatigue crack propagation of 304 stainless steel in high temperature water: additional tests and data correlation" ASME 2005 Pressure Vessels and Piping Conference. American Society of Mechanical Engineers, 2005, pp. 207-222 [4] David Tice, Norman Platts, Keith Rigby, John Stairmand and David Swan, "Influence of PWR primary coolant environment on corrosion fatigue crack growth of austenitic stainless steel." ASME 2005 Pressure Vessels and Piping Conference. American Society of Mechanical Engineers, 2005, pp. 193-205. [5] S. Suresh, "Fatigue of Materials Cambridge University Press." Cambridge, UK, 1991. [6] Pearson, S. "Fatigue crack propagation in metals." 1966. [7] K Obrtlı́k, J Polák, M Hájek, A Vašek, "Short fatigue crack behaviour in 316L stainless steel." International journal of fatigue, 19.6, 1997, pp. 471-475. [8] Omesh K. Chopra, and Daniel J. Gavenda, "Effects of LWR coolant environments on fatigue lives of austenitic stainless steels." Journal of pressure vessel technology, 120.2, 1998, pp. 116-121. [9] C. E. Jaske, and W. J. O’donnell. "Fatigue design criteria for pressure vessel alloys." Journal of Pressure Vessel Technology, 99.4, 1977, pp. 584-592. [10] K.Tsutsumi, Kanasaki H., Umakoshi, T., Nakamura T., Urata, S., Mizuta H., and Nomoto S., “fatigue life reduction in PWR water environment for stainless steels,” PVP-Vol, 410.2, American Society Mechanical Engineers, New York, 2000, pp. 23-34 [11] Masakazu Okazaki, Toshio Yada, and Tomohiro Endoh. "Surface small crack growth behavior in low-cycle fatigue at elevated temperature and application limit of macroscopic crack growth law." Nuclear engineering and design, 111.1, 1989, pp. 123-134 [12] G.J. Deng, S.T. Tu Q.Q. Wang, X.C. Zhang, F.Z. Xuan, Small fatigue crack growth mechanisms of 304 stainless steel under different stress levels." International Journal of Fatigue, 64, 2014, pp. 14-21. [13] S.Suresh, and R. O. Ritchie. "Propagation of short fatigue cracks." International Metals Reviews, 29.1, 1984, pp. 445-475. [14] K. Hussain, E. R. De Los Rios, and A. Navarro. "A two-stage micromechanics model for short fatigue cracks." Engineering Fracture Mechanics, 44.3, 1993, pp. 425-436

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Effect of Shoulder Extension Control on Fatigue Endurance Testing of Stainless Steels A McLennan*, A Tweddle†, J Meldrum*, J Holden*, L McVey*, C Austin*, N Platts* and M Twite† Corresponding author: alec.mclennan@amecfw.com *Amec Foster Wheeler, 404 Faraday Street, Birchwood Park, Warrington, WA3 6GA, UK †Rolls-Royce plc, PO Box 2000, Raynesway, Derby, DE21 7XX

ABSTRACT Current fatigue endurance testing standards (e.g. BS 7270, ASTM E606) require strain-controlled tests to be performed using gauge length mounted extensometry. However, for tests conducted in a high temperature water environment within an autoclave it is normally not possible to use a gauge length extensometer because of interference from seals or problems resulting from crevice effects on the specimen gauge length. For this reason many laboratories use shoulder-mounted extensometry for control of cyclic displacement during autoclave testing which, for austenitic stainless steels, can result in an error between the nominal applied cyclic strain range and the actual strain range in the specimen gauge length. This error is caused by the difference in cross-sectional area between the specimen shoulders and specimen gauge length, which results in differences in stress levels and, hence, in extent of the complex cyclic hardening and softening behaviour displayed by these alloys.

To minimise such errors, a correction may be made to the displacement control waveform applied to the specimen shoulders in order to result in the intended cyclic strain range in the specimen gauge length. Accurate correction is especially important when testing complex waveforms.

Currently employed methodologies for correcting cyclic displacement control at specimen shoulders have been reviewed and the potential impacts of the different approaches have been assessed. Dual extensometer tests, employing both shoulder and gauge length mounted extensometers, have been conducted in air at both 300 °C and room temperature in order to measure the changes in cyclic shoulder displacement through the fatigue lives of austenitic stainless steel specimens for a range of gauge length strain amplitudes and strain rates.

These studies enable quantification of errors in the strain range and mean strain in the specimen gauge length, and the effectiveness of correction methods to be assessed. The impact of these errors in terms of data scatter is discussed. This includes the potential effect on derivation of fatigue design curves (S-N curves) when using the approach of NUREG/CR-6909, in which a design curve is derived from a best fit to a database of fatigue test results by application of factors which consider scatter in the database.

INTRODUCTION The fatigue life of Light Water Reactor (LWR) components are typically assessed against design codes such as the ASME Boiler and Pressure Vessel Code (BPVC), Section III1, which provide fatigue design curves based on an extensive database of air fatigue data primarily generated at ambient temperature. The ASME BPVC requires that the impact of environment be accounted for when calculating the fatigue usage factors but do not specifically state how. NUREG/CR-69092 gives a method for taking the effect of environment into account using formulae for “environmental correction factors”, which were developed from Environmentally Assisted Fatigue (EAF) experiments conducted in high temperature water. This approach assumes that the effects of environment may be accounted for in a simple way by applying an environmental factor to air design data; it also assumes that other transference factors used to derive a conservative design fatigue curve from a best fit to test data are unaffected by the environment. There remains a continuing requirement for fatigue life data generation in high temperature water environments in order to better understand the conservatisms within code design curves and how best to account for the effects of environment.

The air data underpinning the ASME BPVC fatigue design curves were largely generated in accordance with strain controlled axial fatigue test standards such as ASTM E6063 and BS 72704 which are focussed on testing of solid bar specimens in air at room temperature, but with some provision for high temperature work.3 These

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standards require strain to be controlled using gauge length extensometry, which can present significant practical problems in high temperature water environments where conventional gauge length extensometry, as used in air, is not readily adaptable to use in an autoclave. Most of the currently available solid bar fatigue life data for high temperature water environments relevant to LWR components were generated using shoulder mounted extensometry. There is, therefore, a need to understand the impact of shoulder displacement control on gauge length strain and the applied strain waveforms, and the potential errors resulting from shoulder displacement control that are inherent in published test results.

The fundamental need for accurate strain control in environmental fatigue endurance tests has led to the use of Linear Variable Displacement Transducer (LVDT) extensometry, which is capable of operating in LWR coolant environments within an autoclave and can be applied to the specimen gauge section. An alternative method of strain control, based on measurement at the specimen shoulders as opposed to gauge control, has been adopted by many laboratories. For shoulder control the LVDT extensometer is clamped to the shoulders of a specimen (Figure 1 a) typically using knife edges. This particular method is well established and utilised by test facilities such as Amec Foster Wheeler5, Argonne National Laboratory2 and Areva6. A method of gauge length control in autoclave testing has been developed by VTT7 utilising a LVDT situated below the specimen but connected to the gauge length by knife edges (Figure 1 b).

Each of these EAF test control methods has strengths and weaknesses associated with it. The main strengths of using a gauge control method similar to that used by VTT are certainty over the waveform applied to the specimen gauge length throughout the test (even with complex of cyclic hardening / softening behaviour), providing direct comparability of results to air data, and compliance with test standards. The weaknesses of this type of method are the compromise between having enough loading force to prevent knife edge slippage whilst not indenting the specimen, some additional limitations on the environments that tests can be performed in and in ensuring accurate mechanical transfer of strain over the long distances from the knife edges to the transducer, which is located inside the autoclave. With this type of in-autoclave strain control, the issue of specimen surface indentation is of major concern due to the possibility of invalidating the test or causing early crack initiation. This issue is affected not just by the loading force of the knife edges but also by how the extensometer is supported in the experimental frame, both of which require careful design. The second issue with knife edge contact is the potential for a crevice to form at the contact point on the gauge length surface. This can be a significant issue in oxygenated water where crevice corrosion can undermine the validity of the experiment. In fact, the VTT method addresses these weaknesses by using a specimen with a slightly increased diameter for a short length just beyond each end of the true gauge length. The knife edges are in contact with the surfaces of these larger diameter regions, which ensures that any indentations or crevice corrosion occurs outside the gauge length; however, this introduces a slight error to strain control in the gauge length (although a correction could be applied for this).

Figure 1: a. Specimen prior to testing in high temperature water in a Amec Foster Wheeler fatigue rig.5 b. Graphical representation of extensometry used in VTT FABELLO rig.8

a.

b.

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The use of shoulder control removes the issues associated with gauge length control methods but has drawbacks of its own. The major benefit of shoulder control is that, by mounting the LVDT extensometer to knife edges on the shoulder, clamping or contact forces (and resultant surface indentations) in the gauge length are no longer an issue. Similarly, even though a crevice is still formed it is remote from the gauge section and will cause galvanic effects only in the most conductive environments. The major drawbacks of this methodology are that there will be uncertainty in the waveform applied to the gauge material (in which the fatigue failure occurs) because strain is controlled from a location remote from the gauge length, the method is not compliant with current testing standards, and results may not be directly comparable to air test data. The primary concern is that when a desired waveform is applied to the shoulders of the specimen the gauge length will be subjected to a related but different waveform. This means that the actual cyclic strain in the gauge section of a specimen tested in an autoclave may be significantly different to the cyclic strain in a specimen tested in air under the same nominal loading conditions. To deal with this issue, a correction must be applied to the extension at the shoulder in order to produce the correct cyclic waveform in the gauge length.

The relationship between the cyclic strain waveform controlled at the specimen shoulders and the waveform experienced in the gauge length is not simple. The relationship is dependent upon the strain amplitude (εa) and varies throughout a test due to the differences in complex cyclic hardening and softening behaviour that occur between the larger diameter shoulder and the smaller diameter gauge section, and through the specimen blend radius.

There are two methods of correcting for difference between the waveform applied at the specimen shoulder and the waveform experiences by material in the specimen gauge section:

a) Single correction factor – the use of a single constant correction applied to the control waveform at the specimen shoulders throughout each test.

b) Full correction function – the applied displacement is corrected by using a function that varies the correction factor during a test to account for differences in cyclic hardening and softening between the specimen shoulders and the gauge length.

The simplest method is expected to be the single correction factor as it should be possible to generate a set of correction factors, dependent on strain amplitude, for one material type (e.g. one grade of material) using relatively few calibration tests. The full correction function requires significantly more material and time to generate a calibration function for each set of testing conditions (strain amplitude, strain rate, temperature, etc.), and is more difficult to apply in control software during testing. Although the single correction factor is less accurate, as it does not account for hardening and softening of the material during a test, the resultant errors are considered to be insignificant over a range of test parameters.

The current paper present a method of correcting shoulder control using a single correction factor based on experimental results, and discusses potential limitations of this method.

EXPERIMENTAL In order to generate correction factors to be applied to shoulder extension when performing tests in a LWR environment within an autoclave, a series of uniaxial fatigue tests was performed in air with strain controlled in the gauge length and extension measured at the specimen shoulders. These experiments were performed by Amec Foster Wheeler in laboratory air at both 21 °C and 300 °C. The materials used for specimen manufacture were the same two heats of type 304L stainless steel used by Amec Foster Wheeler for the EAF experiments described in a recent paper by Platts et al.5; the analysed compositions of both heats were consistent with the 304L grade of stainless steel. The first heat was a section of hot rolled plate denoted as MT643 and the second heat a section of heat treated forged pipe denoted as AS216. The specimens (Figure 2) used for testing were machined to the same specification as those by Platts et al.5

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Figure 2 Specimen manufacturing diagram for dual extensometer tests.

The tests were controlled from an extensometer mounted directly to the gauge length, with a second extensometer mounted to the shoulders of the test piece to measure the shoulder extension during testing. These experiments are referred to as “dual extensometer” tests. The experimental arrangement is shown in Figure 3. The dual extensometer testing was conducted using a triangular waveform using R = -1 (with respect to strain), at strain amplitudes of 0.2 %, 0.3 %, 0.6 % and 0.8 %, and at a strain rate of 0.1 % s-1, with a single test to date also being performed using a strain rate of 0.01 % s-1.

Figure 3 Extensometer arrangement for calibration tests

The experiments were terminated either at specimen separation (Nf), see Figure 4, or at a pre-determined number of cycles at which point the test was classed as a “run out”. The data that were recorded during testing consist of, for each cycle, the maximum and minimum extension (at the specimen shoulders and over the specimen gauge length) and the maximum and minimum applied load. Values at the half life of the specimen (Nf/2) were calculated and were used in analysis; these are presented in Table 1. Values taken at Nf/2 are generally in the “steady-state” region of cyclic hardening and softening behaviour for this material type (as shown in Figure 4) and so are considered to be reasonable “typical” values to represent the entire test. From these data, the test end point was used to calculate the half life of the specimen (Nf/2) and the maximum and minimum extensions at the shoulders of the specimen at half life.

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Figure 4: Typical cyclic hardening and softening behaviour of unstabilised austenitic stainless steels under strain-controlled fatigue testing.

RESULTS An example of raw data gained from a dual extensometer test is shown in Figure 5. The shoulder displacement amplitude (SDA), the shoulder displacement at the peak tensile load during the cycle (SDT), the shoulder displacement at the peak compressive load (i.e. minimum load) during the cycle (SDC), and the mean shoulder displacement during the cycle (SDM) have been calculated at Nf/2 for each dual extensometer test and these values are given in Table 1. For these tests at R = -1, SDA is one half of the total shoulder extension range, i.e. (SDT - SDC)/2. SDM is given by (SDT + SDC)/2. In addition, SDA as a percentage of SDT and SDC has been calculated and is shown in Table 1.

Specimens tested at εa = 0.8 % and room temperature (T2-383 and T2-383) experienced secondary hardening (see Figure 4) during testing which began prior to Nf/2. Therefore two sets of shoulder displacement data are reported for these tests, one at Nf/2 and one at N = 200 cycles, which corresponds to the minimum tensile peak load prior to the secondary hardening. The shoulder displacements at 200 cycles are considered to provide a better comparison with results from testing at other strain amplitudes. Specimen T2-386, tested at εa = 0.8 % and 300 °C, did not experience secondary hardening; therefore, only one set of shoulder displacement data is presented. The 0.2 % strain amplitude tests conducted on material MT643 were all run-outs and therefore the data used in this work were taken from an appropriate part of the steady state region of the test stress vs. cycles plot.

An example of the data collected at εa = 0.3 % from the shoulders of the specimen during a dual extensometer test is presented in Figure 5. The small red and large blue points represent maximum and minimum displacement data (SDT and SDC) respectively and the mid-sized green points show the development of the mean shoulder displacement (SDM) as a function of cycle number. It is clear from the data that the mean shoulder displacement establishes itself within the first few cycles and then remains approximately constant with further cycling. Figure 5 also shows the effect of cyclic hardening and softening on the minimum and maximum shoulder displacements which presents as an initial increase in shoulder displacement magnitude in the early cycles before a slower softening and achievement of a steady state.

Figure 6 presents the dependency of SDM on εa for the experiments conducted at 21 °C and 300 °C. These data show no significant mean displacement (indicating a mean strain) at εa = 0.2 %, but a general trend of increasing mean strain with increasing εa . However, the graph clearly shows a large scatter in the SDM data, particularly at 300 °C, indicating a possible dependency of SDM on temperature. The single lower strain rate (0.01 % s-1) point at εa = 0.45 % and a temperature of 300 °C (Figure 6) also shows significantly lower mean shoulder displacement than the other data, possibly indicating that SDM is strain rate dependent, but more data at a range of strain rates would be required to confirm this.

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Table 1: Summary of results from the dual extensometer tests.

a Run-out test b Tested using a strain rate of 0.01 % s-1. All other tests carried out using a strain rate of 0.1 % s-1.

Figure 5: Shoulder displacement data for a dual extensometer test with applied strain amplitude of 0.3 % in the gauge length

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T2-380a MT643 21 0.2 N/A 15,000 48.30 -49.80 49.05 -0.75 101.55 98.49 T2-388a MT643 300 0.2 N/A 100,000 45.65 -52.58 49.12 -3.47 107.59 93.41 T2-377 MT643 21 0.3 91,818 45,909 80.60 -63.20 71.90 8.70 89.21 113.77 T2-379 MT643 300 0.3 35,000 17,500 71.70 -61.20 66.45 5.25 92.68 108.58 T2-392 AS216 21 0.3 75,769 37,885 71.47 -44.50 57.98 13.48 81.13 130.30

T2-387b MT643 300 0.45 7977 3989 97.70 -92.17 94.93 2.77 97.17 103.00 T2-389 MT643 300 0.45 7100 3550 126.07 -70.77 98.42 27.65 78.07 139.07 T2-375 MT643 21 0.6 1,722 861 162.00 -115.60 138.80 23.20 85.68 120.07 T2-376 MT643 21 0.6 2,371 1,186 161.90 -108.70 135.30 26.60 83.57 124.47 T2-378 MT643 300 0.6 3,795 1,898 142.60 -126.70 134.65 7.95 94.42 106.27 T2-391 AS216 21 0.6 8574 4287 184.00 -92.90 138.45 45.55 75.24 149.03

T2-382 MT643 21 0.8 1,131 566 211.10 -156.90 184.00 27.10 87.16 117.27 0.8 200 197.40 -149.70 173.55 23.85 87.92 115.93

T2-383 MT643 21 0.8 1,193 597 235.10 -142.70 188.90 46.20 80.35 132.38 0.8 200 214.80 -137.70 176.25 38.55 82.05 128.00

T2-386 MT643 300 0.8 2557 1279 239.77 -136.93 188.35 51.42 78.56 137.55

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Figure 6: The development of the mean strain offset at the specimen shoulders with strain amplitude controlled from the gauge length of the specimen.

Figure 7 presents relationships between the applied strain amplitude in the specimen gauge length and the measured shoulder displacement amplitude (SDA) for two temperatures, based on results of dual extensometer tests presented here. These relationships were used by Platts et al.5 as “calibration curves” to allow calculation of approximate strain amplitudes in the gauge sections of test specimens based on the applied amplitudes at the specimen shoulders. For all tests, the shoulder displacement amplitudes plotted were based on measurements at Nf/2. For the tests conducted at εa = 0.8 %, which experienced secondary hardening, the values at saturation (N = 200 cycles) were used for the fitted curve, although values at half life are also plotted. Comparison of the data generated for each of the heats suggests that there may be a heat-to-heat variability effect on the calibration curves, with an apparently greater effect at εa = 0.3 % than at εa = 0.6 %. More data are required in order to understand whether this indicates a significant difference that may warrant the development of heat-specific calibration curves.

Figure 7 also shows that the calibration curve for tests conducted at 300 °C on MT643 material may differ slightly from that generated for the data collected at 21 °C. Unlike for mean shoulder displacement, the data generated from the test completed at 300 °C and a strain rate of 0.01 % s-1, when compared to a similar experiment done at a strain rate of 0.1 % s-1, suggest no significant effect of strain rate on the relationship between gauge length strain amplitude and SDA.

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21 C: Strain vs. Mean Shoulder Displacement AS216

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Figure 7: Shoulder displacement amplitude vs. controlled gauge length strain

Figure 8 presents an alternative method for correcting for both the shoulder displacement amplitude (SDA) and the mean shoulder displacement (SDM) in order to achieve the intended cyclic strain waveform in the specimen gauge section by fitting two separate lines to the minimum and maximum data (SDT and SDC) at half life. The separate corrections for SDT and SDC may be applied to the control waveform at the specimen shoulders during testing.

Figure 8: Measured maximum (tensile) and minimum (compressive) shoulder displacements at half life as a function of strain amplitude applied in the specimen gauge length.

DISCUSSION The dual extensometer studies were undertaken to allow correction of applied shoulder displacement during strain-controlled EAF testing in an autoclave in order to attain the intended cyclic strain waveform in the specimen gauge length. This was achieved by the generation of calibration curves relating gauge length strain amplitude to shoulder displacement amplitude, where the curves provide a single correction factor to be applied throughout each test. The data generated warrant further consideration due to the presence of mean strain observed at the shoulders, which is not accounted for by a correction factor based only on differences in amplitude between the shoulders and the gauge length. Also the use of shoulder displacement control and the

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application of this calibration curve require the acceptance of certain assumptions which are discussed later in this paper.

The existence of a mean shoulder displacement during dual extensometer tests shows that, during a test with displacement controlled at the specimen shoulders and R = -1 at the shoulders, a mean strain would be caused within the gauge length of the specimen. This has the potential to affect the fatigue life of the specimen in two ways: a direct effect of the mean strain, or an effect of the associated mean stress. During the dual extensometer tests with gauge length strain control, a positive mean shoulder displacement was measured. Therefore, the use of a single correction factor based on amplitudes measured during dual extensometer tests would result in a negative (compressive) mean strain in the gauge length during autoclave testing using shoulder displacement control. The peak applied strains in the gauge length would also be lower than the intended peak tensile and compressive strains. As an example of the scale of potential errors in cyclic strain values, if a test were run at a nominal ±0.6 % strain at the shoulders, the actual strain in the gauge length would cycle between peaks of approximately +0.5 % and -0.7 %.

A negative mean strain, during a test in which zero mean strain is intended, results in a greater proportion of the strain cycle being associated with negative (compressive) strain. It is considered likely that the deleterious effect of the LWR coolant environmental on fatigue life (compared to life in air) is associated with a process of the surface oxide film at the crack tip rupturing under positive strain, followed by a period of localised corrosive attack on the underlying metal, with the extent of damage dependent on a balance between the corrosion rate and the rate of repassivation of the exposed metal surface at the crack tip. If a greater proportion of the strain cycle is negative (compressive), as will occur with a negative mean strain, there is potential for a lower degree of damage to the crack tip oxide and so a smaller enhancement of EAF cracking. Similarly, there is a potential impact on crack nucleation life (i.e. prior to crack growth) through a lower degree of damage to oxide films formed on the specimen surface.

In the absence of plasticity/ shakedown a negative mean strain in the gauge length would also result in a negative mean stress in the material and, hence, the material being under a tensile stress for a smaller proportion of the loading cycle. This has the potential to affect crack nucleation life due the effect on the cyclic stress experienced at the specimen surface prior to a crack forming. Once a crack exists, a compressive mean stress may also reduce fatigue crack growth rates in the specimen if it is assumed that growth of a fatigue crack occurs mainly during the tensile portion of a loading cycle, when a greater driving force for growth exists at the crack tip. For many cyclic loading conditions, the mean stress will rapidly shake down to zero (and a resultant R = -1 in terms of stress) within a small number of strain cycles at the start of a test due to plastic deformation. Previous work investigating mean strain suggests that, unless it results in a permanent mean stress, there is only a minimal effect on fatigue life9; however, the ability of the specimen to shake down to zero mean stress decreases with decreasing plastic strain and is therefore related to the applied strain amplitude. Hence, mean stress effects resulting from an applied mean strain are expected to be less important at higher strain amplitudes when effective shakedown occurs, but will be more significant as strain amplitude (and consequent extent of plastic deformation) decrease. These observations are normally associated with a positive (tensile) mean stress, but it is assumed that similar shake down will occur under a compressive mean stress. For EAF studies focussed on testing within the LCF regime (i.e. at higher strain amplitudes) this potential problem with shoulder extensometry is of less practical significance.

The trend of increasing importance of mean stress with decreasing strain amplitude is offset by results from the current work showing that, as strain amplitude is decreased and the potential for mean stress effects to be sustained increased, the mean shoulder displacements observed in dual extensometer test results also reduce. Therefore, the effects of mean stress are considered unlikely to be significant in this material. This perception of an insignificant effect of mean strain on fatigue life is supported by the EAF tests on the same materials as the current work reported recently by Platts et al.5, in which it was found that the specimens rapidly shook down into fully reversed stress cycles even when there existed a significant uncompensated mean shoulder displacement (e.g. for tests at a = 0.6 %).

For these reasons it is not considered that the potential presence of a mean stress needs to be explicitly addressed in testing of the current materials, but it is necessary to be aware of the effect and be able to make compensations for those materials or test conditions where shakedown does not occur rapidly after the onset of cyclic loading. The potential direct effects of mean strain on fatigue life in a LWR environment are less well understood and should be considered when selecting the appropriate correction to use for displacement control applied at the specimen shoulders.

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The effect of temperature may also be important when considering mean strain. In addition to the specimen geometry resulting in different rates of cyclic hardening and softening between the shoulders and gauge length, a temperature variation may exist between the shoulders and the gauge length when testing at elevated temperatures (especially in non-autoclave configurations) which would affect relative hardening/ softening behaviour and could contribute to mean strain. In the dual extensometer tests, this temperature variation may also have contributed to the scatter observed in the mean shoulder displacements measured at 300 °C, as shown in Figure 6.

The potential effect of strain rate should also be considered. The majority of dual extensometer tests were conducted at a strain rate of 0.1 % s-1, which is much faster than strain rates typically used in EAF testing in LWR environments, where the deleterious effect of environment on fatigue life of austenitic stainless steels is defined in NUREG/CR-69092 as being a function of strain rate, temperature and dissolved oxygen content of the coolant. Recent EAF testing at Amec Foster Wheeler has used strain rates of 0.01 % s-1 or lower. The rate of strain hardening, and hence the cyclic hardening and softening behaviour of austenitic stainless steels, is affected by strain rate. This suggests that strain rate will affect the relationship between strain in the specimen gauge length and specimen shoulder extension, raising the possibility of separate calibration curves being required for every strain rate tested. In the current work, the experiments conducted at εa = 0.45 % using strain rates of 0.1 % s-1 and 0.01% s-1 suggest a very small effect of strain rate on shoulder displacement amplitude (SDA) but a large effect on peak shoulder displacement in tension (SDT) and, consequently, on mean shoulder displacement (SDM). As these results suggest that the primary effect of strain rate is on mean strain, the significance of strain rate is likely to depend on whether mean strain is considered to be of concern. Further testing is required to confirm whether this initial observation of the effect of strain rate is found at other strain amplitudes, and whether it should be considered in shoulder displacement corrections.

An initial indication of possible heat-to-heat variability in the correction for shoulder displacement is provided by the two dual extensometer results for the AS216 and comparison of these with results for the MT643 material. When tested at 21 °C at a strain amplitude of 0.3 %, the AS216 material results shows a lower SDA and higher SDM than the equivalent test on MT643. When tested at 21 °C and a strain amplitude of 0.6 %, the SDA is similar to equivalent tests on MT643, but the SDM is higher. This apparent difference in behaviour at difference strain amplitudes may reflect the lower room temperature yield stress of AS216 relative to MT643, but could equally be an artefact of data scatter that is not represented by the very limited results available for AS216. Further work is necessary in order to understand whether separate heat specific calibration curves are required.

Use of dual extensometer tests to develop correction factors for strain control during fatigue tests in autoclaves using LWR water requires two key assumptions: That the relationship between strain (or displacement) at the specimen shoulders and strain in the specimen gauge section is not affected by test environment; and that this relationship is reversible.

The assumption of no effect of environment on the relationship is considered to be reasonable as the differences in strain between the two locations will be due to bulk material effects that are not expected to be affected by the environment, which is in contact with only the surface of the specimen.

The assumption that the strain relationship is reversible means that the ratio between cyclic strain controlled in the gauge length and the cyclic displacement measured at the specimen shoulders may be reversed, so that the relationship between the two locations is the same during testing when the displacement is controlled at the shoulders. This assumption is also considered to be reasonable once the cyclic hardening and softening of the material has reached a steady state. However, the use of a single correction factor for each test is likely to lead to a complex strain history within the gauge length during the initial cyclic hardening and softening stages, which may affect the level of work hardening experienced by the gauge length.

The use of a single correction factor throughout a test does not account for changes in relative rates of cyclic hardening and softening between material in the specimen shoulders and in the specimen gauge length over the duration of the test. Rather, it assumes a constant difference, approximated by values at Nf/2, throughout the test. The greatest difference in rates of hardening and softening between the two locations is seen at the start of the test. This is shown in Figure 5 in which, at the start of testing, the maximum and minimum shoulder displacements for each cycle are a measure of the difference in rates of initial hardening and subsequent softening between the two locations. The initial peaks in maximum and minimum shoulder displacements show that, during this initial cycling, the material in the specimen shoulders hardens more

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rapidly than the material in the gauge length. The use of a single correction factor throughout a test using displacement control at the specimen shoulders will therefore underestimate this difference in hardening in the early stages of the test, resulting in greater maximum strain being applied to the gauge length than the nominal value during the first few cycles and a higher level of gauge length hardening than would occur using gauge length strain control. This may subsequently lead to a redistribution of strain onto the less hardened material in the specimen shoulders, with the result of producing a reduced level of strain (and, most importantly, plastic strain) in the specimen gauge length. Experiments have been conducted using shoulder control in which adhesive strain gauges were applied to the specimen gauge length to monitor the development of gauge length strain under constant amplitude shoulder displacement control.10 Figure 9 shows the maximum measured strain during each cycle for a test with a nominal gauge length strain amplitude of 0.3 %. As can be seen, although the gauge length strain amplitude at half life is in good agreement with the nominal strain amplitude, the applied strain over the first 1000 cycles is significantly lower than the target value.

The effect of this on fatigue life is likely to be minimal at higher strain amplitudes where short and long crack growth dominate fatigue life, but increasingly important at lower strain amplitudes where crack nucleation life (rather than crack growth life) dominates overall fatigue endurance. This variation with strain amplitude is supported by the data of Platts et al.5 which show good agreement between lives of specimens tested in air using shoulder displacement control and with gauge length strain control at strain amplitudes of around 0.3 % and greater. The reduced levels of plastic strain anticipated in the gauge length are considered likely to affect crack nucleation, potentially leading to increased fatigue lives at lower strain amplitudes and apparent elevation of the fatigue limit. It is known that some workers who use shoulder extensometry apply cycle-by-cycle shoulder calibration throughout each test in order to maintain constant gauge length strain amplitude.11 Shoulder displacement data gained throughout each of the dual extensometer tests, such as that shown in Figure 5, would permit a similar correction to be applied in autoclave testing at Amec Foster Wheeler if this were considered to be beneficial.

Overall, there are many potential complications in developing and applying correction factors for control of cyclic displacement at specimen shoulders during EAF testing in an autoclave. Full investigation of the effects of variables such as temperature, strain rate and material type on correction factors would require considerable time, effort and cost. Similarly, development of complex correction factors or correction functions will be onerous and has the potential to significantly increase the cost and timescales associated with EAF testing. The use of a single correction factor per test, as presented in the correction curves developing during the current work, is considered to be a good solution to provide a reasonable approximation of cyclic strain conditions in the specimen gauge length through a practicable level of expenditure. Limited additional testing is planned to investigate the significance of some variables.

Figure 9: Strain amplitude in the gauge length of a specimen tested in air at εa = 0.3 % using shoulder displacement control with a single correction factor and adhesive strain gauges attached to the gauge length.

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CONCLUSION Most EAF endurance testing on solid specimens in autoclaves containing LWR water environments utilises shoulder displacement control through shoulder-mounted extensometry in lieu of direct strain control at the specimen gauge length. However there has been little discussion of the resulting errors in the actual cyclic strain experienced by material in the specimen gauge length compared to the nominal values. A correction method for cyclic displacement controlled at the specimen shoulders is presented based on experimental results, and the limitations inherent in different methods of correction are discussed.

From the results of dual extensometer experiments relating the shoulder displacement amplitude at half life to the applied gauge length strain amplitude, a curve of correction factors as a function of strain amplitude has been developed. This has been applied to fatigue endurance testing at Amec Foster Wheeler using a single correction factor throughout each test.

The use, for each test, of a single correction factor based on amplitude may not accurately represent the effects of temperature, strain rate and heat-to-heat variability on cyclic strain in the gauge length. Also, it does not account for mean strain (and associated mean stress), where a negative (compressive) mean strain is expected to occur during testing using displacement control at the specimen shoulders. Finally, examination of dual extensometer test data shows that the relationship between shoulder cyclic displacement and gauge length cyclic strain varies throughout a test, with a higher degree of variation at the start of testing; this is not accounted for by use of a single correction factor throughout each test.

Despite these concerns, it is considered that the use of a single correction factor per test, as presented in the correction curves developing during the current work, is considered to be a good solution to provide a reasonable approximation of cyclic strain conditions in the specimen gauge length through a practicable level of expenditure.

REFERENCES 1. ASME Boiler and Pressure Vessel Code, Section III, The American Society of Mechanical Engineers,

New York. 2. O.K. Chopra & G.L. Stevens, “Effect of LWR Coolant Environments on the Fatigue Life of Reactor

Materials”: U.S. Nuclear Regulatory Commission. NUREG/CR-6909, Revision 1 and ANL-12/60, March 2014.

3. ASTM E606/E606M, Standard Method for Strain Controlled Fatigue Testing. 4. BS 7270, Metallic materials – Constant amplitude strain controlled axial fatigue – Method of test, British

Standards Institution, December 2006. 5. N. Platts, D. Tice, J. Stairmand, K. Mottershead, W. Zhang, J. Meldrum and A. McLennan, “Effect of

Surface Condition on the Fatigue Life of Austenitic Stainless Steels in High Temperature Water Environments”: PVP2015-45029. July 2015

6. J A le Duff, A Lefrançois and J Ph. Vermot, “Effects of surface finish and loading conditions on the low cycle fatigue behaviour of austenitic stainless steel in LWR environment for various strain amplitude levels”, Proc. ASME 2009 Pressure Vessels and Piping Division Conference, PVP2009-78129, Prague, Czech Republic.

7. J. Solin, G. Nagel, W. Mayinger, “Cyclic behaviour and fatigue of stainless surge line material”, Proc. ASME Pressure Vessel and Piping Division Conference, PVP2009-78138, Prague, Czech Republic.

8. E.K. Puska and V. Soulanen. “The Finnish Research Programme on Nuclear Power Plant Safety” Final Report, Espoo 2011, VTT Tiedotteita – Research Notes 2571.

9. Fatemi, “Metal Fatigue in Engineering”: Wiley-Interscience, ISBN: 9780471510598. 2007. 10. J. Meldrum, D. Tice and J. Stairmand. “Effect of Surface Condition on Fatigue Endurance of Stainless

Steels in High Temperature Water”. Amec Foster Wheeler internal communication. December 2013. Ref: AMEC/CE/17038/R052 Issue 1.

11. Private communication between O.K. Chopra (Argonne National Laboratory) and D. Tice (Amec Foster Wheeler).

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OECD/NEA CSNI WGIAGE; Fourth International Conference on Fatigue of Nuclear Reactor Components

28th September-1st October, 2015, Seville, Spain

Consideration of the Mismatch between Environmental Fatigue Behaviourof Laboratory Specimens and Plant Components in Real Environment

Jussi SolinVTT, Espoo, Finland

Armin RothAREVA GmbH, Erlangen, Germany

Wolfgang MayingerE.ON Kernkraft GmbH, Hannover, Germany

SUMMARY

The assessment of environmentally assisted fatigue of metals in high-temperature water is currentlybased on material group specific design curves, codified procedures of fatigue analyses and parametricfactors (Fen) to account for environmental effects. Environmental factors depending on material, waterchemistry and operational data are measured using different kinds of laboratory specimens and oftenusing non-standard test methods, which are not used to determine the design curves. Furthermore, de-finition of Fen factors is not fully compatible with the codified fatigue assessment rules. The designfactor for elevated temperature is ignored. It seems to be generally acknowledged that there is a mis-match between the environmental fatigue lives of laboratory specimens and plant components undernominally similar conditions. In other words, transferability of the laboratory data is obviously notsufficient. However, a closer look to the detailed local mechanical, environmental and thermal loadingconditions often reveals obvious differences between laboratory tests and real operational loading.Consequently, we consider it necessary that experts from all relevant disciplines of concern, i.e. plantdesign, operation and research cooperate in order to derive and establish appropriate and compre-hensive approaches to address the issue properly. We have developed experimental methods aiming toimprove the state of the art in transferability of data. This paper presents and discusses advancedexperimental approaches and results using such improved methods. Explanations for apparentlydifferent fatigue behaviour in laboratories and in the field are discussed from the viewpoints of plantvendors, utilities and research laboratories. Moreover, the paper provides ideas of general approachesfor the improvement of laboratory testing conditions in order to closer simulate the true operationalloading conditions. Results from such tests can then serve as more reliable data for the prediction ofcomponent lives. Component relevant testing conditions are much more complex and time consumingthan any conventional fatigue test before. A coordinated cooperative approach worldwide is suggestedas an affordable way to create the necessary quantity of high quality laboratory test data which canserve for the reliable derivation of more realistic predictions of component lives under real operationaland environmental conditions. A reduction of environmental fatigue penalty factors withoutcompromising safety is anticipated and suggested as motivation for this effort.

Keywords: Fatigue, Environmentally Assisted Fatigue, EAF, Laboratory Tests, Operational Experience, ComponentRelevance, Benefits, Hold Time, Complex Loadings

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1. Introduction

The issue of environmental effects on fatigue is challenging the international community of plantdesigners, vendors and operators, in particular mechanical engineers and material engineers alreadyfor several decades since the 1970’s. Many interesting or even scaring observations have been made inlaboratory tests to study crack initiation or crack growth due to environmentally assisted fatigue. Manydifferently sounding names were given to this effect, e.g. corrosion fatigue, strain induced corrosioncracking or environmentally assisted cracking (EAC). The latest commonly used terminology for thismode of EAC is environmentally assisted fatigue (EAF). In contrast to stress corrosion cracking,which occurs in static or monotonic loading, environmentally assisted fatigue has never systematicallycaused serious degradation or failure of components in nuclear power plants worldwide.

Although numerous cases of degradation of components due to EAF during service were reportedin the literature, almost all of them can be attributed to significant deviations from nominal, specifiedconditions regarding material, design, fabrication and/or operation. This has been mutually agreed inthe nuclear community at the three international conferences on Fatigue of Nuclear ReactorComponents, which took place more than ten years ago.

1.1 EAF related operational experience discussed in previous conferences

The operational experience on fatigue and EAF was summarized at the preceding InternationalConferences on Fatigue of Nuclear Reactor Components, that took place in 2000, 2002 and 2004 [1],[2], [3].

Selected example statements are reminded herafter.In the summary of the 1st Conference [1]:“… Significant advancements have been made in the international communityregarding the effects of thermal fatigue and reactor water environment.Additional research and international collaboration are recommended in theseareas in order to resolve technical issues and utilize the results of these efforts invarious operating plant criteria. …”

In the summary of the 2nd Conference [2]:“… 9. Further reconciliation between operating experience and laboratory/component / structural data is recommended. …”

At this conference [2] also by Nickell & Rosinski:“… Plant operating experience has not shown significant increases in fatiguefailures ascribed to reactor water environmental effects as a function ofincreasing length of service of nuclear power plant components. …”

In the summary of the 3rd Conference [3]:“… 3. There were still discussions within the community on the consideration ofenvironmental factors. In particular, they should be compared with operatingexperience. …”

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1.2 EAF introduced into the ASME Boiler & Pressure Vessel Code

An article introducing the environmental effects in ASME Boiler & Pressure Vessel Code stated:“Laboratory tests have shown that LWR can have a detrimental effect on both S-N fatigue propertiesand fatigue crack growth ... To date, there has been no documented instance of a fatigue failure in anoperating LWR plant where the primary cause of the failure could be ascribed to a reduction in S-Nfatigue life due to LWR coolant environmental effects. However, since laboratory tests do show that areduction in S-N life can occur under certain conditions, it is prudent to consider environmental effectsin design.” [4].

Since then, no additional cases of EAF have been reported from nuclear power plants worldwide.This is considered as an indication of limited burden for currently operating plants.

1.3 Basis of operating plant designs: “DESIGN BY ANALYSIS”

The development of the ASME code was primarily aimed to prevent catastrophic fractures ofpressure vessels. Therefore, the fatigue assessment was focusing on severe but rare thermal transientsthat can cause notable low cycle fatigue damage in heavy equipment. The committee pointed out thatthe code was developed for pressure equipment, for which “the number of cycles seldom exceeds10 000” [5].

For fatigue design according to ASME III [7], the allowable loading is given in form of designcurves, which are based on strain controlled low cycle fatigue tests in room temperature. Similarcurves are applied also in other design codes, e.g., the German KTA and French RCC-M.

Figure 1 shows the rationale for adopting a version of local strain approach for ASME III design.Similar shape of fatigue curves makes strain controlled data better transferable to components thanstress controlled data. Fatigue endurance depends on the local strain and material at a stressconcentration experiences strain control also when the component is loaded under load control.

Figure 1:Transferability of strain or stress controlled data

to component behaviour in low cycle fatigue regime [5].

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For the ASME code design curves the vertical axis units are translated to quasi-elastic stressunits. A temperature dependent elastic modulus is applied to total strain (including also plastic strain).This yields to very high values of stress intensity amplitudes allowable for short lives. In laboratorytest measured stress amplitudes are not comparable to the design curve. For stainless steels, whichexperience nonlinear strain even at endurance limit, this is true also in high cycle regime. All data usedfor design of stainless steels shall be strain based.

The “design by analysis” philosophy for ASME Code Section III assumed that the designerknows the relevant material performance. To reduce need for material testing, a set of generalizeddesign curves for the basic material types were included in the code. However, applicability of theselected design curve for the particular application remains responsibility of the designer.

The code itself does not give quantitative factors for adopting the influence of reactor coolant orother plant specific conditions to fatigue calculation. Moderate environmental effects were accountedfor in the design curve definition (that time margin of 20 in life), but the responsibility of consideringeventual more significant environmental effects was left to the designer. This was stated in the CriteriaDocument for the ASME III Design by analysis procedure as follows: “protection againstenvironmental conditions such as corrosion and radiation effects are the responsibility of thedesigner” [5].

Detailed justifications for the design curve margins were not formally published, but a generallyreferred heritage says that they were based on three sub factors:

2.0 for scatter of data,2.5 for size effect, and4.0 for surface finish and environment.

It shall be noted that the design temperature was not accounted for the design curve margins.There are probably two main reasons for this. Firstly, the ASME III design rules were mainly targetingto relatively short lives, where effect of temperature is moderate in terms of fatigue life, thoughhardness and elastic modulus of materials is affected. A general tendency is that high strength steelshave lower S-N curve slopes, while soft materials have steeper slopes. In other words, change inmaterial strength does not shift the curve, but often turns it around a rotation point, see Figure 2. Thisrotation point also happens to be very convenient and popular for laboratory testing and the effects oftemperature have not been separately much addressed. As an exception, the German KTA standardintroduced in 2013 [19] two separate design curves for RT and elevated temperatures.

However, the design rules still assumes that an increase of design temperature reduces theallowed number of cycles. The ASME III design curve is defined for the room temperature, but thedesign temperature is accounted for by multiplying the stress intensity value by a ratio of elasticmodulus in room and design temperatures:

Sa,design = ERT / ET,design Sa (Equation 1)

The ratio of elastic moduli does not affect elastic strain only. Also plastic strain is multiplied,when assessing fatigue in elevated temperatures. This should be kept in mind, when discussing oneffects of temperature and environment.

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Figure 2:Strain life curves for a medium carbon steel in a quenched and tempered and normalised

condition to illustrate the general trend in slopes for hard and soft materials [6].

1.4 Evolution towards consideration of EAF

Figure 3 recalls some stages along the evolution process towards global consensus onconsideration of environmental effects in fatigue assessment. Hopefully we are moving in direction ofconsensus, but a long road is still ahead. The goal is not reached yet.

The sub factors for the design curve margins became subjects of much discussion, in particularwhen laboratory data published in Japan and USA pointed out a need to properly address the effects ofcoolant water. Accounting for the “moderate environmental effects” (Z 4) to reduce the proposedincrease in fatigue usage factors was much debated.

Environmental factors (Fen) had been proposed and discussed well before we gathered previoustime for this series of conferences, but publications of the NUREG/CR 6909 report and US NRCRegulatory Guide 1.207 in 2007 were landmarks in this evolution. In addition to the equations forcalculation of Fen values, Chopra et al. proposed and the NRC endorsed also a new air curve forstainless steels as part of this Regulatory Guide “for new designs in USA only” [21], [23]. In practicethe regulatory guide made it mandatory to consider environmental penalty factors for licence renewalsin US and since 2007, it has been difficult to find a paper on EAF without a reference to theNUREG/CR 6909 report.

Popularity of the report is mainly due to the new reference curves, which were based on a widemix of new experimental data. However, the original data for stainless steels – on which design ofmany operating plants is based on – and any data for stabilized stainless grades, which are used inprimary piping of many operating plants, is missing. Obviously, the NRC had good reasons to limitapplicability of the Regulatory Guide to new designs only. However, the new fatigue design curve forstainless steels was adopted as such into a “Mandatory appendix” of ASME III in 2009 [7].

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The Japan Society of Mechanical Engineers, JSME published already in 2006 a method forenvironmental fatigue evaluation for nuclear power plants and an update in 2009 [22]. The JSMECode and NUREG/CR 6909 report are based on shared data bases and quite similar, but the numericalFen values differ a little.

Since the Conference in Seville, 2004, the research has been continued, also in Europe. Eventualupdates for the French code RCC-M are considered and the German code KTA was revised in 2013, toinclude design curves for stabilized stainless steels and elevated temperatures [19]. The approaches forenvironmental fatigue will be separately discussed below.

Figure 3:Evolution of approaches for EAF.

2. Examples of Operational Experience

As a reminder, some of the relevant European cases are briefly mentioned here:

A) Circumferential cracking at a BWR feedwater nozzle-to-pipe weld with piping made fromGerman type WB35 low-alloy high-strength structural steel [8]. This cracking was attributed to straininduced corrosion cracking (SICC), which is another name for environmentally assisted low-cyclefatigue (LCF) at very low frequencies. The identified root causes were

a. Materiali. local stress increase due to significant mismatch in wall-thickness between the RPV nozzle

and the pipeii. low-damage tolerance of thin-walled pipe

b. Environmenti. high-temperature water containing dissolved oxygen

c. Stressi. Additional thermal stress due to thermal stratification caused by cold and hot water, which

was not considered in the design base of this component.ii. unknown local residual weld stress

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After significant improvements and modifications for all important parameter areas material-environment-stress (change of the material to a medium strength low-alloy steel, reconciliation of thewall thickness, post-weld stress relief annealing, limitation of the level of dissolved oxygen to 30 ppbin the feedwater), no further cases of cracking occurred.

B) Circumferential cracking due to SICC resembling environmentally assisted LCF at PWRsteam generator feedwater-to-nozzle welds fabricated from LAS and appropriate weld filler metal [8],[9]. This case is somewhat similar to case A) and was also attributed to SICC (EAF at low frequency)at low-alloy steel which was caused by varying local plastic deformation in high temperaturefeedwater due to a moving phase boundary between hot and cold water during thermal stratification.Although PWR secondary circuit feedwater is low in dissolved oxygen, it was anticipated that oxygenwas temporarily elevated during operation.

C) The very local occurrence of minor surface flaws, which appear partly as pits, partly as smallcracks, which were discovered by NDE at a PWR steam generator feedwater nozzle (LAS) apart fromany weld in the context of the ISI programme, was attributed to the onset of EAF [10]. The flaws werelocated in the area of highest fatigue load. Although the calculated usage factor was well below 0.5,environmental effects might have accelerated crack initiation in this case. Moreover, it should be notedthat the maximum crack depth determined by metallographic means was only approx. 2 mm had anextension of approx. 280 mm in circumferential direction. This is still in the range of crack initiationand thus far from the failure of the component. The damage analyses showed mainly pitting corrosion due to idle time, partly SICC; no activecrack tip (stable oxide layer on surface of pits) was observed. Reason for the indication was

stratified flow with thermal load transients T = 265 K mainly duringcommissioning and

insufficient conservation measures during long outages (> 2 month).

After refurbishment of this segment of the feedwater nozzle, the operational parameter to reduce thethermal loads T (preheating of feedwater) and conservation measures (wet conservation) duringoutages longer than 2 weeks were optimized.

D) The case of thermal fatigue in a mixing tee junction fabricated from austenitic stainless steelwhere a through-wall crack was found on an elbow in mixing area of high and low temperature fluids([11], [12]) in CIVEAUX nuclear power plant. The reason was a through-wall crack (TWC) in anelbow of the residual heat removal system. It was located at the longitudinal weld root on the extrados.Based on metallographic examinations and the analytical damage evaluation, the major root cause forcracking was attributed to high cycle thermal fatigue and not of fabrication faults. The cracks werefound in the tee and at the root of welds in mixing areas. Checking of further loads showed that thermal loads could be attributed to the relevantdegradation mechanism. In the commissioning phase a high number of thermal loads with high T-cycles had been applied because the bypass branch parallel to the residual heat exchanger was usedmany times. During normal operation of the plant the bypass will be closed. The bypass is only open in failuremodes with blocked or leaking residual heat exchanger. Those load cycles are not specified andtherefore had not been taken into account during design.

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3. EAF and how it is currently addressed in selected codes

3.1. ASME B&PV Code, Section III

Moderate environmental effects were accounted for in the definition of the design curves for theASME B&PV Code, Section III, but responsibility on applicability of the design curve was left for thedesigner. In 1999 the non-mandatory article W-2700 introduced the environmental effects in ASMEBoiler & Pressure Vessel Code addressing the need to consider environmental effects in design.However consensus on the methodology has not been easy to reach.

The research in Argonne National Laboratory resulted to statistical models for estimating thefatigue lives in air and LWR environments [13]. Such environment and strain rate dependant designcurves (Figure 4) were provided in 2010 by the Code Case ASME N-761 "Fatigue Design Curves forLight Water Reactor (LWR) Environments" [14].

An alternative approach for presenting the environmental effects in terms of an environmentalfatigue correction factor Fen was proposed by Higuchi and Iida [15] and Mehta used the ANLstatistical models for calculating Fen in an approach known as the EPRI/GE methodology [16], [17].Later on the Argonne final report NUREG/CR-6909 became a central reference. The environmentalfatigue correction factor Fen approach was introduced in 2010 into ASME III by the Code Case ASMEN-792 "Fatigue Evaluation Including Environmental Effects” [14].

For readers not familiar with the methodologies for Fen calculation, it is recommended to findintroduction in any recent conference in this area, e.g. Chopra & Shack (presented by Cullen) insession 3 of the 2004 conference in Seville. The main references are NUREG/CR-6909 [21] and JSMES NF1 – 2009 [22].

Figure 4:Environmental fatigue design curves for stainless steels

as proposed for the code case ASME N-761 [14].

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3.2 KTA

EAF is taken into account in the German KTA framework in KTA No. 3201.2 for primary circuitcomponents [19] and in KTA No. 3211.2 for secondary side piping components [20]. Within therevision phase of these regulatory guidelines in 2013 the national and international state-of-the-art wasdiscussed and analysed intensively. The basis for this discussion was [21] and [23]. For primary circuit components an evaluation of EAF relevant loading cycles has beenperformed. In terms of these relevant locations, temperature measurements of PWR and BWR plantshave been evaluated identifying relevant transient temperature loadings (thermal shock andstratification). Additionally, system specifications of transient temperature loadings (design transients)were evaluated. A typical specified transient is shown for example in Figure 5. Based on these relevant sets of loadings EAF correction factors were calculated according to [21].Beyond that, for austenitic stainless steels an additional safety margin was included for cases when olddesign fatigue curves are applied. The result was the introduction of so called threshold of attentionvalues for the CUF as described in previous sections. Alternatively, these thresholds of attentionvalues can be interpreted as immanent margins of the applicable design fatigue curves with regard toEAF. This philosophy is close to the approach chosen for the French EAF methodology as describedin [24].

Figure 5:Typical specified temperature design transient for PWR spray lines.

According to KTA 3201.2 if environmental effects cannot be excluded, actions shall be taken atthe time when the cumulative usage factor reaches the fixed threshold value of CUF = 0.4. Foroperation beyond these threshold values, one of the following measures shall be taken:

Integration of the relevant parts/areas into the inspection/monitoring program (in-serviceinspections and operational monitoring, compilation of the occurring operational thermaltransients as well as NDT measures) according to KTA 3201.4 [26] or

Performance of service relevant laboratory tests or

Fatigue analyses considering environmental reduction factors (Fen) and realistic boundaryconditions.

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10

The last mentioned point may lead to the detailed consideration of environmental factors Fen e.g.according to NUREG/CR-6909 (e.g. [21] or [28]), the ASME Code Cases (e.g. [31]) or alternativemethods such as the method described in [24] and foreseen for implementation in the RCC-M Code.The consideration of EAF by definition of threshold of attention values for the Cumulative UsageFactor (CUF) is a specific approach in the German KTA rules and is the result of an engineeringconsideration.

3.3 RCC-M

The concept of this new approach is described in detail by Courtin et al. [25]. It is based on thefact that in the ASME boiler & pressure vessel code, Section III, the design curve is derived from themean data air curve by the application of 4 factors, which should consider the variations of

material variability (a)size effect (b)surface finish effect (c)environmental effect (atmosphere) (d)

during the transition from laboratory data to plant components. Fixed factors for each effect werechosen and the product of all of them was 20. The idea of the new alternative concept is to removeuncertainty in individual factors as much as possible by the application of lab tests which to someextend represent the real situation on a loaded component. This applies to surface finish andenvironmental effect (factors “c” and “d”), however cannot be used for factors “a” and “b”.

This idea was realized by the application of controlled surface conditions (ground vs polished)and testing in relevant hydrogenated high-temperature water environment with PWR primary sideconditions.

For a dedicated test and at a given strain amplitude in the design curve, the specifically defined“allowable environmental factor” Fen, allowable can be calculated based on the test result Ntest fromthis dedicated test, which is related to the product of c x d, which fully covers surface finish andenvironmental effect. Therefore, these two factors (c and d) do not need to be considered anymore inthe further treatment. The comparison with the associated environmental factor Fen calculatedaccording to Appendix A of NUREG/CR-6909 [21] then delivers Fen, allowable based on thefollowing equation [25] (see also Figure 6):

Where:Fen test is the level of environmental effects introduced in the test according to Eq. (2), i.e.according to [21]Ntest is the experimental fatigue life relating to the test (number of cycles at 25% maximumload drop)Ndesign is the number of cycles predicted by the design curvea and b, respectively, are the margins relating to material variability and size effect, taken fromChopra et al. [21]

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11

a) case where Fen test is covered by the designcurve

b) case where Fen test is not covered by thedesign curve

Figure 6:Reserve factors between the best fit mean air curve and the design curve [25].

4. Residual Concerns & Approach for Related Improvements

4.1 Potential Explanations for the non-coincidence of Operational Experience and Lab-Data

The obvious non-coincidence between laboratory experience (test results) and operationalexperience of plant components can be easily explained by the significant features that apply here for:

Plant componentso Conservative stress/strain analyses are used for the design of components.o Conservative assumptions are made for the number and/or frequency of loads/transients.o Critical areas are mostly loaded with thermal loads (delta T) which are characterized by

complex load shapesindividual transients (modelled for analysis) – not cyclic repeats of the same shapelong periods (days or weeks) of steady state load („hold times“)

Laboratory testso do not always consider the real loading of components,o e.g. thermal load at components vs. mechanical load at lab specimenso mechanical and environmental loads are simultaneously applied here

Permanent artificial signals for mechanical loading (triangular or sinusoidal) – noconsideration of hold-times.

The consideration of these differences in specifically designed laboratory tests has already shownto provide beneficial effects on environmental factors Fen when they are derived from experimentswith complex loadings or with applied hold-times. However the database is still poor and thebeneficial effects may not exist at every level of strain.

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4.2 Challenges and achievements in laboratory testing

Strain controlled mechanical tests are crucial in order to directly compare EAF results with thereference curve. However strain control is not easy arranged in autoclaves used for tests in high-temperature water environment. The controlled parameter is normally connected as a feedback signalfor the fatigue test rig controller, compared to the instantaneously desired value and the difference isamplified for corrective command. Any error or excessive noise in the feedback signal during the longduration of test can easily destroy the specimen or even the whole system. As instruments for reliablemeasurement of strain at the smooth gauge length of the specimen are not commercially available,strain can hardly be used as controlling parameter for servo hydraulic test machines. AREVA GmbHand VTT have solved the challenge of generating design code compatible data in hot water in slightlydifferent ways.

AREVA GmbH is using kind of remote strain control strategy, where two independentmeasurements are performed. Displacement measurement by LVDT at the specimen shoulder can beused as a controlling parameter for the test machine, but it does not accurately reflect the real strain atthe specimen gauge length. A real strain measurement by a strain-gauge based measuring device isperformed at the gauge length of the specimen. These parallel measurements can be calibrated in away that the desired strain cycles are realised at the gauge length of the specimen, though theinstantaneous feedback signal for test control is received from the strain measurement at the shoulderof the specimen.

VTT has developed a special device for fatigue testing in simulated LWR coolant environments.It is powered by servo-controlled pneumatic bellows. The experimental techniques for straincontrolled testing are described in a parallel paper by Seppänen et al. [29].

Figure 7:Double device measurement for remote control of strain in hot water tests:

LVDT for displacement with an in-house designed measuring device for real strain(Courtesy of AREVA GmbH).

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4.3 Internationally used testing methods

Several laboratories, Argonne National Laboratory being one of the best known of them, havesolved the problem of strain measurement by building a small autoclave round the specimen andcalibrating the strain with displacement measurements outside of autoclave. A reasonable accuracymay be achieved through careful calibration for cyclically stabile materials, which do not harden orsoften too much. But accurate strain calibration becomes extremely complex or impossible forstainless steels, which harden and soften notably during different phases of test.

One compromise engineering approach is to perform displacement controlled tests using LVDTtransducers inside the water autoclave attached to specimen shoulders at close distance to gaugesection. This arrangement is also subject to non-constant calibration of strain during a test for stainlesssteels, but the calibration drifts are smaller than is the previous approach. For example AREVA SASin France has used this kind of test arrangement for developing the above discussed Fen allowable concept.

Japanese laboratories developed a test method, where the hot pressurised water is circulatedinside a thin walled tubular specimen. The axial strain in this specimen can be measured in airenvironment outside of the specimen. Tubular specimens are suitable for detecting and comparingeffects of various test parameters, even for studying the effect of coolant flow rate. However, the testgeometry, specimen dimensions and failure criterion differ from the standard LCF tests and directcomparison to standard reference data becomes questionable. Tubular specimen tests can beconsidered as miniature component testing.

4.4 Example data in PWR water and interpretation of results for the designer

An example of recent laboratory data [30] is introduced and discussed in the following. Figure 8shows the raw data as numbers of cycles until 25% peak load drop for tests performed by VTT insimulated PWR coolant water in 325°C and 200°C. For comparison, the mean data curves for thesame material batch at 25, 200 and 325°C are shown together with a mean curve covering the wholetemperature range for non-stabilized stainless grades. The experimental data is for niobium stabilizedalloy 347 steel taken from a pipe manufactured and inspected for use in NPP primary piping.

The dotted lines represent predictions according to the mean curve and Fen calculation given inthe NUREG/CR-6909 report and horizontal piles illustrate the differences in prediction and result. Onedata point equals with the prediction and all other exceeded the predicted lives. The difference waslargest for the slowest strain rates.

The laboratory data in Figure 8 is comparable to the air data and predictions. However,comparison of this raw data with the design curve would be a little misleading, because the designcurve is to be applied with design values shifted with a factor according to equation 1. In this case, thecomparison would be overly conservative by a factor of about 1.5 for the 325°C data.

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Figure 8:Laboratory data in simulated PWR coolant water [30]

The data in Figure 8 is plotted as predicted and experimentally measured life reductions (Fen) incomparison to the air reference curve [21] in Figure 9. As seen in Figure 8, the elevated temperaturereduces the fatigue life obtained at low strain amplitudes also in air. Extracting the in air obtainedexperimental temperature effects out of (Fen) gives values for the effect of water environment (Fen,water),Figure 9 (a).

As noted above, direct comparison of the laboratory data and design curve would be misleading.A bias or unintended penalty factors arise, if the experimental reduction factors (Fen,experiment) werereported to a designer, who performs fatigue assessment for components operated in designtemperatures of 200°C or 325°C. This could be avoided without change of the design procedure ordefinition of environmental factors (Fen), if the laboratory data were reversely modified “fortransferability” before reporting to the designer. This would naturally be an abnormal – thoughcorrective – operation and in minimum require proper documentation. Such modification is illustratedin Figure 9 (b) and the result can be seen in comparison of Figure 9 (a) and (b). The consequences ofmodification depend on temperature and slope of the S-N-curve. It has a maximum impact on data inhigh temperature and low strain amplitude. The temperature effect (Fen,T) embedded in (Fen) is alsoshown in Figure 9 (b).

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15

(a) (b)

Figure 9:Comparison of experimental data with predicted environmental life reduction factors as raw

data (a) and as modified for compatibility with ASME III design calculation (b).

4.5 Retardation of crack growth in LWR water due to long hold times at static load

In order to study long-term hold-times without causing unacceptable test durations, a specialtesting sequence was developed. In phase 1 of the experiment, fatigue-pre-cracked 1T-CT-specimensof the materials of concern were fatigued in the selected environment by application of a continuous,cyclic, asymmetric saw-tooth loading signal until a crack advance of approx. 1 mm was achieved(Figure 10 (a)). The alternate direct current potential drop technique was used to determine cracklength. The numbers of cycles necessary to achieve this crack advance were determined and served asa baseline for the modification of the test sequence in the subsequent phases 2 and 3 of the experiment.In phase 2 of the experiment, the same loading signal was applied. However, the loading wasinterrupted after reaching 20 % of the baseline number of cycles from phase 1. The specimen loadingwas then continued with constant load at KI, max of the saw-tooth loading. The load was maintainedconstant for 3 days (72 h). Thereafter, cycling was continued under the initial conditions for another20 % cycles of the baseline value. The sequence of cyclic loading and constant loading was repeated 5times. In a third phase, a similar sequence was applied as in phase 2, however with 30 days (720 h) ofhold-time at constant load at KI, max of the saw-tooth loading. The applied sequence of saw-toothloading including hold-times is schematically shown in Figure 10 (b).Fatigue-pre-cracked 1T-CT-specimens were fabricated from a German RPV steel 22 NiMoCr 3 7(equivalent to ASME SA 508 Grade 2 Cl. 1, formerly SA 508 Class 2) and a Nb-stabilized austeniticCrNi-stainless steel (German mat.-no. 1.4550 (AISI 347 SS)). The tests were performed in autoclaveswhich were attached to a once-trough high-temperature water refreshing loop. The refreshing rate wasapprox. 2 times/hour to maintain controlled chemical conditions. The resulting flow rate was quasistagnant. The environment was pure oxygenated high-temperature water (240 °C, DOinlet = 400 ppb,

inlet < 0.1 µS/cm). The test conditions, in particular the lower temperature were chosen because thereare other published data under similar conditions which could be used for comparison.The applied mechanical loading was an asymmetric saw-tooth signal (100 s rise time, 20 s fall time,KI, max = 35 MPa m, R = 0.7). Test phases with pure saw-tooth loading and interrupted saw-toothloading with hold-times of 3 days and 30 days were used.

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The measured crack growth rates are compared to the rate which was measured without holds. Theresults are plotted in Figure 11. There is only small trend for decreasing crack growth rates at 72 hours(3 days) of hold time for low-alloy steel (Figure 11 (a)) and austenitic stainless steel (Figure 11 (b)).However, there is a significant reduction of the crack growth rate after 720 hours (30 days), inparticular for the austenitic stainless steel (Figure 11).

a) Pure saw-tooth loading without hold-times b) Saw-tooth loading interrupted with hold-timesat maximum load

Figure 10:Schematic of mechanical loading pattern with and without hold-times.

a) Low-alloy steel b) Austenitic stainless steel

Figure 11:Crack growth rates measured in LWR water with and without holds between cycle blocks

10

20

30

40

-1000 1000 3000 5000 7000 9000 11000 13000 15000Time (t)

Load

(or

K) t R t F

10

20

30

40

0 5000 10000 15000Time (t)

Load

(or

K)

t hold

1 10 100

K (MPa m1/2)

da/d

N(m

m/C

ycle

)

22NiMoCr3-7

ASME B&PVCSect. XI (Air)

ASME B&PVC Sect. XI(Light Water ReactorCondition)R > 0.65

R < 0.25

R > 0.9

10-2

10-3

10-4

10-5

T = 240 °C < 0.1 µS/cm

DO = 400 ppb

10-1

Phase 2thold = 72 h

Phase 3thold = 720 h

/ R = 0.7

Phase 1

1 10 100

K (MPa m1/2)

da/d

N(m

m/C

ycle

)

1.4550

ASME B&PVC Sect. XI (Air)

R = 0.7

R = 0.9

10-3

10-4

10-5

10-6

T = 240 °C < 0.1 µS/cm (at inlet)

DO = 400 ppb (at inlet)

10-2

Phase 2thold = 72 h

Phase 3thold = 720 h

/ R = 0.7

Phase 1

R = 0

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5. Conclusions & Outlook into the future

A burden for accounting the environmental effects in fatigue assessment of NPP primary pipingwas created by results of laboratory testing programmes. A corresponding need for improved EAFrules has not been aroused from operational experiences.

New European data for non-stabilised and stabilised stainless steels tends to give lowerenvironmental correction factors than would be expected based on the currently used Fen approaches.

There may be several reasons for this, but several main suspected reasons are:Part or testing is performed for stainless steel grades not considered in data bases behind thecurrent Fen approaches. Different alloys have different cyclic performances and they mayexperience also different environmental effects.It is obvious that the mode of control can affect the obtained endurance, which is defined bypeak load drop. The softening phase often occupies most of the experiment duration. If thesoftening is inadequately identified and compensated during displacement controlled tests, thiswill result to endurances shorter than the strain controlled standard methods. Naturally,overcompensation would lead to non-conservative results.Ideas and real results on component relevance of data (hold-time effects, complex loadings,etc.) need to be extended to consider the whole range of parameters which determine thefatigue life of components.

A worldwide, cooperative and collaborative effort will be necessary to address the recentlyidentified gaps in the database for component relevant data.

REFERENCES

[1] Proceedings of the 2000 International Conference on Fatigue of Reactor Components, Napa Valley, CA, July 31 –August 2, 2000, organized by EPRI, Palo Alto, CA, OECD/NEA/CSNI and the U.S. NRC, (PWR Materials ReliabilityProgram, PWRMRP-46), 2001. 1006070.

[2] Second International Conference on Fatigue of Reactor Components, Snowbird Ski and Summer Resort, Snowbird,Utah, 29-31 July, 2002. (EPRI Materials Reliability Program, MRP-84).

[3] Third International Conference on Fatigue of Reactor Components,Seville, Spain, October 3-6, 2004, sponsored by EPRI, NRC and OECD/NEA/CSNI, hosted by Consejo de SeguridadNuclear (CSN); (MRP-151, EPRI, Palo Alto, CA, 2005, 1011958).

[4] ASME Boiler & Pressure Vessel Code, Non-mandatory article W-2700, 1999.[5] Criteria of the ASME Boiler and Pressure Vessel Code for design by analysis in sections III and VIII division 2.

Pressure Vessels and Piping: Design and Analysis, A Decade of Progress, Vol. 1 ASME 1972, p. 61-83.[6] Bannantine, J.A., Comer, J.J., Handrock, J.L., 1990:

Fundamentals of metal fatigue analysis. Prentice Hall, ISBN 0-13-340191-X. 273 pages.[7] ASME Code, Sections III and VIII, Divisions 1, 2 and 3. American Society of Mechanical Engineers, New York. &

Addendum 2009b: Section III Division 1, Mandatory Appendix 1 Design Fatigue Curves.[8] Kussmaul, K., Blind, D., Jansky, J.:

Formation and Growth of Cracking in Feedwater Pipes and RPV Nozzles;Nuclear Engineering and Design 81 (1984) 105-119.

[9] Hickling, J., Blind, D.:Strain-induced Corrosion Cracking of Low-alloy Steels in LWR Systems – Case Histories and Identification ofConditions Leading to Susceptibility;Nuclear Engineering and Design 91 (1986) 305-330.

[10] Kohlpaintner, W.; Neumann, J.; Nowak, E.; Schmidbauer, J.; Voskamp, R.; Wachter, O.; Wesseling, U:Befunde an den Speisewasserstutzen von Dampferzeugern des Kernkraftwerkes Unterweser - Detektierung,Ursachenklärung, Sanierung, Abhilfemaßnahmen;29. MPA Seminar, 2003.

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[11] Cipière, M.-F., Goltrant, O.:Circuit RRA N4 – Incident de Civaux 1 endommagement par fatigue thermique de tuyauteries situées dans de zone demelange;Fontevraud 5, 2002.

[12] Horst Rothenhöfer:Fatigue Caused by Temperature Changes in Mixing Tees;36. MPA Seminar 2010.

[13] Majumdar, S., Chopra, O.K., Shack, W.J.:Interim fatigue design curves for carbon, low-alloy, and austenitic stainless steels in LWR environments, NUREG/CR-5999 (ANL-93/3) for U.S. Nuclear Regulatory Commission, Washington DC, 1993. 48 p.

[14] Code Case ASME N-761 "Fatigue Design Curves for Light Water Reactor (LWR) Environments Section III,Division 1", 2010.

[15] Higuchi, M., Iida, K.:Fatigue strength correction factors for carbon and low-alloy steels in Oxygen-containing high-temperature water, Nucl.Eng. Des. 129, 1991, pp. 293-306.

[16] Mehta, H., Gosselin, S.R.:An environmental factor approach to account for reactor water effects in light water reactor pressure vessel and pipingfatigue evaluations. Fatigue and Fracture - 1996-Vol. 1, PVP-vol 323, ASME, 1996, pp. 171-185.

[17] Mehta, H.:Update on the EPRI/GE environmental fatigue evaluation methodology and its applications. Probabilistic andEnvironmental Aspects of Fracture and Fatigue - 1999, PVP-Vol 386, ASME, 1999, pp. 183-193.

[18] M. Dahlberg et al.:Development of a European Procedure for Assessment of High Cycle Thermal Fatigue in Light Water Reactors;Final Report of the NESC-Thermal Fatigue Project; NESC 2007.

[19] KTA Program of Standards, Standard No. 3201.2:Components of the Reactor Coolant Pressure Boundary of Light Water Reactors, Part 2: Design and Analysis, issue2013-11.

[20] KTA Program of Standards, Standard No. 3211.2:Pressure and Activity Retaining Components of Systems Outside the Primary Circuit; Part 2: Design and Analysis 2013-11.

[21] Chopra, O. K., Shack, W. J.:Effect of LWR Coolant Environments on the Fatigue Life of Reactor Materials,NUREG/CR-6909, ANL-06/08, February 2007.

[22] Code for Nuclear Power Generation Facilities, Environmental Fatigue Evaluation Method for Nuclear Power Plants(JSME S NF1-2009), Japan Society of Mechanical Engineers (2009)

[23] U.S. Nuclear Regulatory Commission Regulatory Guide 1.207, 2007:“Guidelines for evaluating fatigue analyses incorporating the life reduction of metal components due to effects of thelight-water reactor environment for new reactors”.

[24] Métais, T.; Courtin, S.; Genette, P.; De Baglion, L.; Gourdin, C.; Le Roux, J.-C.:Status of the French Methodology Proposal for Environmentally Assisted Fatigue Assessment.Proceedings of PVP2014, 2014 ASME Pressure Vessels & Piping Division Conference. July 20-24, 2014, Anaheim,CA, USA, Paper No. PVP2014-28408.

[25] Stéphan Courtin, André Lefrançois, Jean-Alain Le Duff, Anne Le Pécheur:Environmentally assisted fatigue assessment considering an alternative methode to ASME code case N-792;Proceedings of the ASME 2012 Pressure Vessels & Piping Conference, PVP2012, July 15-19, 2012, Toronto, Ontario,CANADA, PVP2012-78088.

[26] KTA Program of Standards, Standard No. 3201.4,Components of the Reactor Coolant Pressure Boundary of Light Water Reactors, Part 4: In-service Inspections andOperational Monitoring, issue 2010-11.

[27] Armin Roth und Bastian Devrient:Environmental Effects on Fatigue – Possible Reasons for the Apparent Mismatch between Laboratory Test Results andOperational Experience;FONTEVRAUD 7 - Contribution of Materials Investigations to Improve the Safety and Performance of LWRs, 26-30September, 2010, Avignon, Pope’s Palace, France.

[28] Chopra, O. and Stevens, G. J.:Effect of LWR Coolant Environments on the Fatigue Life of Reactor Materials,NUREG/CR-6909 Rev. 1, ANL-12/60, March 2014, Draft Report for Comment;http://pbadupws.nrc.gov/docs/ML1408/ML14087A068.pdf

[29] Seppänen, T., Alhainen, J., Arilahti, E., Solin, J.:Experimental Methods for Direct Strain-Controlled Low Cycle Fatigue Tests in Simulated PWR Water. OECD/NEACSNI WGIAGE; Fourth International Conference on Fatigue of Nuclear Reactor Components, 28th September-1stOctober, 2015, Sevilla, Spain (this conference), 5 p.

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[30] Solin, J., Reese, S., Karabaki, H.E. and Mayinger, W.:Fatigue of Stainless Steel in Simulated Operational Conditions: Effects of PWR Water, Temperature and Holds.Proceedings of ASME Pressure Vessel and Piping Division Conference, Anaheim, California, USA, July 20-24, 2014.11 p.

[31] ASME Code Case N-792-1, Section III, Division 1, Fatigue Evaluation Including Environmental Effects.

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OECD/NEA CSNI WGIAGE; Fourth International Conference on Fatigue of Nuclear Reactor Components

28th September-1st October, 2015, Sevilla, Spain

Experimental Methods for Direct Strain-Controlled Low Cycle Fatigue Tests in Simulated PWR Water

Tommi Seppänen, Jouni Alhainen, Esko Arilahti, Jussi Solin VTT Technical Research Centre of Finland Ltd., Espoo, Finland

SUMMARY “FaBello” has been developed to perform direct strain-controlled tests for stainless steels in simulated PWR water. Cyclic loading is generated by servo controlled pneumatic bellows inside the pressure vessel. As required in ASTM E-606 LCF procedure, the strain measured from specimen mid-section is used as feedback signal. Specimen alignment is secured by a rigid test frame. The results are directly compatible with international NPP design codes ASME III, KTA 3201.2 and RCC-M. Keywords: Fatigue, stainless steel, bellows, strain control, PWR 1. Introduction Fatigue assessment of nuclear components is based on a local strain approach, codified stress analysis and design curves. The design curves are derived from strain controlled low cycle fatigue (LCF) data in room temperature. As transferability of laboratory data to the operational conditions is of high concern in the nuclear industry, tests to measure effects of hot water environment have been performed in many laboratories. However, a majority of the methods seem to deviate from the standard LCF methods [1] used for determining the reference curve in air. Displacement control or thin walled tubular specimens have been used to overcome the lack of extensometers applicable in hot water. Use of non-standard specimens and methods may affect the resulting environmental factors (Fen). Dedicated facilities for standard LCF testing in high pressure and temperature environment have been developed and used for research at VTT for more than a decade. This paper gives an overview of the experimental methods used with the fatigue bellows, or “FaBello” for short. 2. Operating principle An overall view of one of the four FaBello devices is shown in Figure 1a with the load frame outside of the autoclave for test specimen mounting. During the tests the lid is lowered, leaving the load frame hanging inside the pressurized autoclave. By containing the entire loading unit within the autoclave during tests, problems such as friction from pressure boundary sealing elements are avoided.

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Strain is measured directly from the specimen gauge by using contact free eddy current sensors specifically designed for extreme conditions. A schematic of the measurement system is shown in Figure 1b. Using contacts to measure from the mid-section of the specimen is challenging. A suitable amount of force is necessary to prevent sliding but too much force or sharp knife edges could introduce notches and scratches, enhancing crack initiation from the contact point. A suitable compromise has been found with 3-point spring loaded contacts. The contacts on the specimen gauge section are connected with bars to base plates below the load frame. The eddy current sensors which are connected to the load frame, measure the change in displacement of the base plates as voltage values. These values are numerically transformed into strain values.

a) b)

Figure 1. a) Overview of one of the FaBello setups and b) schematic of the eddy current

displacement measurement, modified from [2]. Strain is induced by the pressurized metal bellows (Figure 2), which are essentially flexible gas springs. The test specimen with threaded ends is mounted at one end to the bellows and at the other end to the rigid load frame. Metal diaphragms at the top end of the specimen ensure alignment yet allow axial movement. Load transferred to the test specimen is calculated as a function of the pressure difference between the bellows and the autoclave. In short, tension to the specimen is caused when bellows pressure is below autoclave pressure. Compression follows the same logic. High precision pressure measurements and sensitive control of circulating water loop pressure improve accuracy. The pneumatic pressure providing system is servo-controlled. Its basic operating principle is shown in Figure 3. The automatic compressor (1) provides the system with an operational pressure. Electrical displacement data from the eddy current sensors (7) is transformed to strain and used as feedback to a servo controller, which compares measured values to command signal values. In case of a difference between the measured and command signals, the servo valve (6) is either opened or closed depending on whether bellows pressure needs to be relieved or increased.

EC sensors

EC base plates

(Inconel 625)

Connecting bars

Specimen

Metal alignment slides

Load frame

Pneumatic bellows

Pressure tube

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Figure 2. Bellows and surrounding components with Ø8 mm specimen.

Figure 3. Operating principle of the pressure adjusting loop, modified from [2]. 3. Fatigue testing capabilities With FaBello fatigue testing complies with standards ASTM E-606 [1] and ASTM E-1012 [3], meaning ASME III criteria for fatigue data are fulfilled. Direct measurement of displacement from the gauge section, rather than from specimen shoulders, is considered much more accurate especially for materials with such complex non-homogenous cyclic behaviour as stainless steels. To demonstrate a test was run in indirect strain control mode with displacement being measured from a 50 mm gauge length, just outside the specimen gauge section. Simultaneous measurement of strain was done directly

EC sensors x2

P

CSNI/R(2017)2/ADD1

from the gauge section. As Figure 4 shows, there is considerable non-linear drift in the real strain values when test control is based on values measured outside the middle of the specimen.

a) b) Figure 4. Comparison of direct (8 mm) and indirect (50 mm) strain measurements during tests

with austenitic stainless steel (alloy 321). a) indirect strain-controlled test b) direct strain-controlled test; both aimed to strain amplitude 0,3 %.

Additionally, the risk of specimen buckling under compression is small due to the shorter overall length required in a compact system entirely submerged inside the test chamber. Together with accurate alignment, the symmetrically attached gauge contacts guarantee that miscalculation of strain due to bending does not occur. Finally, there are no thermal gradients in the specimen material due to it being completely submerged in the autoclave. At present technological limitations of the pneumatic system restrict the maximum available strain rate to 1·10-4 s-1. Future developments are necessary to achieve higher strain rates, if faster HCF testing is aimed. The applied lower strain rate limit has generally been 4·10-6 s-1 but this has more to do with keeping the test duration reasonable than the equipment limits. In some tests with holds or low strain rate close to the horizontal part of the hysteresis loop and/or high strain amplitude, dynamic instability has been observed as shown in Figure 5. This kind of instability is triggered by serrated type flow but is also a consequence of the undamped bellows and could therefore be useful for highly sensitive dynamic strain ageing (DSA) investigation. However in fatigue testing instabilities should be avoided even if they do not affect fatigue life. The strain rate during these instabilities is very low, but they challenge the test control system by variation of the feedback signal. Similar observations on serrated flow have not been reported from laboratories using servo hydraulic test rigs, but this phenomenon may appear also in more rigid systems and cause instability, if high servo amplification is used. In the worst case, this may lead to loss of test control. FaBello has been used to provide data from 200 °C to 325 °C for a variety of loading signals. Constant amplitude tests with linear ramps are the easiest to perform, but also tests with variable amplitude or extended holds have been done as reported in [4] and [5] for example.

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Figure 5. Dynamic instability (DSA) in the near zero slope tensile part of a hysteresis loop after a hold. εa= 0,7 %, ε̇= 0,01 %/s, alloy 321.

4. Conclusion The environmental fatigue facilities developed at VTT represent the state-of-the-art in direct strain-controlled tests in simulated PWR water. Data directly comparable to the ASME air curve for stainless steel has been generated by overcoming the limitations of indirect strain control. Frictionless precision control of displacement with the use of bellows and pneumatic servo control are key elements of this system. Since laboratory data transferability to real components remains questionable even today, it is anticipated that research utilizing FaBello, with capabilities for complex loading sequences and hot holds, will in future continue to improve understanding and fill gaps in this area. 5. Acknowledgements The work is a part of the first author’s MS thesis work within the FOUND project (Analysis of Fatigue and Other Cumulative Ageing to Extend Lifetime), a sub-project of the Finnish Research Programme on Nuclear Power Plant Safety 2015-2018 (SAFIR2018).

REFERENCES

[1] ASTM E-606 Standard Practice for Strain-Controlled Fatigue Testing. ASTM International. [2] Moilanen, P. Pneumatic servo-controlled material testing device capable of operating at high temperature water and irradiation conditions. Doctoral thesis. VTT Publications 532. Espoo, 2004. 154 p. [3] ASTM E-1012 Standard Practice for Verification of Testing Frame and Specimen Alignment Under Tensile and Compressive Axial Force Application. ASTM International. [4] Solin, J. Fatigue of Stabilized SS and 316 NG Alloy in PWR Environment. Proceedings of ASME Pressure Vessel and Piping Division Conference. Vancouver, BC, Canada, July 23-27, 2006. Paper PVP2006-ICPVT11-93833. 11 p. [5] Solin, J., Reese, S., Karabaki, H.E. and Mayinger, W. Fatigue of Stainless Steel in Simulated Operational Conditions: Effects of PWR Water, Temperature and Holds. Proceedings of ASME Pressure Vessel and Piping Division Conference, Anaheim, California, USA, July 20-24, 2014. 11 p.

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