Integrating Computational Materials Engineering into ... · Goals • The goal of ICME is to...

Integrating Computational Materials Engineering into

Probabilistic Damage Tolerance Analysisfor

Component Design

Craig McClung, Michael Enright, Southwest Research Institute

Wei-Tsu Wu, Ravi ShankarScientific Forming Technologies Corporation

TMS 2013 Annual Meeting San Antonio, Texas

March 3-7, 2013

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Acknowledgments

• Funding for this effort was provided by the US Air Force Research Laboratory Small Business Innovative Research (SBIR) Projects

• Topic No. AF093-117• Phase I Contract FA8650-10-M-5110• Phase II Contract FA8650-11-C-5105

Rollie Dutton, AFRL Program Monitor

• Many colleagues made invaluable contributions Wuwei Liang, Kwai Chan, Jonathan Moody (SwRI) Simeon Fitch (Elder Research) Weiqi Luo, Jinyong Oh (SFTC)

Copyright 2013 Southwest Research Institute

Goals

• The goal of ICME is to optimize materials, manufacturing processes, and component design through integration of computational processes into a holistic system

• The specific goal of this effort is to link manufacturing process simulation directly to a critical measure of component reliability using production software

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Residual StressesMicrostructure

Material Anomalies

Risk of Component Fracture

Manufacturing Process Simulation Probabilistic Damage Tolerance Analysis

DARWIN® OverviewDesign Assessment of Reliability With INspection

Probabilistic Fracture Mechanics

Probability of DetectionAnomaly Distribution

Finite Element Stress Analysis

Material Crack Growth Data

NDE Inspection Schedule

Pf vs. Cycles

Risk Contribution FactorsLife Scatter

Stress Scatter

4Copyright 2013 Southwest Research Institute

DEFORM – Integrated Processand Material Modeling System

Inertia Welding

Machining

Cogging

Spin Pit Testing

Heat treatment

Forging

Rolling

Furnace Heating

Induction Heating

Extrusion

Sheet Forming

SPF

Hot Press Forming

Spot Welding

Stir Welding

MillingRing Rolling

Machining Distortion

LifeCasting

5

Numerical Simulation ofMaterial Processing

Residual Stresses Microstructure

Anomaly Tracking and DeformationCopyright 2013 Southwest Research Institute 6

DARWIN OverviewDesign Assessment of Reliability With INspection

• Anomaly location and orientation

• Residual stresses

• Microstructural influence on FCG properties

Probabilistic Fracture Mechanics

Probability of DetectionAnomaly Distribution

Finite Element Stress Analysis

Material Crack Growth Data

NDE Inspection Schedule

Pf vs. Cycles

Risk Contribution FactorsLife Scatter

Stress Scatter


Integration with Manufacturing Process Simulation

Link DEFORM output with DARWIN input Finite element geometry (nodes and elements) Finite element stress, temperature, and strain results Residual stresses at the end of processing / spin test Location specific microstructure / property data Tracked location and orientation of material anomalies


DARWIN-DEFORM Links


Anomaly Tracking and DeformationCopyright 2012 Southwest Research Institute 9

Residual Stress Modelingin DEFORM

• Residual stresses caused by non-uniform thermal, phase transformation and inelastic deformation during thermo-mechanical processing

• Uncontrolled tensile residual stresses result in dimensional control – distortion premature failure – limits life

• Controlled compressive residual stresses are beneficial

• Need to optimize thermo-mechanical processing

• Visco-elastic-plastic model predicts thermal, elastic, plastic, creep strain and residual stresses.

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Heat Treatment Modeling

Quenching after solution heat treat introduces substantial residual stresses11

DEFORM-DARWIN Residual Stress Interface

• A residual stress interface has been established between DEFORM and DARWIN Residual stress files are transferred from DEFORM to DARWIN using

SIESTA neutral file standard Service stress files can be transferred from DEFORM or other FE

codes (e.g., ANSYS, ABAQUS) using existing DARWIN capabilities

DEFORMDARWIN

Service StressNeutral file

Residual StressNeutral file

ANSYS

DEFORMDARWIN



ANSYS

Copyright 2012 Southwest Research Institute 12

DARWIN Stress Superposition Approach for Residual Stresses

• Arbitrary stress gradients are used to calculate crack driving force with weight function stress intensity factors

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stress gradient

Service Stress

0.0 0.2 0.4 0.6 0.8 1.0-0.8

-0.4

0.0

0.4

0.8

1.2

1.6

2.0

Residual Stress

Combined stress

Residual stress analysisDARWIN Stress ExtractionNormalized Distance

Nor

mal

ized

Stre

ssService StressNeutral file


stress gradient

Service Stress

0.0 0.2 0.4 0.6 0.8 1.0-0.8

-0.4

0.0

0.4

0.8

1.2

1.6

2.0

Residual Stress

Combined stress

Residual stress analysisDARWIN Stress ExtractionNormalized Distance

Nor

mal

ized

Stre

ss


Automated Calculation of Crack Growth Life and Risk

• DARWIN can perform full-field automated calculation of location-specific fatigue crack growth life and fracture risk Automatically generate idealized fracture

geometry model for any crack location in an arbitrary component geometry

Automatically extract arbitrary stress gradients from FE models and calculate crack driving force with weight function stress intensity factors

Automatically calculate fatigue crack growth lifetime from a common initial crack size at every designated location in the model

Automatically calculate the risk of component fracture with a probabilistic fatigue crack growth analysis, considering uncertainties in anomaly size & frequency, stress scatter, life scatter, NDE inspection time, and NDE POD



Demonstration Example: Effect of Material Processing Residual Stress on FCG Life

Stress

Life

Without Residual Stress With Residual Stress

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Effect of Material Processing Residual Stress on Fracture Risk

Life

Without Residual Stress With Residual Stress

Risk

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DARWIN-DEFORM Links


Anomaly Tracking and Deformation17Copyright 2012 Southwest Research Institute

Grain Size Modeling in DEFORMEmpirical – JMAK Method

Input: Initial average grain size distribution Strain, temperature, strain rate history Grain growth equations Recrystallization kinetics

• Dynamic• Metadynamic• Static

Output: Location-specific grain size contours Percentage recrystallization

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1010010

101010 cRTQdad

mnh

drx /exp.

Microstructure-Based Fatigue Crack Growth Model

' 'y f

Esξ4σ ε d

b

b1/b

EK2sξ

dNda /2

/11

K: Stress Intensity RangeE: Young’s Moduluss: Dislocation Cell Sized: Dislocation Barrier Spacingy : Cyclic Yield Stressf: Fatigue Ductilityb: Fatigue ExponentD: Grain Size

1/3

00

Dd dD


Practical Implementation of Micromechanical Models in DARWIN

• User provides standard fatigue crack growth properties and a single average grain size associated with these properties

• DEFORM calculates average grain sizes at each FE node

• DARWIN computes crack growth rate at selected locations by scaling micromechanical models based on grain size

• A similar paradigm can be used to calculate fatigue crack initiation lifetimes

*

*da D dafdN D dN


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Demonstration Example: Influence of Grain Size Scaling on Life & Risk

ANSYSABAQUSDEFORM

DEFORM

DARWIN

StressResults

Files

Grain SizeResults

Filegrain size contours

service stress contours


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Influence of Grain Size Scaling on Crack Growth Rate

*

*da D dafdN D dN

grain size contours

crack growth rate multiplier

C=1.56 x 10-11

n2=3.66

Nominal values:


Effect of Location-SpecificGrain Size Scaling on FCG Life

a=0.01”

Without Grain Size Scaling With Grain Size Scaling

a=0.02”


Effect of Location-Specific Grain Size Scaling on Fracture Risk

Life

Without Grain Size Scaling With Grain Size Scaling

Risk

a=0.01”


Other Ongoing Work

• Obtain calculated forging strains from DEFORM and use in DARWIN to predict the most likely orientations of ellipsoidal material anomalies at which fatigue cracks form and grow

• Perform DOE calculations with DEFORM to understand how variabilities in DEFORM input parameters (process variables) cause variability in DEFORM output parameters

• Calculate variability in calculated bulk residual stress as a function of variability in manufacturing process parameters using a surrogate (response surface) model for DEFORM

• Calculate effect of this residual stress variability on FCG life and fracture risk using DARWIN


Random Residual Stress Modeling (1)

• Design of Experiments Identify values of input variables for

response surface construction in DEFORM using Latin Hypercube sampling

Perform deterministic DEFORM runs to determine residual stress values at all nodes within FE model

• Response Surface Fitting Determine the residual stress response at

selected locations within the FE model in DARWIN using Gaussian Process (GP) model

Determine response along the crack path in DARWIN using GP model combined with Principal Components Analysis

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Design of Experiments

Response Surface


Random Residual Stress Modeling (2)

Distribution at Coordinate 0

Mean and variation at all locations along crack path

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• Next step – apply random residual stresses to crack growth life and fracture risk computations in DARWIN


Crack path in FE model

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Linking Materials and Lifing:Some Specific Needs

• Link microstructure and lifing properties

• Link processing analysis with life analysis

• Probabilistic models linking material/microstructural variability at relevant length scales to variability in fatigue/fracture/life properties and risk

• Microstructure-property models that are computationally efficient and robust Suitable for integration into the overall

optimization process, including linkages to probabilistic lifing codes

Microstructure

Processing

Lifing Properties

Life Prediction

Reliability

Summary

• Interfaces between DEFORM and DARWIN have been developed for bulk residual stresses and average grain size.

• These interfaces permit full-field results from manufacturing process simulations to be incorporated in predictions of fracture life and reliability.

• Approaches were presented for modeling the effects of location-specific bulk residual stress and average grain size on crack growth behavior.

• The interface and the proposed approaches were implemented in prototype software and used to perform demonstration examples for an idealized engine disk.

• The exercise demonstrates the practical potential for ICME that directly addresses component integrity.


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