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CFD Modelling of Combustion Instabilities in Gas TurbineCombustors by means of VRG Approach

S. TiribuziENEL, Divisione GEM, Ricerca, PISA, Italy

1. IntroductionENEL operates a dozen combined cycle plants based on V94.3A gas turbines. Thesemachines are equipped with annular combustors. Each combustor has a ring of 24 low NOxswirl stabilized premixed burners equally spaced around the perimeter of the combustionchamber. Under particular conditions, this combustor configuration could develop dangerouscombustion-driven oscillations [1], coupled to strong noise emissions.In order to establish suitable operational rules to avoid such a negative occurrence or toevaluate the performance of possible control systems, a better knowledge of thermoacousticinstability behaviour is required. ENEL Research is pursuing studies to better understandthese phenomena through plant monitoring, experimental testing and numerical simulations.Nowadays many methodologies are used to numerically investigate the behavior ofthermoacoustic oscillations inside combustors. Usually they are hybrid methods which couplea simple acoustic network or finite element program with the flame characteristics derivedfrom experiments or detailed Computational Fluid Dynamics (CFD) runs.CFD itself would be the best tool to study this phenomenon due to its capability to accountfor all the fluiddynamics, reactive and acoustic aspects, but it is generally consideredimmature for the application to an industrial full size combustor, due to the necessity ofextending the computational domain up to including all the cavities involved in the acousticphenomenon and of running the transient for a sufficient time for the oscillation regime todevelop. In fact, the adoption of the canonical criteria on the grid cell refinement inevitablyleads to millions of cell grids, for which only stationary solutions or very short transients arepossible within a reasonable computing time.To overcome this problem, we adopt a CFD approach which shortens the computational timeby employing a very coarse grid. This VRG (Very Rough Grid) approach is based on theconsideration that thermoacoustic oscillations in a closed volume are much more affected byboth the acoustic propagation and the largest scale fluid structures, than by the detailed fluiddynamics aspects.KIEN, an in-house CFD code, has been used for the subject simulations. It is provided with acomplete set of specifically developed auxiliary codes for meshing, post-processing, andvisualization. The RANS fluid dynamic solver integrates the time dependent 3D Navier-Stokes equations for compressible viscous flows using the ALE (Alternate LagranganEulerian) method [2]. Fluid velocities are located on the vertexes of hexahedral cells arrangedin a monoblock structured grid, while all the other quantities are cell centred. For the presentapplication, turbulence is accounted for by adopting the k-_ RNG model and chemicalreactions are modelled with a reduced scheme of 7 reactions, whose reaction rates aredetermined by a combination of Arrhenius law and EDM (Eddy Dissipation Model)turbulence mixing. The transport of all the species involved in the reaction scheme plusnitrogen (9 in total) is modelled.

2. TAO Experimental Single Burner ConfigurationThe V64.3A premixed burner, a downscaled version of the burner equipping the V94.3A gasturbines, has been extensively tested in our TAO experimental plant, a facility for testing

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industrial size burners at low pressure combustive conditions, fitted with quartz windows forvisual access to the flame thus permitting optical measurements.Many tests have been performed to identify the operating conditions that inducethermoacoustic instabilities. Air mass flow and temperature, fuel gas mass flow and itsdistribution among premixed, diffusion and pilot nozzles have been changed. Variousquantities have been monitored at high frequency sampling rate, in particular the dynamicpressures in the air plenum and in the combustion chamber.Some of the test conditions produced large pressure oscillations, whose dominant frequenciesgroup around some discrete values, namely: 82, 105, 128, 152 Hz. Two of these tests,referred to as setting A and setting B, have been simulated using the KIEN code [3]. Bothsettings had the same dominant frequency of about 105 Hz, but different intensities.In order to correctly reproduce the acoustics of the facility, the computational domainincludes the air plenum chamber upstream of the burner and the whole 10 meter long exhausttube (fig.1a). The grid consists of a 3D monoblock arranged in a cylindrical logical structure.The grid is quite coarse (less than 15000 active cells), and therefore some important details,which are too small to be geometrically reproduced, have been modelled by simulating thecorresponding effects on the flow field.

Simulatedtime (s)

Fig. 1 TAO simulation: a (left) Computational domain and instantaneous pressurefluctuation field; b (right) KIEN transient profiles

The presented simulated transient lasts for 2.8 s in real time (fig.1b), starting from no motionand homogeneous initial conditions with initial temperature sets at ambient value. Thecomputational CPU time was about 9 hours on our SV1 Cray computer. The duration of thetransient was sufficient to let wide oscillations onset and reach the limit cycle for both thesettings. After ignition, the total heat release reached the power level of 450 kW. Then, widepower and pressure oscillations appeared and grew. At 1.2 s, their frequency spontaneouslyjumped from 82 Hz to the experimental value of 105 Hz and their amplitudes stabilized. At2.4 s, simulated test condition were switched from setting A to setting B, causing a furtherincrease in oscillation amplitudes.Congruence between the computed results and the available experimental values is good. Forexample, the spectra of the measured and computed time signals for the fluctuatingcomponent of the pressure inside the plenum (fig.2) exhibit the same dominant frequency,close maximum amplitudes and very similar trends. This dominant frequency corresponds tothe 5th longitudinal mode of the resonant pipe formed by the combustion chamber and theexhaust tube (fig.1a).

Static pressure incombustion chamber

(mbar abs)

Heat release (kW)

Combustion chamber

Burner

Airplenum

Exhaust tube (__10 m)

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Frequency (Hz) Frequency (Hz)

Fig. 2 TAO simulation - Spectra of fluctuating component of the plenum pressure

Figure 3 shows the periodical evolution at the end of simulated transient of streamlinesoriginated at the fuel injection section just inside the premix duct of the burner. The streamlines showthe strong variation in the axial component of the velocity (their length corresponds to 0.01 s, i.e.nearly one cycling period) and its swirling components. They are coloured with the local CH4 densitylevel to show the forward moving of the rich fuel mixture pocket up to the flame front location werethe methane burns.

Fig. 3 TAO simulation - Sequence of frames representing the burner mouth with streamlines

(generated at fuel injection section and advancing for 0.01s) coloured with CH4 density

2.1. Mechanism of Combustion InstabilityThe combustion instability mechanism driven by fuel inhomogeneities is well known, butCFD results provide a more precise description of its space-temporal evolution.Figure 4 represents 2 oscillation cycles at the end of the computed TAO transient, togetherwith a radial section of the computational grid in the burner region. An oscillation cycle startsat the pressure peak inside the combustion chamber. Immediately after, the maximum backpressure across the burner happens. After a while, it determines the minimum mixture flow inthe premixed channel of the burner. Due to the assumed flow constancy of the natural gasinjection, a fuel rich pocket forms in the premixed channel. This pocket travels downwards asthe mixture flow in the premix duct resumes, and exits the burner when the methane densityat the premix duct outlet reaches the peak. This pocket flows forward until it reaches theflame front where it burns. The maximum in heat release is immediately followed by a newhigh pressure peak in the combustion chamber, and this event completes the cycle.

Measuredspectrum

Simulatedspectrum

mbar mbar

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Fig. 4 TAO simulation - Analysis of thermoacoustic oscillation mechanism. Colour: blue = plenumpressure (mbar); red = combustion chamber pressure (mbar); black = burner Δp (mbar);green = premixed duct outlet flow (g/s); cyan = CH4 density of the burner outlet mixture(g/cm3); magenta=global instantaneous thermal power (kW).

The instability mechanism develops between two events which alternatively influences eachother: the pocket formation at the fuel injection and its burning in the flame. The downwardconvective delay time depends on the gas flow velocity and lasts for almost the entire cycleduration. The remaining part is spent on the influence of the pressure peak generated by theburning to the gas flow. This effect travels backward at sonic speed.

3. Whole Annular Combustor ConfigurationThe good results obtained with the single burner TAO configuration encouraged us to adoptthe same VRG approach to perform a CFD simulation of the whole annular combustorequipping our V94.3A gas turbines [4,5].The computational domain includes the entire circumferential extension of the combustionchamber, all 24 burners and the annular chamber of the air plenum upstream of them. Thegrid fineness was further reduced to keep the total number of grid nodes low, the resultingnumber of active cells being less than 74000.Many runs were performed varying operational and modelling parameters. Among the latter,the most effective one was the first coefficient AEDM of the Eddy Dissipation Model fordetermining the turbulent mixing reaction rate. The transient illustrated here includes twoconsecutive runs, where the two values of 3.0 and 4.5 were respectively attributed to AEDM

coefficient. The runs were prolonged until wide pressure oscillations spontaneously onset andgrew up to reaching the stationary limit cycle. The first run lasted for 1.2 s of real timesimulation, starting from no motion, homogeneous conditions, and the second run lasted for0.8 s. The overall CPU time was less than 40 hours, i.e. less than 1 day of CPU for 1 secondof simulated real time.

Maximumbackpressure

Pressurepeak in

combustionchamber

Maximummixtureenrich.

1 cycle

Simulated time(s)

Maximumheat release

Minimunair flow

intern.external

Air

Nat.Gas

Convective delay

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Fig. 5 Annular combustor simulation - a (left) Transient trends of some computed quantities; b(right) Wavelet analysis of pressure fluctuation inside the plenum

Figure 5a shows the trends of some computed quantities, and figure 5b presents the time-frequency wavelet analysis of the pressure fluctuation inside the plenum. The wavelet maphighlights the different oscillation regimes obtained with the two AEDM values, whichcorrespond to different fuel reactivity levels. A higher AEDM value produces a shorter flameand decreases the external convective time delay, making the oscillation regime to switchfrom the 2nd to the 3rd azimuthal mode. For the present run the first regime corresponds to the2nd rotating acoustic mode (fig.6), while the second regime corresponds to the 3rd standingacoustic mode (fig.7).

Fig. 6 Annular combustor simulation - Rotating 2nd acoustic mode pressure field

Fig. 7 Annular combustor simulation - Standing 3rd acoustic mode pressure field

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Other runs showed different acoustic field behaviour, with 2nd mode standing and 3rd moderotating oscillating pressure fields. In reality both these modes are the combination of twocounter-rotating acoustic fields, whose prevalent behaviour is determined by the differencebetween their respective intensities. Standing acoustic fields indicate that the counter-rotatingfields have nearly the same amplitudes, while rotating fields derive from a big differencebetween them.Notwithstanding the roughness of the grid, the low numerical diffusion of the computationalschemes implemented in the KIEN code is able to realistically represent some importantaspects of the fluid dynamic structures considered to play an essential role in the combustioninstability mechanism. This is the case of the large toroidal recirculation vortexes whichperiodically develop at the outer periphery of the burner mouth. The presence of thesevortices can be inferred from the negative (blue) values assumed by the axial velocity on thetemperature isosurfaces of figure 8 in the vicinity of the burner mouth.

Fig. 8 Annular combustor simulation - Flame front evolution (1350 K isosurfaces) coloured with

longitudinal velocity (blu: negative, red:, positive) during 2nd acoustic mode.

4. ConclusionsVRG approach for CFD simulation of combustive oscillation is capable of capturing the mostsignificant acoustic aspects of the thermoacoustic phenomena that could occur insideindustrial combustors. Such an approach is a straightforward method, which does not requirethe adoption of combined different methods for separately simulating the fluid dynamic andacoustic aspects of the phenomenon.This approach helps in better understanding the basic mechanism underlying the combustioninstabilities and in performing a preliminary evaluation of the effectiveness on the stabilitydue to modifications of operational conditions or combustor geometrical configuration.

5. References1. U. Krueger, J. Hueren, S. Hoffmann, W. Krebs, P. Flohr, and D. Bohn: Prediction and

Measurement of Thermoacoustic Improvements in Gas Turbines with AnnularCombustion Systems, ASME Turbo 2000-GT-0095 (Munich , 2000)

2. A. Amsden, J. Ramshaw, P. O’Rourke, and J. Dukowicz: A Computer Program for Two- andThree-Dimensional Fluids Flow with Chemical Sections and Fuel Sprays, Los Alamos,LA10245MS (1985)

3. S. Tiribuzi: CFD Modelling of thermoacoustic oscillations inside an atmospheric testrig generated by a DLN burner, ASME GT2004-53738 (Vienna, 2004)

4. S. Tiribuzi: Simulazione CFD delle instabilità termoacustiche in un combustoreanulare di un turbogas equipaggiato con bruciatori premiscelati, (in Italian), ATI60-12-09 (Roma, 2005)

5. S. Tiribuzi: Very Rough Grid Approach for CFD Modelling of ThermoacousticOscillations inside an Annular Premixed Combustor, ASME GT2006-90055(Barcelona 2006)