Large-eddy/Reynolds-averaged Navier–Stokes simulation of cavity-stabilized ethylene combustion

Potturi, Amarnatha Sarma; Edwards, Jack R.

doi:10.1016/j.combustflame.2014.10.011

Cited by 65 publications

(13 citation statements)

References 17 publications

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“…Based on these detailed mechanisms, reduced mechanisms have also been developed, such as the 19-species reduced mechanism [69], 22-species reduced mechanism [70], etc. These reduced mechanisms have been successfully used [71,72] in several LES studies of ethylene flames. However, the present study simulates many LES cases and those mechanisms remain too expensive.…”

Section: Numerical Methods For Flame Simulationsmentioning

confidence: 95%

Prediction of combustion instability limit cycle oscillations by combining flame describing function simulations with a thermoacoustic network model

Han

Morgans

2015

Combustion and Flame

203

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a b s t r a c t Accurate prediction of limit cycle oscillations resulting from combustion instability has been a long-standing challenge. The present work uses a coupled approach to predict the limit cycle characteristics of a combustor, developed at Cambridge University, for which experimental data are available (Balachandran, Ph.D. thesis, 2005). The combustor flame is bluff-body stabilised, turbulent and partially-premixed. The coupled approach combines Large Eddy Simulation (LES) in order to characterise the weakly non-linear response of the flame to acoustic perturbations (the Flame Describing Function (FDF)), with a low order thermoacoustic network model for capturing the acoustic wave behaviour. The LES utilises the open source Computational Fluid Dynamics (CFD) toolbox, OpenFOAM, with a low Mach number approximation for the flow-field and combustion modelled using the PaSR (Partially Stirred Reactor) model with a global one-step chemical reaction mechanism for ethylene/air. LES has not previously been applied to this partially-premixed flame, to our knowledge. Code validation against experimental data for unreacting and partially-premixed reacting flows without and with inlet velocity perturbations confirmed that both the qualitative flame dynamics and the quantitative response of the heat release rate were captured with very reasonable accuracy. The LES was then used to obtain the full FDF at conditions corresponding to combustion instability, using harmonic velocity forcing across six frequencies and four forcing amplitudes. The low order thermoacoustic network modelling tool used was the open source OSCILOS (http://www.oscilos.com). Validation of its use for limit cycle prediction was performed for a well-documented experimental configuration, for which both experimental FDF data and limit cycle data were available. The FDF data from the LES for the present test case was then imported into the OSCILOS geometry network and limit cycle oscillations of frequency 342 Hz and normalised velocity amplitude of 0.26 were predicted. These were in good agreement with the experimental values of 348 Hz and 0.21 respectively. This work thus confirms that a coupled numerical prediction of limit cycle behaviour is possible using an entirely open source numerical framework.

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Section: Numerical Methods For Flame Simulationsmentioning

confidence: 95%

Prediction of combustion instability limit cycle oscillations by combining flame describing function simulations with a thermoacoustic network model

Han

Morgans

2015

Combustion and Flame

203

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“…Here, we have blanked regions where the gradient of Z is large (in regions of non-premixed combustion such as at the leading edge of the jet) and where the equivalence ratio ϕ is less than 0.5 or greater than two (where the fuel and air are not mixed). We also do not plot regions where the heat release is less than 4% of the maximum heat release, similar to Poturri and Edwards [50]. The plotted region of the Karlovitz number shows that there is a significant fraction of the flowfield where Ka > 100, indicating that combustion in those regions occurs in the DRZ regime.…”

Section: B a Posteriori Analysis Of Combustion Regimementioning

confidence: 93%

Wall-Modeled Large-Eddy Simulation of Autoignition-Dominated Supersonic Combustion

2017

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Simulations of combustion in high-speed and supersonic flows need to account for autoignition phenomena, compressibility, and the effects of intense turbulence. In the present work, the evolution-variable manifold framework of Cymbalist and Dimotakis ("On Autoignition-Dominated Supersonic Combustion," AIAA Paper 2015-2315, June 2015) is implemented in a computational fluid dynamics method, and Reynolds-averaged Navier-Stokes and wall-modeled large-eddy simulations are performed for a hydrogen-air combustion test case. As implemented here, the evolution-variable manifold approach solves a scalar conservation equation for a reaction-evolution variable that represents both the induction and subsequent oxidation phases of combustion. The detailed thermochemical state of the reacting fluid is tabulated as a low-dimensional manifold as a function of density, energy, mixture fraction, and the evolution variable. A numerical flux function consistent with local thermodynamic processes is developed, and the approach for coupling the computational fluid dynamics to the evolution-variable manifold table is discussed. Wall-modeled large-eddy simulations incorporating the evolution-variable manifold framework are found to be in good agreement with full chemical kinetics model simulations and the jet in supersonic crossflow hydrogen-air experiments of Gamba and Mungal ("Ignition, Flame Structure and Near-Wall Burning in Transverse Hydrogen Jets in Supersonic Crossflow," Journal of Fluid Mechanics, Vol. 780, Oct. 2015, pp. 226-273). In particular, the evolutionvariable manifold approach captures both thin reaction fronts and distributed reaction-zone combustion that dominate high-speed turbulent combustion flows.Nomenclature a = speed of sound, m∕s C; X ; Z = progress variable, nonfuel mass fraction, and fuel mass fraction c v ; c v;s = mixture and s-species specific heats, J∕kg ⋅ K D = diffusion coefficient, m 2 ∕s E = total energy per unit volume, J∕m 3 e; e s = mixture and s-species specific energy, J∕kg F = convective flux vector h; h 0 = enthalpy and total enthalpy, J∕kg i = grid index J = jet momentum ratio j h = diffusive enthalpy flux k = kinetic energy, J∕kg L; R = values obtained from left and right data M s = s-species molar mass, kg∕kmol N s = number of species in detailed kinetics model n; n x ; n y ; n z = element face unit normal vector and components p = pressure, Pa q j = heat flux vector= vectors of conserved and primitive variables u; u; v; w = velocity vector and components, m∕s u 0 = face-normal velocity component, m∕s x; x j = position vector and its components, m Y s = s-species mass fraction α = dissipative flux factor δ R = reaction-zone thickness, m ε = dissipation rate ζ = evolution-variable source term, 1∕s η k = Kolmogorov length scale, m Λ; λ = diagonal matrix of eigenvalues and eigenvalue ν t ; ν = turbulence field variable and kinematic viscosity ρ; ρ s = density and s-species density, kg∕m 3 σ ij = viscous and Reynolds stress τ = evolution variable ϕ = stoichiometric fuel-air ratio χ = subgrid-s...

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“…In the present work, the reactive compressible Navier–Stokes (NS) equations are solved to identify the mechanism of detonation stabilization in a supersonic model combustor (Sun et al . 2008; Potturi & Edwards 2015), which consists of an expanding wall and a cavity. Previous investigations (Cai et al .…”

Section: Introductionmentioning

confidence: 99%

“…In the present work, the reactive compressible Navier-Stokes (NS) equations are solved to identify the mechanism of detonation stabilization in a supersonic model combustor (Sun et al 2008;Potturi & Edwards 2015), which consists of an expanding wall and a cavity. Previous investigations (Cai et al 2018a(Cai et al , 2019 have shown that both the cavity and expanding wall configurations can result in the generation of unburned jets, whose consumption and subsequent heat release are subjected to rapid turbulent mixing and diffusion.…”

Section: Introductionmentioning

confidence: 99%

Mechanism of detonation stabilization in a supersonic model combustor

et al. 2021

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Large-eddy/Reynolds-averaged Navier–Stokes simulation of cavity-stabilized ethylene combustion

Cited by 65 publications

References 17 publications

Prediction of combustion instability limit cycle oscillations by combining flame describing function simulations with a thermoacoustic network model

Prediction of combustion instability limit cycle oscillations by combining flame describing function simulations with a thermoacoustic network model

Wall-Modeled Large-Eddy Simulation of Autoignition-Dominated Supersonic Combustion

Mechanism of detonation stabilization in a supersonic model combustor

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