An efficient flamelet-based combustion model for compressible flows

Saghafian, Amirreza; Terrapon, Vincent; Pitsch, Heinz

doi:10.1016/j.combustflame.2014.08.007

Cited by 98 publications

(45 citation statements)

References 54 publications

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“…The results of the compressible FPV results of Saghafian et al [18] are notably different in the DRZ regime identified in the Karlovitz number analysis, with less near-wall burning where Ka > 100 in Fig. 7.…”

Section: B a Posteriori Analysis Of Combustion Regimementioning

confidence: 89%

“…Again, the EVM simulations are consistent with the experimental data, given the inherent temporal variation. See the work of Saghafian et al [18] for a corresponding image obtained with a compressible flamelet progress variable approach. Figure 9 plots the OH-PLIF experimental and EVM simulation data in a plane located at y∕d 0.5 above the flat plate.…”

Section: -Million-element Grid Simulationsmentioning

confidence: 99%

“…See the work of Saghafian et al [18] for corresponding compressible flameletprogress variable simulations. The EVM code was run in RANS mode (using second-order-accurate upwind fluxes, the SpalartAllmaras model [35], and a large time step) and in wall-modeled LES mode as described in Sec.…”

Section: Test Casesmentioning

confidence: 99%

“…Rather than tabulating all possible thermodynamic variables and transport properties (e.g., Saghafian et al [18] in the context of a compressible FPV model), we follow the approach suggested by Oevermann [32] and used by Wang et al [19]. That is, we tabulate the mass fractions obtained from the detailed chemistry WSR model and compute the local thermodynamic state from the density and energy computed by the CFD and the mass fractions interpolated from the table.…”

Section: Evm-les Implementationmentioning

confidence: 99%

“…Recent examples include compressible FPV simulations by Chan and Ihme [17], Saghafian et al [18], Wang et al [19], and Cao et al [20]; LEM simulations by Génin and Menon [21]; and TPDF and FMDF simulations by Delarue and Pope [22], Cocks et al [23], and Irannejad et al [24].…”

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confidence: 99%

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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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Section: B a Posteriori Analysis Of Combustion Regimementioning

confidence: 89%

Section: -Million-element Grid Simulationsmentioning

confidence: 99%

Section: Test Casesmentioning

confidence: 99%

Section: Evm-les Implementationmentioning

confidence: 99%

mentioning

confidence: 99%

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

2017

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Flamelet Modeling for Supersonic Combustion

Drozda

Quinlan

Drummond

2020

Modeling and Simulation of Turbulent Mixing and Reaction

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Simulation of a Scramjet Combustor: A Priori Study of Thermochemistry Tabulation Techniques

Ruan

Bouheraoua

Domingo

et al. 2020

Flow Turbulence Combust

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Large eddy simulations (LES) of a scramjet combustor are reported in this paper. The case under study is a cavity-based combustion chamber that is experimentally studied at the U.S Air Force Research Laboratory. The chamber is fed by eleven injectors. The computational domains are either simplified including only one or two injectors or complete with the 11 injectors. A good agreement is found between experimental data (velocities measured by PIV) and results from the LES if the kinetic used is chosen with care. A high temperature is found inside the cavity promoting a reactive zone located in the mixing layer where the flow velocity is high. At this location, the combustion occurs first in a diffusion dominated regime followed by the efficient burning of a well mixed mixture (rich then lean). A significant diffusion dominated burning is also found inside the cavity, mostly at the interface between the two recirculation zones. The simulation of the complete geometry revealed a transverse phenomenon on the temperature and mixing fields, but which had nevertheless little effect on the comparison with the available experimental data. A tabulation of the chemistry based on a premixed flamelet library without compressibility effects has been tested a priori on the results of the simulation with one injector. Good results on temperature and H 2 O fields are found. Significant localized discrepancies appeared on CO and CO 2 fields due to the complexity of the combustion regimes, while compressibility effects were found to be weak for the configuration studied.

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An efficient flamelet-based combustion model for compressible flows

Cited by 98 publications

References 54 publications

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

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

Flamelet Modeling for Supersonic Combustion

Simulation of a Scramjet Combustor: A Priori Study of Thermochemistry Tabulation Techniques

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