Modelling effects of subgrid-scale mixture fraction variance in LES of a piloted diffusion flame

Kemenov, Konstantin A.; Wang, Haifeng; Pope, Stephen B.

doi:10.1080/13647830.2011.645881

Cited by 43 publications

(27 citation statements)

References 37 publications

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“…This is not the case for the conditions of the SGT-100 and so this criterion works quite well. Also, this grid resolves the mixture fraction field well (see section IV C) and so the mean of the residual field is Φ" ≃ 0 and hence Φ ≃ Φ [69]. Hence the tilde notation will be dropped in the following discussion for the sake of simplicity.…”

Section: Resultsmentioning

confidence: 99%

Large-Eddy Simulation of Reacting Flows in Industrial Gas Turbine Combustor

Langella

Chen

Swaminathan

et al. 2018

Journal of Propulsion and Power

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The turbulent reacting flow in an industrial gas turbine combustor operating at 3 bar is computed using LES paradigm. The subgrid scale (SGS) combustion is modelled using a collection of unstrained premixed flamelets including mixture stratification.The non-premixed combustion mode is also included using a simple closure involving the scalar dissipation rate of the mixture fraction. A close attention is paid to maintain physical consistencies among sub-closure models for combustion and these consistencies are discussed on a physical basis. The importance of non-premixed mode and SGS mixture fraction fluctuations are investigated systematically. The results show that the SGS mixture fraction variance plays an important role and comparisons to measurements improve when contributions from the premixed and non-premixed modes are included. These numerical results and observations are discussed on a physical basis along with potential avenues for further improvements. a Research Associate, il246@cam.ac.uk b Research Associate, zc252@cam.ac.uk c Professor, ns341@cam.ac.uk d Engineer, suresh.sadasivuni@siemens.com 4 combustors. Thus, the ability of reacting flow CFD (Computational Fluid Dynamics) to capture these phenomena is crucial for their use in the design of next-generation combustors [2].Past studies have demonstrated that Large Eddy Simulation (LES) is suitable to capture aerodynamics of swirling flows, and the continuous increase of computing power allows application of LES-based models to practical burners [3][4][5][6][7]. Combustion requires modelling as it is a subgrid phenomenon in LES. Closures developed for the subgrid scale (SGS) reaction rate include: dynamic thickened flame model [8,9], linear eddy model [10], fractal flame-wrinkling model [11], partiallystirred reactor model [12], and Eulerian stochastic fields [13]. Another recently developed flamelet model for LES uses Scalar Dissipation Rate (SDR) closure [14,15], which is shown to be successful in RANS studies of industrial gas turbine combustors [16,17], but this approach has not been tested for LES of reacting flows in these combustors. This provides the motivation for this work.Due to large costs for experiments at realistic operating conditions of gas turbines (i.e. with optical access, high pressure, and preheated air), high quality validation data is rare [18]. One widely studied database is the set of laser-diagnostics obtained for Siemens SGT-100 combustor at 3 bar [19]. Analyses of these measurements and past LES results suggest that the combustion has flamelet-like properties despite the highly turbulent flow [5-7, 20, 21]. Flamelet models assume that the combustion time scale, τ c = s L /δ is shorter than the smallest turbulent scales (this also applies for length scales) implying that the flamelet structure is undisturbed by the turbulence. Thus, the SGS reaction rate can be calculated a priori using laminar flamelets. Hence, this methodology is also known as tabulated chemistry approach.Turbulent eddies can penetrate the flame-front di...

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Section: Resultsmentioning

confidence: 99%

Large-Eddy Simulation of Reacting Flows in Industrial Gas Turbine Combustor

Langella

Chen

Swaminathan

et al. 2018

Journal of Propulsion and Power

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“…However, differences may arise between the models at the discrete level, as previously highlighted by Kemenov et al 29 for models I and II. The variance models are indeed subject to numerical errors associated with the underresolution of the squared-gradient terms.…”

Section: Model Iii: Transport Equation For the Departure From Maximalmentioning

confidence: 88%

“…Especially, in the near field, the total variance (resolved and residual) is close to its maximum value, which is certainly due to the negligible scalar dissipation rate 2ρ χ ξ . As highlighted by Kemenov et al ,29 if the scalar dissipation rate is set to zero then the resolved squared mixture fraction ξ 2 will have the same transport equation than the resolved mixture fraction ξ. In this case, ξ 2 and ξ evolve in the same way, which formally leads to the maximum value of the SGS variance,…”

Section: Ivb2 Scalar Mean and Variance Profilesmentioning

confidence: 96%

Large Eddy Simulations of Combustion in a Supersonic Mach 2 Transverse Flow

Techer¹,

Lehnasch²,

Mura³

et al. 2015

20th AIAA International Space Planes and Hypersonic Systems and Technologies Conference

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Large eddy simulations (LES) of a hydrogen jet injected into a transverse supersonic flow of vitiated air at Mach 2 are carried out. The numerical simulations are performed with the computational fluid dynamics (CFD) solver CREAMS developed at the Pprime Institute of Poitiers. It makes use of high precision centered schemes combined with a seventh-order WENO reconstruction of the numerical fluxes. Detailed chemistry and transport are also taken into account at the resolved scale. The present study is focused on the assessment of the retained numerical strategy with respect to first-order computational parameters. This includes the discussion of the numerical errors including commutation and discretization errors as well as the influence of the retained subgrid scale closures. The sensitivity of the latter, i.e., subgrid scale representation, on the former, i.e., numerical errors is enlightened. A special focus is placed on the subgrid scale scalar variance evaluation, which is of much importance for forthcoming applications to reactive flow simulations. Nomenclature D m α matrix of flux diffusion coefficients of the species α into the mixture (m 2 /s) ∆ characteristic mesh size (m) e t mass total energy (J/kg) λ thermal conductivity of the mixture (W/m/K) µ sgs subgrid scale viscosity (kg/m/s) p pressure (Pa) ρ density of the mixture (kg/m 3 ) R universal gas constant (J/mol/K) τ ij viscous stress tensor (kg/m/s 2 ) T temperature of the mixture (K) T ij subgrid scale (SGS) stress tensor (kg/m/s 2 ) u i velocity component in direction i (m/s) V αi diffusion velocity component in direction i of the αth species (m/s) Y αchemical species mass fraction of the αth species (-) W molecular mass of the mixture (mol/kg) W α molecular mass of the αth species (mol/kg) X α molar fraction of the αth species (-) ξ passive scalar (or mixture fraction) (-) ξ v subgrid scale scalar variance (-)

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“…In this sense, the flamelet-type small-scale description is a better approach for modeling differential diffusion. Although such physics have been incorporated into conditional-diffusion models for the PDF approach as well [33], their accuracy has not been widely tested.On the other hand, resolved molecular transport can be the same order of magnitude as the sub-filter turbulent transport in the LES context [21,34]. This is mainly due to the fact that LES resolves large scale transport directly, and sub-filter turbulent diffusivity only captures the small-scale turbulence (in this paper, "turbulent viscosity" and "turbulent diffusivity" denote the viscosity and diffusivity used to model the turbulent motions unresolved by the LES grid; "molecular diffusivity" denotes the diffusivity resolved by the LES grid).…”

mentioning

confidence: 99%

“…On the other hand, resolved molecular transport can be the same order of magnitude as the sub-filter turbulent transport in the LES context [21,34]. This is mainly due to the fact that LES resolves large scale transport directly, and sub-filter turbulent diffusivity only captures the small-scale turbulence (in this paper, "turbulent viscosity" and "turbulent diffusivity" denote the viscosity and diffusivity used to model the turbulent motions unresolved by the LES grid; "molecular diffusivity" denotes the diffusivity resolved by the LES grid).…”

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confidence: 99%

LES/PDF modeling of autoignition in a lifted turbulent flame: Analysis of flame sensitivity to differential diffusion and scalar mixing time-scale

Han

Raman

Chen

2016

Combustion and Flame

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The stabilization of lifted flames involves a complex competition between small-scale mixing and propagation of flame kernels at the base of the flame. Here, the effect of species diffusivity on this stabilization process is explored. For this purpose, a large-eddy simulation (LES)/probability density function (PDF) methodology accounting for differential diffusion is developed. A dynamic model for scalar mixing time-scale is formulated to accurately describe the turbulence-driven mixing of scalars at the small-scales. Autoignition-stabilized H 2 /N 2 lifted turbulent flames in a vitiated coflow burner are chosen as test cases. Detailed chemical kinetics is used along with in situ adaptive tabulation (ISAT) to accelerate the computations. Four configuration test cases are considered: neglecting differential diffusion (Cases 1 and 2), considering differential diffusion (Case 3) and considering differential diffusion but neglecting molecular transport of H and H 2 (Case 4). A dynamic model for scalar mixing time-scale appearing in the mixing model is used in Cases 2, 3 and 4, which removes the need to specify the value of model constant. It is found that the lifted flames are very sensitive to differential diffusion. The predictions of major species mass fractions, temperatures and lift-off heights are in good agreement with the experimental data. Further, such agreement could be achieved without changing any boundary conditions. In particular, increased diffusion of species upstream allows ignition kernels to survive turbulent dissipation, causing stabilization to occur upstream. H 2 and H are identified as two critical species that play a dominant role in the differential diffusion effect. The model is also able to capture the change in lift-off height with change in coflow temperature. The results show that even in turbulent flames, stabilization of the flame zone can be sensitive to molecular diffusion. In LES computations where a significant part of this diffusion effect is resolved, the use of the enhanced LES/PDF/ISAT approach is seen as a promising approach for capturing the lift-off physics accurately.2 for in the solution to the one-dimensional flamelet equations. On the other hand, the spatial transport of this flame structure is through a conserved scalar (mixture fraction) and a reactive scalar representation. These scalars are necessarily transported using a single diffusivity. Consequently, the effect of differential diffusion at scales larger than the flame scales are neglected (or at best, inaccurately modeled). Blanquart et al. [31] have sought to address this issue by constructing mixture fraction equations that contain source terms to account for the change in species balance arising from differential diffusion. However, application of this approach to detailed chemistry based models is still being pursued. In the context of PDF methods, differential diffusion manifests in two different ways again. At the resolved scales, the PDF is altered by molecular diffusion through a second-order diffusion...

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Modelling effects of subgrid-scale mixture fraction variance in LES of a piloted diffusion flame

Cited by 43 publications

References 37 publications

Large-Eddy Simulation of Reacting Flows in Industrial Gas Turbine Combustor

Large-Eddy Simulation of Reacting Flows in Industrial Gas Turbine Combustor

Large Eddy Simulations of Combustion in a Supersonic Mach 2 Transverse Flow

LES/PDF modeling of autoignition in a lifted turbulent flame: Analysis of flame sensitivity to differential diffusion and scalar mixing time-scale

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