Front propagation formulation for large eddy simulation of turbulent premixed flames

Kim, Seung Hyun; Su, Yunde

doi:10.1016/j.combustflame.2020.07.009

Cited by 7 publications

(6 citation statements)

References 36 publications

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“…Heuristically, this is because the curvature term smooths out the flame front and reduces the total area of chemical reaction. Under the G-equation model, this is equivalent to showing that the effective burning velocity H is decreasing with respect to the Markstein number d, which has been observed in combustion experiments [26] and numerical computations [60,62]. We would like to point out that different Markstein number is achieved by the mixture of different fuels in experiments [26].…”

Section: Existence Of H For 2d Incompressible Flowsmentioning

confidence: 72%

“…Curvature dependence of flame speeds remain an active research topic in combustion science today [62]. With the increasing concern of global warming, new combustion systems aim specifically to reduce or eliminate greenhouse gas emissions.…”

Section: Basic Stochastic G-equationmentioning

confidence: 99%

“…To initiate a practical simulation of G-equation for turbulent flows, solutions of Navier-Stokes equations are often computed first to set up the velocity field V . For numerical approximations of G-equations and applications in combustion, we refer to [58,62,66,70,87,88,124] among others.…”

Section: Introductionmentioning

confidence: 99%

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Lagrangian, game theoretic, and PDE methods for averaging G-equations in turbulent combustion: existence and beyond

Xin,

Yu,

Ronney

2024

Bull. Amer. Math. Soc.

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G-equations are popular level set Hamilton–Jacobi nonlinear partial differential equations (PDEs) of first or second order arising in turbulent combustion. Characterizing the effective burning velocity (also known as the turbulent burning velocity) is a fundamental problem there. We review relevant studies of the G-equation models with a focus on both the existence of effective burning velocity (homogenization), and its dependence on physical and geometric parameters (flow intensity and curvature effect) through representative examples. The corresponding physical background is also presented to provide motivations for mathematical problems of interest. The lack of coercivity of Hamiltonian is a hallmark of G-equations. When either the curvature of the level set or the strain effect of fluid flows is accounted for, the Hamiltonian becomes highly nonconvex and nonlinear. In the absence of coercivity and convexity, the PDE (Eulerian) approach suffers from insufficient compactness to establish averaging (homogenization). We review and illustrate a suite of Lagrangian tools, most notably min-max (max-min) game representations of curvature and strain G-equations, working in tandem with analysis of streamline structures of fluid flows and PDEs. We discuss open problems for future development in this emerging area of dynamic game analysis for averaging noncoercive, nonconvex, and nonlinear PDEs such as geometric (curvature-dependent) PDEs with advection.

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Section: Existence Of H For 2d Incompressible Flowsmentioning

confidence: 72%

Section: Basic Stochastic G-equationmentioning

confidence: 99%

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Lagrangian, game theoretic, and PDE methods for averaging G-equations in turbulent combustion: existence and beyond

Xin,

Yu,

Ronney

2024

Bull. Amer. Math. Soc.

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“…It is assumed that the transition can be characterized primarily by the kernel size at which the transition process ends, defined here as the transition scale. The proposed flame transition model is combined with the FPF method 40,41 and a spark-ignition model adapted from Richard et al 33 for multi-cycle engine LES.…”

Section: Discussionmentioning

confidence: 99%

“…The flame propagation is simulated with the front propagation formulation (FPF) method, 40,41 which can maintain the flame speed and flame inner structure on under-resolved grids. The FPF method solves the filtered transport equation for the progress variable:…”

Section: Turbulent Combustion Modelmentioning

confidence: 99%

Laminar-to-turbulent flame transition and cycle-to-cycle variations in large eddy simulation of spark-ignition engines

Splitter

Kim

2020

International Journal of Engine Research

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This paper investigates the effect of laminar-to-turbulent flame transition modeling on the prediction of cycle-to-cycle variations (CCVs) in large eddy simulation (LES) of spark-ignition (SI) engines. A laminar-to-turbulent flame transition model that describes the non-equilibrium sub-filter flame speed evolution during an early stage of flame kernel growth is developed. In the present model, the flame transition is characterized by the flame kernel size at which the flame transition ends, defined here as the flame transition scale. The proposed model captures the effects that variations in a turbulent flow field have on the evolution of early-stage burning rates, through variations in the flame transition scale. The proposed flame transition model is combined with the front propagation formulation (FPF) method and a spark-ignition model to predict CCVs in a gasoline direct injection SI engine. It is found that multi-cycle LES with the proposed flame transition model reproduces experimentally-observed CCVs satisfactorily. When the transition model is not considered or when variations in the transition process are neglected, CCVs are significantly under-predicted for the case considered here. These results indicate the importance of modeling the laminar-to-turbulent flame transition and the effect of turbulence on the transition process, when predicting CCVs, under certain engine conditions. The LES results are also used to analyze sources for variations in the flame transition. It is found, for the present engine case, that the most important source is the cycle-to-cycle variation in the turbulence dissipation rate, which is used to measure the strength of turbulence in the proposed model, near a spark plug. The large-scale velocity field and the variations of the laminar flame speed due to the mixture composition and thermal stratification are also found to be important factors to contribute to the variations in the flame transition.

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Suppression of the turbulent kinetic energy and enhancement of the flame-normal Reynolds stress in premixed jet flames at small Lewis numbers

Yang

2022

Combustion and Flame

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Front propagation formulation for large eddy simulation of turbulent premixed flames

Cited by 7 publications

References 36 publications

Lagrangian, game theoretic, and PDE methods for averaging G-equations in turbulent combustion: existence and beyond

Lagrangian, game theoretic, and PDE methods for averaging G-equations in turbulent combustion: existence and beyond

Laminar-to-turbulent flame transition and cycle-to-cycle variations in large eddy simulation of spark-ignition engines

Suppression of the turbulent kinetic energy and enhancement of the flame-normal Reynolds stress in premixed jet flames at small Lewis numbers

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