Multiple Mapping Conditioning: A New Modelling Framework for Turbulent Combustion

Cleary, M. J.; Klimenko, A. Y.

doi:10.1007/978-94-007-0412-1_7

Cited by 12 publications

(8 citation statements)

References 54 publications

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“…Most current approaches to modeling turbulent combustion in RANS and LES context can be categorized as flamelet-like [32][33][34][35][36][37][38][39][40][41] or PDF-like [42][43][44][45][46][47][48][49][50] with chemical species being directly transported. The former assumes that the compositions occurring in turbulent combustion reside in a very-low-dimensional manifold, and that the coupling between turbulent mixing and reaction can be parameterized by very few variables, e.g.…”

Section: Turbulence-chemistry Interactionsmentioning

confidence: 99%

Numerical simulation of turbulent combustion: Scientific challenges

Ren

Hou

et al. 2014

Sci. China Phys. Mech. Astron.

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Predictive simulation of engine combustion is key to understanding the underlying complicated physicochemical processes, improving engine performance, and reducing pollutant emissions. Critical issues as turbulence modeling, turbulence-chemistry interaction, and accommodation of detailed chemical kinetics in complex flows remain challenging and essential for highfidelity combustion simulation. This paper reviews the current status of the state-of-the-art large eddy simulation (LES)/probability density function (PDF)/detailed chemistry approach that can address the three challenging modelling issues. PDF as a subgrid model for LES is formulated and the hybrid mesh-particle method for LES/PDF simulations is described. Then the development need in micro-mixing models for the PDF simulations of turbulent premixed combustion is identified. Finally the different acceleration methods for detailed chemistry are reviewed and a combined strategy is proposed for further development.turbulence-chemistry interaction, detailed chemistry, probability density function, mixing models, large eddy simulations PACS number(s): 47.27.ep, 47.70.Fw, 47.70.Pq Citation:

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Section: Turbulence-chemistry Interactionsmentioning

confidence: 99%

Numerical simulation of turbulent combustion: Scientific challenges

Ren

Hou

et al. 2014

Sci. China Phys. Mech. Astron.

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“…We now consider Pope particles and distinguish location of the particle denoted by x = (x 1 , ..., x kx ) and particle properties denoted by y = (y 1 , ..., y ky ), that is X = (x, y) and k d = k x + k y . The variables x 1 , ..., x kx represent physical coordinates and, possibly, other reference variables such as those used in MMC mixing [40,41]. The coordinates x are conventionally governed by a Markov diffusion process while the particle properties y change due to mixing and, possibly, chemical reactions.…”

Section: Entropy Of Pope Particlesmentioning

confidence: 99%

Mixing, entropy and competition

Klimenko¹

2012

Phys. Scr.

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Non-traditional thermodynamics, applied to random behaviour associated with turbulence, mixing and competition, is reviewed and analysed. Competitive mixing represents a general framework for the study of generic properties of competitive systems and can be used to model a wide class of non-equilibrium phenomena ranging from turbulent premixed flames and invasion waves to complex competitive systems. We demonstrate consistency of the general principles of competition with thermodynamic description, review and analyse the related entropy concepts and introduce the corresponding competitive H-theorem. A competitive system can be characterized by a thermodynamic quantity-competitive potential-which determines the likely direction of evolution of the system. Contested resources tend to move between systems from lower to higher values of the competitive potential. There is, however, an important difference between conventional thermodynamics and competitive thermodynamics. While conventional thermodynamics is constrained by its zeroth law and is fundamentally transitive, the transitivity of competitive thermodynamics depends on the transitivity of the competition rules. Intransitivities are common in the real world and are responsible for complex behaviour in competitive systems. This work follows ideas and methods that have originated from the analysis of turbulent combustion, but reviews a much broader scope of issues linked to mixing and competition, including thermodynamic characterization of complex competitive systems with self-organization. The approach presented here is interdisciplinary and is addressed to the general educated readers, whereas the mathematical details can be found in the appendices.

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“…23 The model developed for sparse-Lagrangian FDF simulations is a generalized version 17 of the multiple mapping conditioning (MMC) framework for turbulent reactive flows. 24,25 In MMC, the mixing is localized within a reference space which is mathematically independent of the reactive composition field. This independence is highly desirable in a mixing model as it ensures that all chemical species mix equally and linearly.…”

Section: Introductionmentioning

confidence: 99%

A detailed quantitative analysis of sparse-Lagrangian filtered density function simulations in constant and variable density reacting jet flows

Cleary

Klimenko

2011

Physics of Fluids

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Sparse-Lagrangian filtered density function (FDF) simulations using a generalized multiple mapping conditioning mixing model and density coupling via a conditional form of the equivalent enthalpy method are performed for both constant density and variable density turbulent jet diffusion flames. The consistency between the sparse-Lagrangian FDF for the reactive species and the Eulerian large eddy simulation (LES) for velocity along with the accuracy of the reactive species predictions relative to the exact equilibrium solution are presented in detail. The sensitivity to the number of particles used in the simulations, the mixing localization structure, chemistry and numerical time step are all investigated. The analysis shows that consistency between the FDF and LES fields is relatively insensitive to the sparseness of the particle distributions and other model parameters but that the reactive species are strongly dependent on the degree of mixing localization in the LES mixture fraction space. An algorithm is developed to control the localization for any sparse distribution of particles with inter-particle distances within the inertial range, and it is shown that reactive species predictions are sensitive to the mixing distance in a reference mixture fraction space while there is very low sensitivity to the number of particles used in the simulations.

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Multiple Mapping Conditioning: A New Modelling Framework for Turbulent Combustion

Cited by 12 publications

References 54 publications

Numerical simulation of turbulent combustion: Scientific challenges

Numerical simulation of turbulent combustion: Scientific challenges

Mixing, entropy and competition

A detailed quantitative analysis of sparse-Lagrangian filtered density function simulations in constant and variable density reacting jet flows

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