A stochastic multiple mapping conditioning computational model in OpenFOAM for turbulent combustion

Galindo-Lopez, S., Salehi, F., Cleary, M. J., Masri, A. R., Neuber, G., Stein, O. T., Kronenburg, A., Varna, A., Hawkes, E. R., Sundaram, B., Klimenko, A. Y. and Ge, Y. (2018) A stochastic multiple mapping conditioning computational model in OpenFOAM for turbulent combustion. Computers and Fluids, . doi:10.1016/j.compfluid.2018.03.083

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Author Galindo-Lopez, S.
Salehi, F.
Cleary, M. J.
Masri, A. R.
Neuber, G.
Stein, O. T.
Kronenburg, A.
Varna, A.
Hawkes, E. R.
Sundaram, B.
Klimenko, A. Y.
Ge, Y.
Title A stochastic multiple mapping conditioning computational model in OpenFOAM for turbulent combustion
Journal name Computers and Fluids   Check publisher's open access policy
ISSN 0045-7930
Publication date 2018-03-31
Sub-type Article (original research)
DOI 10.1016/j.compfluid.2018.03.083
Open Access Status File (Author Post-print)
Total pages 16
Place of publication Kidlington, Oxford, United Kingdom
Publisher Pergamon Press
Language eng
Abstract Computational models for combustion must account for complex and inherently interconnected physical processes including dispersion, mixing, chemical reactions, particulate nucleation and growth and, critically, the interactions of these with turbulence. The development of affordable and accurate models that are widely applicable is a work in progress. Stochastic multiple mapping conditioning (MMC) is a fast-emerging approach that has been successfully applied to non-premixed, premixed and partially premixed flames as well to the modelling of liquid and solid particulate synthesis. The method solves the conventional PDF transport equation but incorporates an additional constraint in that the mixing is localised in a reference space. This paper describes the numerical implementation of stochastic MMC in an OpenFOAM compatible code called mmcFoam. The model concepts and equations along with alternative submodels, code structure and numerical schemes are explained. A focus is placed on validation of the computational methods in particular demonstrating numerical convergence and mass consistency of the hybrid Eulerian/Lagrangian schemes. Four validation cases are selected including a combustion direct numerical simulation (DNS) case, two combustion experimental jet flame cases and a non-combusting particulate synthesis case. The results show that the total mass and mass distribution of Eulerian and Lagrangian schemes are consistent and confirm that the solutions numerically converge with increasing number of stochastic computational particles and sections for describing particulate size distribution.
Keyword MmcFoam
Multiple mapping conditioning
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: School of Mechanical & Mining Engineering Publications
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Created: Fri, 20 Apr 2018, 04:32:59 EST