TY - JOUR

T1 - Modeling subfilter soot-turbulence interactions in Large Eddy Simulation

T2 - An a priori study

AU - Berger, Lukas

AU - Wick, Achim

AU - Attili, Antonio

AU - Mueller, Michael E.

AU - Pitsch, Heinz

N1 - Funding Information:
Generous support of the Deutsche Forschungsgemeinschaft (DFG) and the Research Association for Combustion Engines (FVV) under grant numbers PI 368/25-1 (DFG) and 6013970 (FVV) for L.B. A.W. and H.P. is gratefully acknowledged. A.A. and H.P. gratefully acknowledge generous support of the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program (grant agreement no. 695747). Computational resources have been provided by the Gauss Centre for Supercomputing/Leibniz Supercomputing Centre in Munich.
Publisher Copyright:
© 2020 The Author(s)

PY - 2021/1

Y1 - 2021/1

N2 - A new LES model for subfilter soot-turbulence interactions is developed based on an a priori analysis using large-scale DNS data of temporally evolving non premixed n-heptane jet flames at a jet Reynolds number of 15,000. In this work, soot formation is modeled in LES by solving explicit transport equations for soot moments, and the unclosed filtered soot moment source terms are closed by a presumed PDF approach. Due to the strong intermittency of soot fields, a previous modeling approach assumes the presumed PDF to be bimodal accounting for sooting and non-sooting subfilter regions but neglects any sub-structure of the soot distribution. In this work, the modeling framework is improved by a new presumed PDF model that explicitly accounts for the sub-structure of the sooting mode, which is modeled by a log-normal distribution. The previous and new models are assessed by means of their prediction of the filtered source terms and the filtered intermittency, and the log-normal distribution is found to significantly reduce modeling errors, in particular, for the coagulation source term. Introducing a log-normal distribution for the PDF of the sooting mode involves a large amount of additional model parameters, such as the width of the distribution and correlation coefficients among different soot moments, so model assumptions to reduce the number of model parameters are discussed by means of the DNS data. The conclusions are found to be robust with respect to a variation in the global Damköhler number in the DNS datasets. The final model formulation only requires solving two additional transport equations in LES compared to previous models, while significantly improved model predictions are obtained for the coagulation source term which is import for predicting the number of soot particles.

AB - A new LES model for subfilter soot-turbulence interactions is developed based on an a priori analysis using large-scale DNS data of temporally evolving non premixed n-heptane jet flames at a jet Reynolds number of 15,000. In this work, soot formation is modeled in LES by solving explicit transport equations for soot moments, and the unclosed filtered soot moment source terms are closed by a presumed PDF approach. Due to the strong intermittency of soot fields, a previous modeling approach assumes the presumed PDF to be bimodal accounting for sooting and non-sooting subfilter regions but neglects any sub-structure of the soot distribution. In this work, the modeling framework is improved by a new presumed PDF model that explicitly accounts for the sub-structure of the sooting mode, which is modeled by a log-normal distribution. The previous and new models are assessed by means of their prediction of the filtered source terms and the filtered intermittency, and the log-normal distribution is found to significantly reduce modeling errors, in particular, for the coagulation source term. Introducing a log-normal distribution for the PDF of the sooting mode involves a large amount of additional model parameters, such as the width of the distribution and correlation coefficients among different soot moments, so model assumptions to reduce the number of model parameters are discussed by means of the DNS data. The conclusions are found to be robust with respect to a variation in the global Damköhler number in the DNS datasets. The final model formulation only requires solving two additional transport equations in LES compared to previous models, while significantly improved model predictions are obtained for the coagulation source term which is import for predicting the number of soot particles.

KW - LES

KW - Presumed PDF

KW - Soot

KW - Soot-turbulence interactions

KW - Subfilter modeling

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U2 - 10.1016/j.proci.2020.06.386

DO - 10.1016/j.proci.2020.06.386

M3 - Article

AN - SCOPUS:85097388858

SN - 1540-7489

VL - 38

SP - 2783

EP - 2790

JO - Proceedings of the Combustion Institute

JF - Proceedings of the Combustion Institute

IS - 2

ER -