Deep learning-based model for progress variable dissipation rate in turbulent premixed flames

Yellapantula, Shashank; Perry, Bruce A.; Grout, Ray W.

doi:10.1016/j.proci.2020.06.205

Deep learning-based model for progress variable dissipation rate in turbulent premixed flames

Journal Article · Fri Sep 11 00:00:00 EDT 2020 · Proceedings of the Combustion Institute

DOI:https://doi.org/10.1016/j.proci.2020.06.205· OSTI ID:1665878

^[1]; Perry, Bruce A. ^[1]; Grout, Ray W. ^[1]

National Renewable Energy Lab. (NREL), Golden, CO (United States)

A deep neural network (DNN) based large eddy simulation (LES) model for progress variable dissipation rate in turbulent premixed flames is presented. The DNN model is trained using filtered data from direct numerical simulations (DNS) of statistically planar turbulent premixed flames with n-heptane as fuel. Training data was comprised of flames with varying turbulence levels leading to a range of Karlovitz numbers. Through a-priori tests the DNN model is shown to predict the subfilter contribution to progress variable dissipation rate accurately over a range of filter widths and for all Karlovitz numbers examined in this study. Superior performance of the DNN model relative to an established physics-based model is also demonstrated. Additionally, transferability of the DNN model is highlighted by a-priori evaluation of the model using filtered DNS data from multiple cases with different Karlovitz numbers and fuel species than those that were used for training the model.

View Accepted Manuscript (DOE)

Research Organization:: National Renewable Energy Laboratory (NREL), Golden, CO (United States)

Sponsoring Organization:: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Vehicle Technologies Office (EE-3V)

Grant/Contract Number:: AC36-08GO28308

OSTI ID:: 1665878

Report Number(s):: NREL/JA--2C00-75428; MainId:6223; UUID:4d7fbbc7-8a05-ea11-9c2a-ac162d87dfe5; MainAdminID:18561

Journal Information:: Proceedings of the Combustion Institute, Journal Name: Proceedings of the Combustion Institute Journal Issue: 2 Vol. 38; ISSN 1540-7489

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

References (20)

Scalar Dissipation Rate Transport in the Context of Large Eddy Simulations for Turbulent Premixed Flames with Non-Unity Lewis Number Gao, Y.; Chakraborty, N.; Swaminathan, N. Flow, Turbulence and Combustion, Vol. 93, Issue 3 https://doi.org/10.1007/s10494-014-9553-5	journal	July 2014
Dynamic Closure of Scalar Dissipation Rate for Large Eddy Simulations of Turbulent Premixed Combustion: A Direct Numerical Simulations Analysis Gao, Y.; Chakraborty, N.; Swaminathan, N. Flow, Turbulence and Combustion, Vol. 95, Issue 4 https://doi.org/10.1007/s10494-015-9631-3	journal	August 2015
Turbulent premixed combustion: Further discussions on the scales of fluctuations Borghi, R. Combustion and Flame, Vol. 80, Issue 3-4 https://doi.org/10.1016/0010-2180(90)90106-2	journal	June 1990
Turbulent combustion modeling Veynante, Denis; Vervisch, Luc Progress in Energy and Combustion Science, Vol. 28, Issue 3 https://doi.org/10.1016/S0360-1285(01)00017-X	journal	March 2002
Validation and implementation of algebraic LES modelling of scalar dissipation rate for reaction rate closure in turbulent premixed combustion Ma, Terence; Gao, Yuan; Kempf, Andreas M. Combustion and Flame, Vol. 161, Issue 12 https://doi.org/10.1016/j.combustflame.2014.05.023	journal	December 2014
Differential diffusion effects, distributed burning, and local extinctions in high Karlovitz premixed flames Lapointe, Simon; Savard, Bruno; Blanquart, Guillaume Combustion and Flame, Vol. 162, Issue 9 https://doi.org/10.1016/j.combustflame.2015.06.001	journal	September 2015
A priori filtered chemical source term modeling for LES of high Karlovitz number premixed flames Lapointe, Simon; Blanquart, Guillaume Combustion and Flame, Vol. 176 https://doi.org/10.1016/j.combustflame.2016.11.015	journal	February 2017
Effects of dissipation rate and diffusion rate of the progress variable on local fuel burning rate in premixed turbulent flames Savard, Bruno; Blanquart, Guillaume Combustion and Flame, Vol. 180 https://doi.org/10.1016/j.combustflame.2017.02.025	journal	June 2017
Training convolutional neural networks to estimate turbulent sub-grid scale reaction rates Lapeyre, Corentin J.; Misdariis, Antony; Cazard, Nicolas Combustion and Flame, Vol. 203 https://doi.org/10.1016/j.combustflame.2019.02.019	journal	May 2019
Deep learning for presumed probability density function models T. Henry de Frahan, Marc; Yellapantula, Shashank; King, Ryan Combustion and Flame, Vol. 208 https://doi.org/10.1016/j.combustflame.2019.07.015	journal	October 2019
Premixed turbulent combustion modeling using tabulated detailed chemistry and PDF Fiorina, B.; Gicquel, O.; Vervisch, L. Proceedings of the Combustion Institute, Vol. 30, Issue 1 https://doi.org/10.1016/j.proci.2004.08.062	journal	January 2005
Scalar dissipation rate modelling for Large Eddy Simulation of turbulent premixed flames Dunstan, T. D.; Minamoto, Y.; Chakraborty, N. Proceedings of the Combustion Institute, Vol. 34, Issue 1 https://doi.org/10.1016/j.proci.2012.06.143	journal	January 2013
Modified laminar flamelet presumed probability density function for LES of premixed turbulent combustion Mahdi Salehi, M.; Kendal Bushe, W.; Shahbazian, Nasim Proceedings of the Combustion Institute, Vol. 34, Issue 1 https://doi.org/10.1016/j.proci.2012.06.177	journal	January 2013
Influence of combustion on principal strain-rate transport in turbulent premixed flames Steinberg, A. M.; Coriton, B.; Frank, J. H. Proceedings of the Combustion Institute, Vol. 35, Issue 2 https://doi.org/10.1016/j.proci.2014.06.089	journal	January 2015
A two mixture fraction flamelet model for large eddy simulation of turbulent flames with inhomogeneous inlets Perry, Bruce A.; Mueller, Michael E.; Masri, Assaad R. Proceedings of the Combustion Institute, Vol. 36, Issue 2 https://doi.org/10.1016/j.proci.2016.07.029	journal	January 2017
Interaction of turbulence and scalar fields in premixed flames Swaminathan, N.; Grout, R. W. Physics of Fluids, Vol. 18, Issue 4 https://doi.org/10.1063/1.2186590	journal	April 2006
Influence of the Damköhler number on turbulence-scalar interaction in premixed flames. II. Model development Chakraborty, N.; Swaminathan, N. Physics of Fluids, Vol. 19, Issue 4 https://doi.org/10.1063/1.2714076	journal	April 2007
Interactions between turbulence and flames in premixed reacting flows Hamlington, Peter E.; Poludnenko, Alexei Y.; Oran, Elaine S. Physics of Fluids, Vol. 23, Issue 12 https://doi.org/10.1063/1.3671736	journal	December 2011
Scalar Dissipation Rate Modeling and its Validation Kolla, H.; Rogerson, J. W.; Chakraborty, N. Combustion Science and Technology, Vol. 181, Issue 3 https://doi.org/10.1080/00102200802612419	journal	February 2009
Algebraic Closure of Scalar Dissipation Rate for Large Eddy Simulations of Turbulent Premixed Combustion Gao, Y.; Chakraborty, N.; Swaminathan, N. Combustion Science and Technology, Vol. 186, Issue 10-11 https://doi.org/10.1080/00102202.2014.934581	journal	September 2014

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