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Combustion Theory and Modelling Volume 23, 2019 - Issue 4
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Articles

Adaptive chemistry lookup tables for combustion simulations using optimal B-spline interpolants

Mathis BodeInstitute for Combustion Technology, RWTH Aachen University, Aachen, GermanyCorrespondence[email protected]
ORCID Iconhttps://orcid.org/0000-0001-9922-9742View further author information
ORCID Icon,
Nathan CollierComputational Sciences and Engineering Division, Oak Ridge National Laboratory, Oak Ridge, TN, USAView further author information
,
Fabrizio BisettiDepartment of Aerospace Engineering and Engineering Mechanics, University of Texas at Austin, Austin, TX, USAView further author information
&
Heinz PitschInstitute for Combustion Technology, RWTH Aachen University, Aachen, GermanyView further author information
Pages 674-699 | Received 22 Mar 2018, Accepted 30 Sep 2018, Published online: 27 Feb 2019

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Read on this site (4)

Elizabeth Armstrong, John C. Hewson & James C. Sutherland. (2023) Characterizing Tradeoffs in Memory, Accuracy, and Speed for Chemistry Tabulation Techniques. Combustion Science and Technology 195:11, pages 2614-2633.
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Arash Mousemi, Mehdi Jadidi, Seth B. Dworkin & W. Kendal Bushe. (2023) Application of machine learning in low-order manifold representation of chemistry in turbulent flames. Combustion Theory and Modelling 27:1, pages 83-102.
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Panlong Yu & Hiroaki Watanabe. (2023) A simplified two-mixture-fraction-based flamelet modelling and its validation on a non-premixed staged combustion system. Combustion Theory and Modelling 27:1, pages 37-56.
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Elizabeth Armstrong, Michael A. Hansen, Robert C. Knaus, Nathaniel A. Trask, John C. Hewson & James C. Sutherland. (2022) Accurate Compression of Tabulated Chemistry Models with Partition of Unity Networks. Combustion Science and Technology 0:0, pages 1-18.
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Articles from other publishers (11)

Soledad Le Clainche, Esteban Ferrer, Sam Gibson, Elisabeth Cross, Alessandro Parente & Ricardo Vinuesa. (2023) Improving aircraft performance using machine learning: A review. Aerospace Science and Technology 138, pages 108354.
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Mathis Bode, Abhishek Y. Deshmukh, Tobias Falkenstein, Seongwon Kang & Heinz Pitsch. (2023) Hybrid scheme for complex flows on staggered grids and application to multiphase flows. Journal of Computational Physics 474, pages 108478.
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John P. Wakefield, Aaron M. Lattanzi, M. Brennan Pecha, Peter N. Ciesielski & Jesse Capecelatro. (2023) Fast estimation of reaction rates in spherical and non-spherical porous catalysts. Chemical Engineering Journal 454, pages 139637.
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Mathis Bode, Michael Gauding, Dominik Goeb, Tobias Falkenstein & Heinz Pitsch. (2023) Applying physics-informed enhanced super-resolution generative adversarial networks to turbulent premixed combustion and engine-like flame kernel direct numerical simulation data. Proceedings of the Combustion Institute 39:4, pages 5289-5298.
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M. Bode. 2023. Machine Learning and Its Application to Reacting Flows. Machine Learning and Its Application to Reacting Flows 279 305 .
Mathis Bode. (2022) Applying Physics-Informed Enhanced Super-Resolution Generative Adversarial Networks to Large-Eddy Simulations of ECN Spray C. SAE International Journal of Advances and Current Practices in Mobility 4:6, pages 2211-2219.
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Matthias Ihme, Wai Tong Chung & Aashwin Ananda Mishra. (2022) Combustion machine learning: Principles, progress and prospects. Progress in Energy and Combustion Science 91, pages 101010.
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Giuseppe D’Alessio, Alberto Cuoci & Alessandro Parente. (2021) Feature extraction and artificial neural networks for the on-the-fly classification of high-dimensional thermochemical spaces in adaptive-chemistry simulations . Data-Centric Engineering 2.
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Mathis Bode, Michael Gauding, Zeyu Lian, Dominik Denker, Marco Davidovic, Konstantin Kleinheinz, Jenia Jitsev & Heinz Pitsch. (2021) Using physics-informed enhanced super-resolution generative adversarial networks for subfilter modeling in turbulent reactive flows. Proceedings of the Combustion Institute 38:2, pages 2617-2625.
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Mathis Bode, Michael Gauding, Konstantin Kleinheinz & Heinz Pitsch. 2019. High Performance Computing. High Performance Computing 541 560 .
John P. Wakefield, Aaron M. Lattanzi, M. Brennan Pecha, Peter N. Ciesielski & Jesse Capecelatro. (2022) Fast Estimation of Reaction Rates in Spherical and Non-Spherical Porous Catalysts. SSRN Electronic Journal.
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