A deep learning-based model reduction (DeePMR) method for simplifying chemical kinetics

A deep learning-based model reduction (DeePMR) method for simplifying chemical kinetics is proposed and validated using high-temperature auto-ignitions, perfectly stirred reactors (PSR), and one-dimensional freely propagating flames of n-heptane/air mixtures. The mechanism reduction is modeled as an...

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Veröffentlicht in:	arXiv.org 2022-09
Hauptverfasser:	Wang, Zhiwei, Zhang, Yaoyu, Zhao, Enhan, Ju, Yiguang, Weinan, E, Zhi-Qin John Xu, Zhang, Tianhan
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial neural networks Boolean Boolean algebra Data sampling Deep learning Delay time Equivalence ratio Flames Heptanes High temperature Iterative methods Machine learning Model reduction Optimization Reaction kinetics
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