arXiv Machine Learning August 4, 2026 By Jiawei Wu, Teng Wang, Jiaqi Nan, Wang Han, Lijun Yang, Jingxuan Li

Efficient nonlinear flame response modeling for propulsion thermoacoustic analysis using limited numerical data

Read the original on arXiv Machine Learning →

arXiv:2409. 05885v2 Announce Type: replace Abstract: Characterizing nonlinear flame response is critical for predicting thermoacoustic instabilities in propulsion combustors, yet obtaining a comprehensive response map through high-fidelity simulations remains computationally prohibitive.

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