Regression transients modeling of solid rocket motor burning surfaces with physics-guided neural network

Monitoring the burning surface regression in ground static ignition tests is crucial for predicting the internal ballistic performance of solid rocket motors (SRMs). A previously proposed ultra-sparse computed tomography imaging method provides a possibility for real-time monitoring. However, sample...

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書誌詳細

主要な著者:	XueQin Sun, Yu Li, YiHong Li, SuKai Wang, Xuan Li, Ming Lu, Ping Chen
フォーマット:	Artigo
言語:	Inglês
出版事項:	IOP Publishing 2024-01-01
シリーズ:	Machine Learning: Science and Technology
主題:	solid rocket motors burning surface regression level-set partial differential equation physics-informed neural network neural operator
オンライン･アクセス:	https://doi.org/10.1088/2632-2153/ad2973
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