Physical information neural networks for 2D and 3D nonlinear Biot model and simulation on the pressure of brain

In this paper, we propose a self-adaptive algorithm of physics-informed neural networks (PINNs) for 2D and 3D linear and nonlinear Biot models, including solving the forward and inverse problems. Firstly, we apply the original PINNs algorithm to 2D and 3D linear and nonlinear Biot models. Secondly,...

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Veröffentlicht in:	Journal of computational physics Jg. 490; S. 112309
Hauptverfasser:	Chen, Hao, Ge, Zhihao
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Inc 01.10.2023
Schlagworte:	Deep learning High-dimensional problems Inverse problem Nonlinear Biot model Physics-informed neural networks Self-adaptive algorithm Deep learning Nonlinear Biot model Self-adaptive algorithm High-dimensional problems Physics-informed neural networks Inverse problem
ISSN:	0021-9991, 1090-2716
Online-Zugang:	Volltext
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