Dynamically configured physics-informed neural network in topology optimization applications

Integration of machine learning (ML) into the topology optimization (TO) framework is attracting increasing attention, but data acquisition in data-driven models is prohibitive. Compared with popular ML methods, the physics-informed neural network (PINN) can avoid generating enormous amounts of data...

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Hauptverfasser:	Yin, Jichao, Wen, Ziming, Li, Shuhao, Zhanga, Yaya, Wang, Hu
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Learning
Online-Zugang:	Volltext bestellen
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