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pro vyhledávání: '"Zhanga, Yaya"'
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 (P
Externí odkaz:
http://arxiv.org/abs/2312.06993
The concurrent optimization of topology and fibre orientation is a promising approach to pursue higher strength and lighter weight of variable-stiffness structure. This study proposes a novel discrete-continuous scheme for the concurrent optimization
Externí odkaz:
http://arxiv.org/abs/2306.12297