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pro vyhledávání: '"Hosseinmardi, Shirin"'
Topology optimization (TO) provides a principled mathematical approach for optimizing the performance of a structure by designing its material spatial distribution in a pre-defined domain and subject to a set of constraints. The majority of existing
Externí odkaz:
http://arxiv.org/abs/2408.03490
Deep neural networks (DNNs) are increasingly used to solve partial differential equations (PDEs) that naturally arise while modeling a wide range of systems and physical phenomena. However, the accuracy of such DNNs decreases as the PDE complexity in
Externí odkaz:
http://arxiv.org/abs/2403.15652
Neural Networks with Kernel-Weighted Corrective Residuals for Solving Partial Differential Equations
Physics-informed machine learning (PIML) has emerged as a promising alternative to conventional numerical methods for solving partial differential equations (PDEs). PIML models are increasingly built via deep neural networks (NNs) whose architecture
Externí odkaz:
http://arxiv.org/abs/2401.03492
Publikováno v:
Computational Mechanics; Jul2024, Vol. 74 Issue 1, p191-221, 31p