Physics-informed neural networks for data-free surrogate modelling and engineering optimization – An example from composite manufacturing

Engineering components require an optimization of design and manufacturing parameters to achieve maximum performance – usually involving numerous physics-based simulations. Optimizing these parameters is a resource-intensive endeavor, though, especially in high-dimensional scenarios or for complex m...

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Hlavní autoři:	Tobias Würth, Constantin Krauß, Clemens Zimmerling, Luise Kärger
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	Elsevier 2023-07-01
Edice:	Materials & Design
Témata:	Machine learning Physics-based modeling Mesh-free surrogate modeling Data-free surrogates Composite process optimization
On-line přístup:	http://www.sciencedirect.com/science/article/pii/S0264127523004495
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