Physics-guided spatiotemporal approach for melt pool size prediction in laser powder bed fusion

This study first proposes a physics-guided spatiotemporal graph. The melt pool temporal feature nodes and spatial feature nodes are extracted from melt pool images based on spatiotemporal correlations. These feature points are treated as graph nodes, and the edge weights in the graph are calculated...

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Hlavní autoři:	Yangkun Mao, Xin Lin, Haihong Zhu, Kunpeng Zhu
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	Taylor & Francis Group 2024-12-01
Edice:	Virtual and Physical Prototyping
Témata:	Forming process monitoring melt pool size prediction graph convolutional network (GCN) physics-guided machine learning feature fusion
On-line přístup:	https://www.tandfonline.com/doi/10.1080/17452759.2024.2427243
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