Graph neural network structural limitation for thermal simulation and architecture optimization through rating system
Abstract Graph neural networks are well suited for physics based simulation. Among other features, graphs can accurately represent thermal effects, with energy conservation operating on the nodes (vertices) and heat flow coursing through edges. Moreover, graph neural networks incorporate the data to...
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| Main Authors: | Pierre Hembert, Chady Ghnatios, Julien Cotton, Francisco Chinesta |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2025-08-01
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| Series: | Advanced Modeling and Simulation in Engineering Sciences |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s40323-025-00306-5 |
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