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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Bibliographic Details
Main Authors: Pierre Hembert, Chady Ghnatios, Julien Cotton, Francisco Chinesta
Format: Article
Language:English
Published: SpringerOpen 2025-08-01
Series:Advanced Modeling and Simulation in Engineering Sciences
Subjects:
Online Access:https://doi.org/10.1186/s40323-025-00306-5
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