Physics-informed PointNet: A deep learning solver for steady-state incompressible flows and thermal fields on multiple sets of irregular geometries
We present a novel physics-informed deep learning framework for solving steady-state incompressible flow on multiple sets of irregular geometries by incorporating two main elements: using a point-cloud based neural network to capture geometric features of computational domains, and using the mean sq...
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Veröffentlicht in: | Journal of computational physics 2022-11, Vol.468, p.111510, Article 111510 |
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Sprache: | eng |
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