Physics-informed PointNet: a deep learning solver for steady-state incompressible flows and thermal fields on multiple sets of irregular geometries
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Publication:2168328
DOI10.1016/j.jcp.2022.111510OpenAlexW4288734997WikidataQ114163215 ScholiaQ114163215MaRDI QIDQ2168328
Publication date: 31 August 2022
Published in: Journal of Computational Physics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2202.05476
automatic differentiationincompressible flowirregular geometriesphysics-informed deep learningthermally-driven flow
Basic methods in fluid mechanics (76Mxx) Numerical methods for partial differential equations, initial value and time-dependent initial-boundary value problems (65Mxx) Incompressible viscous fluids (76Dxx)
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Uses Software
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