MACHINE-LEARNING BASED SOLVER OF COUPLED-PARTIAL DIFFERENTIAL EQUATIONS
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Aug 15, 2024
app pub date -
Apr 26, 2024
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Mar 25, 2020
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Partial differential equations used to simulate physical systems can be solved, in one embodiment, by a solver that has been trained with a set of generative neural networks that operated at different resolutions in a solution space of a domain that defines the physical space of the physical system. The solver can operate in a latent vector space which encodes solutions to the PDE in latent vectors in the latent vector space. The variables of the PDE can be partially decoupled in the latent vector space while the solver operates. The domain can be divided into subdomains that are classified based on their positions in the domain.
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