Computational fluid dynamics iteration driven by data
Thermal Science(2022)
摘要
Data-driven approaches have achieved remarkable success in different applica-tions, however, their use in solving PDE has only recently emerged. Herein, we present the potential fluid method, which uses existing data to nest physical meanings into mathematical iterative processes. Potential fluid method is suita-ble for PDE, such as CFD problems, including Burgers' equation. Potential fluid method can iteratively determine the steady-state space distribution of PDE. For mathematical reasons, we compare the potential fluid method with the finite dif-ference method and give a detailed explanation.
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关键词
data driven,artificial neural network,PDE,CFD,iteration
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