TY - JOUR
TI - Computational fluid dynamics iteration driven by data
AU - Zhou Zhijun
AU - Zhang Qi
AU - Cai Xichuan
AU - Li Kun
AU - Zhao Jingwei
JN - Thermal Science
PY - 2022
VL - 26
IS - 2
SP - 1165
EP - 1174
PT - Article
AB - Data-driven approaches have achieved remarkable success in different applications, 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 suitable 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 difference method and give a detailed explanation.