Neuroevolution-enabled adaptation of the Jacobi method for Poisson's equation with density discontinuities

• 作者: T.-R. Xiang X.I.A. Yang Y.-P. Shi
• 来源期刊: 力学快报（英文版）
• 年，卷（期）: 2021,（3）
• 所属期刊栏目: Fluid Mechanics
• 页码范围: 172-179
• 页数: 8页
• 语种: 英文
• DOI: 10.3969/j.issn.2095-0349.2021.03.009

摘要

Lacking labeled examples of working numerical strategies, adapting an iterative solver to accommodate a numerical issue, e.g., density discontinuities in the pressure Poisson equation, is non-trivial and usually involves a lot of trial and error. Here, we resort to evolutionary neural network. A evolutionary neural network observes the outcome of an action and adapts its strategy accordingly. The process requires no labeled data but only a measure of a network's performance at a task. Applying neuro-evolution and adapting the Jacobi iterative method for the pressure Poisson equation with density discontinuities, we show that the adapted Jacobi method is able to accommodate density discontinuities.