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

T. R. Xiang, X. I.A. Yang, Y. P. Shi

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


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.

Original languageEnglish (US)
Article number100252
JournalTheoretical and Applied Mechanics Letters
Issue number3
StatePublished - Mar 2021

All Science Journal Classification (ASJC) codes

  • Computational Mechanics
  • Environmental Engineering
  • Civil and Structural Engineering
  • Biomedical Engineering
  • Aerospace Engineering
  • Ocean Engineering
  • Mechanics of Materials
  • Mechanical Engineering


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