Abstract
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 language | English (US) |
|---|---|
| Article number | 100252 |
| Journal | Theoretical and Applied Mechanics Letters |
| Volume | 11 |
| Issue number | 3 |
| DOIs | |
| State | Published - 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