A systematic study of physics-informed neural networks for the level-set interface advection
We present a systematic ablation study of physics-informed neural networks (PINNs) for level-set advection across four benchmarks of increasing complexity: linear translation (TR), solid-body rotation (RO), reversed vortex deformation (RV), and the Zalesak rotating slotted disc (ZD), covering 69 experiments. For TR, a...