Guaranteed Conservation of Momentum for Learning Particle-based Fluid Dynamics. (arXiv:2210.06036v1 [cs.LG])

We present a novel method for guaranteeing linear momentum in learned physics
simulations. Unlike existing methods, we enforce conservation of momentum with
a hard constraint, which we realize via antisymmetrical continuous
convolutional layers. We combine these strict constraints with a hierarchical
network architecture, a carefully constructed resampling scheme, and a training
approach for temporal coherence. In combination, the proposed method allows us
to increase the physical accuracy of the learned simulator substantially. In
addition, the induced physical bias leads to …

arxiv conservation dynamics fluid dynamics