Smoothed Particle Hydrodynamics

Smoothed Particle Hydrodynamics (SPH) is a mesh-free computational method used to simulate fluid dynamics and other physical phenomena by representing the continuum as interacting particles. Current research emphasizes integrating SPH with machine learning, particularly graph neural networks and neural operators, to improve simulation accuracy, efficiency, and the ability to solve inverse problems. This approach is proving valuable in diverse applications, including robot swarm control, generative modeling, and multiscale modeling of complex systems, offering a powerful alternative to traditional grid-based methods. The development of differentiable SPH frameworks and comprehensive benchmarking suites further accelerates progress in this rapidly evolving field.