AF: Small: Collaborative Research: Scalable and Topologically Versatile Material Point Methods for Complex Materials in Multiphysics Simulation

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Computational simulation of natural phenomena is a ubiquitous tool in the natural sciences (environmental modeling, prediction of earthquakes or avalanches), bio-mechanics (modeling the musculoskeletal system, organ function, or tissue damage), manufacturing (product design, prototyping, and verification) as well as in computer graphics/animation. This project advances the science of simulation using a technique called Material Point Methods (MPM), by increasing the number of materials and range of phenomena that can be simulated, and optimizing the performance of numerical algorithms used for simulations at larger scales. The enhancements from this project will enable studies in terrain dynamics, design and prototyping of vehicles and agricultural implements interacting with complex soils, modeling of material failure and fracture scenarios including biological settings such as skin tearing, surgical incisions, or vascular rupture. The optimization and scaling will allow computational studies of simulated physical systems at levels of resolution that were previously only afforded to large enterprises.This project extends MPM simulation to: a) materials with multi-phase interactions influenced by thermodynamics; and b) media with complex multi-scale geometric features, including porosity (e.g. water-soil interactions) or aggregates dominated by grains of non-spherical geometry. This project extends MPM simulation to phenomena that include intricate frictional contact (beyond the no-slip contact model embedded in traditional MPM), dynamic crack propagation, and de-cohesion. This research thread leverages the team's prior work on non-manifold data structures for storing implicit geometry representations, allowing the background grids of MPM to incorporate a richer set of topological features (e.g. tears and incisions) than those incorporated by conventional array-based regular lattices. Finally, this research boosts the scale of MPM simulations that can be accommodated in modern multiprocessors, improving detail, resolution as well as parallel efficiency.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.