CRII: CHS: Robust Algorithms Modeling Frictional Contact with Industrial, Medical and Computer Graphics Applications

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Visual simulation methods for natural phenomena involving complex solid and fluid dynamics have been widely applied in digital animation and effects. Computer graphics and computational mechanics have also proved to be a powerful combination for pushing the boundaries of science and engineering in diverse fields such as soil mechanics, geophysics, biomechanics and engineering design. The current research aims to both alleviate existing computational bottlenecks and improve simulation resolution, with an emphasis on interacting coupled virtual materials with elaborate geometry and intricate frictional contact. Project outcomes will include algorithms with broad impact in various applications such as the analysis of geo-mechanical phenomena (landslides, debris flows, avalanches), the simulation of fully coupled human body parts for medical training (skin, muscle, organ, bone), and the design of granular material processing (in food, agriculture, mining, and the pharmaceuticals industry). The project will collaborate with researchers from these related science and engineering fields, and will advocate for interdisciplinary collaborations among undergraduate and graduate students and researchers. It will take steps to engage and attract both design and medical science students and will encourage the research careers of women and minority students through educational events, exchange programs, and other social activities. The project will focus on the development of highly robust and efficient new algorithms for modeling frictional contact under complex settings through innovative numerical discretization schemes and continuum elastoplastic models. The work will utilize the proven hybrid Lagrangian / Eulerian Material Point Method (MPM). A primary focus will be on the simulation of granular materials with nontrivial geometries in multi-physics settings. The methods will leverage spatial / temporal adaptivity, multiscale modeling, novel discretization schemes, efficient data structures, and low-level optimization exploiting hardware architecture. The techniques developed in this work will offer seamless coupling between rigid bodies, granular materials, deformable objects, and fluids; they will establish a solid foundation for a unified, versatile multi-material physics solver to handle complex phenomena in a way that requires minimal user interference.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.