High-fidelity physics-based simulation of 3D materials and natural phenomena has become essential in many computational science domains such as structural engineering and vehicle/aircraft design, as well as a critical component in motion pictures, visual effects (VFX), animation, and video games. Numerical simulations have further found an increasing breadth of new applications such as real-time VFX previews, virtual reality games, interactive surgical training, predictive soft robotics, and computational fabrication. While theoretical computation capacity is now less of an impediment, a timely opportunity emerges for innovations in designing new numerical algorithms that mathematically resolve complex geometry and multi-physics with high accuracy and can best utilize new computational platforms with plausible scalability. While contributing towards this direction, the project will also directly promote modern interdisciplinary studies and education in scientific computing, mechanical engineering, and human-robot interaction. The application to simulating virtual humans will enable clinical training software, which not only improves patient care but also eliminates animal experiments. The support for large-scale geophysical simulation saves lives by improving the prediction of disasters like avalanches and landslides. The innovation of a versatile multi-physics system facilitates advances in climate sciences by modeling Arctic sea ice. This project will produce highly useful software systems for non-simulation experts and educational tools for STEM students. It will also strongly encourage the involvement of undergraduate students, underrepresented minorities, and women through a versatile set of educational events, exchange programs, and outreach activities.
This project will develop innovative computational algorithms, including flexible treatment of thin structures with the Material Point Method, a unified multi-material multi-physics framework to capture versatile phenomena, along with novel approaches harnessing the power of next-generation multi-GPU platforms. Co-dimensional geometries (metallic shells, fluid sheets, filaments, biological membranes, fibrous composites, threaded alloys, etc.) will be a primary focus. The project will build innovative geometric representations that are robust for heterogeneous materials, and numerical algorithms that naturally capture multi-physics. The innovative treatment of thin structures will enable new applications such as fiber-level wood crack prediction and fibrous food design/processing. The unified framework will create an exciting opportunity to improve clinical planning and training by enabling high-fidelity biomechanical simulation directly from tomographic imaging, while investigations into numerical stability and computational scalability will advance synergistic domains in computer graphics and computational science at large.
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.
