GAMES Webinar 2019 – 88期（物理模拟专题课程） | Xifeng Gao（佛罗里达州立大学），刘天添（微软亚洲研究院）
【GAMES Webinar 2019-88期】
报告题目：Decoupling Simulation Accuracy from Mesh Quality
Numerically solving partial differential equations (PDE) is a basic building block in many computer graphics and engineering applications, ranging from the computation of texture mappings and animation weights to the simulation of elastic deformations, fluid dynamics, and sound propagation. Finite element method (FEM) is the most common approach to solve PDEs, which should be a “black box”: the user provides as input the domain, boundary conditions, and the governing equations, and the FEM solver works as an evaluator that can compute the value of the solution at any point of the input domain. This is surprisingly far from being the case for all existing open-source or commercial software since FEM relies on a good mesh discretization of the domain, which is a fundamental challenge to control.I will present a simple, yet very effective, technique that decouples the simulation accuracy of elliptic PDEs from the mesh discretization quality. This technique decreases the burden on meshing algorithms, reducing the need for expensive mesh optimization, and automatically compensates for bad mesh regions, which are present due to boundary constraints or limitations of current meshing methods. This technique enables a fully black-box meshing and analysis solution for elliptic PDE problems.
Dr. Xifeng Gao is a tenure-track assistant professor of the Computer Science Department at Florida State University. Dr. Gao was a PostDoc for two years at the Courant Institute of Mathematical Sciences of New York University. He received his Ph.D. degree in 2016 and won the best Ph.D. dissertation award from the Department of Computer Science at the University of Houston. Dr. Gao has wide research interests that are related to geometry, such as Computer Graphics, Visualization, Multimedia Processing, Robotics, and Digital Fabrication. His research works have been published in several leading journals and conferences, e.g., ACM TOG, ACM TOMM, IEEE TVCG, SIGGRAPH, and SIGGRAPH ASIA. More etails about his research can be found on his homepage: https://gaoxifeng.github.io/.
报告题目：Position Based Dynamics — A fast yet physically plausible method for elastic body simulation
Position based dynamics (PBD) has gained its popularity in the computer graphics community for years because of its efficiency, stability, and simplicity. PBD is the foundation of many off the shelf real-time deformable body simulators such as NVidia Flex and Maya nDynamics; it has been therefore widely used by game and movie industries. However, PBD has also been considered as an ad-hoc solution that might deviate from the correct Newtonian physics solution ever since it was published. That is not an accurate statement. In this talk, we show a constraint-based simulation framework fully derived from Newtonian physics with different kinds of numerical solvers. We also reveal that PBD is one special numerical solver for this framework. Based on this observation, we discuss the potential future work to further improve the existing solvers to simulate elastic materials.
Tiantian Liu is an associate researcher at the Internet Graphics group in Microsoft Research Asia. His research interests include physically-based simulation and fast geometry processing algorithms. Before joining MSRA, he obtained his Ph.D. degree in Computer and Information Science at the University of Pennsylvania with Prof. Ladislav Kavan. He also had a Master’s degree in Computer Graphics and Game Technology at the University of Pennsylvania, and a Bachelor’s degree in Computer Science and Technology at Zhejiang University.
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