GAMES Webinar 2017-09期（Siggraph 2017论文报告）| 蒋陈凡夫（美国宾夕法尼亚大学）
【GAMES Webinar 2017-09期】
报告嘉宾：蒋陈凡夫，美国宾夕法尼亚大学
报告时间：2017年8月17日（星期四）晚20:00-21:30（北京时间）
主持人：郭延文，南京大学（个人主页：http://cs.nju.edu.cn/ywguo）
报告题目：物质点法模拟最新进展：混合材料交互以及全自动布料与毛发的摩擦碰撞
报告摘要：
Simulation of natural phenomena for virtual worlds and characters is an important aspect of computer graphics that remains extremely demanded. The most challenging natural phenomena are those whose dynamics involve dramatic topological changes and therefore require sophisticated numerical approaches to achieve sufficient accuracy and visual realism. The need for computational efficiency, topological variability, and numerical stability has led trendy visual computing toward hybrid, Lagrangian/Eulerian methods, particularly the Particle-In-Cell variants. In this talk, I will discuss the recent research advances in the Material Point Method (MPM) — a generalization of the Fluid Implicit Particle (FLIP) method to solid mechanics.
Particularly I will cover two of our recent SIGGRAPH 2017 papers:
(1) Multi-species simulation of porous sand and water mixtures, Andre Pradhana Tampubolon, Theodore Gast, Gergely Klar, Chuyuan Fu, Joseph Teran, Chenfanfu Jiang, Ken Museth;
(2) Anisotropic Elastoplasticity for Cloth, Knit and Hair Frictional Contact, Chenfanfu Jiang, Theodore Gast, Joseph Teran. Both projects are based on MPM.
The technique is now extended much beyond simulating single granular material (snow or sand) as known in the past. The first paper presents an easy approach for simulating multi-species mixture of materials that is particularly important in describing continuum porous media. The second paper shows how physical elastoplastic consitutive modeling with MPM can help us automatically handle arbitrarily complex friction contacting scenarios in cloth, knit, and hair simulations, without the explicit need of implementing any collision detection or treatment.
讲者简介：
蒋陈凡夫，2017年6月起于宾夕法尼亚大学计算机与信息科学系任助理教授。2010年毕业于中国科学技术大学少年班物理专业。2015年于UCLA获得计算机博士学位（授予工程学院Edward K. Rice Outstanding Doctoral Student奖）。2015年至2017年5月于UCLA数学系任博士后。主要研究方向是计算固体和流体力学的偏微分方程数值解，计算机图形学中基于物理的自然现象和固体液体的模型与仿真，弹性塑性力学，有限元法和物质点法，医学虚拟手术仿真等。曾与迪士尼，梦工厂等工作室合作开发用于最新电影如Zootopia，Moana的固流体解算器。个人主页：http://www.seas.upenn.edu/~cffjiang
直播链接：http://webinar.games-cn.org
