GAMES Webinar 2023 – 298期(共维模型下的物理仿真) | 武奎(腾讯光子工作室), Yunuo Chen(University of California, Los Angeles)

【GAMES Webinar 2023-298期】(模拟与动画专题-共维模型下的物理仿真)

报告嘉宾：武奎(腾讯光子工作室)

报告时间：2023年11月2号星期四早上10:00-10:40（北京时间）

报告题目：Sag-Free Initialization for Strand-Based Hybrid Hair Simulation

报告摘要：

Initializing simulations of deformable objects involves setting the rest state of all internal forces at the rest shape of the object. However, often times the rest shape is not explicitly provided. In its absence, it is common to initialize by treating the given initial shape as the rest shape. This leads to sagging, the undesirable deformation under gravity as soon as the simulation begins.

In this talk, we will introduce a novel solution to the sagging problem that can be applied to a variety of simulation systems and materials. The key feature of our approach is that we avoid solving a global nonlinear optimization problem by performing the initialization in multiple stages, including global linear stages for static equilibrium and local stages, which solves many small local problems efficiently in parallel. We show that our approach can be applied to various simulation systems, such as mass-spring systems, FEM, MPM, cloth, and hairs, with contacts. Our results show that our method successfully prevents sagging and has minimal impact on the motion during runtime.

讲者简介：

Kui Wu is a principal research scientist in LightSpeed Studios, Tencent America. Previously, he was a postdoctoral associate in the Computational Design & Fabrication Group under the guidance of Prof. Wojciech Matusik at MIT CSAIL. He received my PhD degree in Computer Science from University of Utah in 2019, advised by Prof. Cem Yuksel. His research interests are computer graphics, especially on mesh processing, knitting, real-time rendering, and physical-based simulation. He received 2019 University of Utah SoC Outstanding Dissertation Award and 2023 Symposium on Computer Animation (SCA) Early Career Researcher Award.

讲者主页：https://kuiwuchn.github.io/

报告嘉宾：Yunuo Chen(University of California, Los Angeles)

报告时间：2023年11月2号星期四早上10:40-11:10（北京时间）

报告题目：Multi-Layer Thick Shells

报告摘要：

In this presentation, I will introduce our recent work, which aims to simulate the intricate dynamics of continuum thick shells. To accurately represent the constitutive behavior of structural responses in the thickness direction, we have developed a dual-quadrature prism finite element formulation that is free from shear locking and naturally incorporates three-dimensional elastoplastic and viscoelastic constitutive models. Additionally, we have introduced a simple and effective technique for coupling a high-resolution membrane layer on top of the thick shell, enabling complementary high-frequency deformation modes that produce realistic wrinkles. Our approach opens up new possibilities for fast, high-quality simulations that take into account the thickness of materials, such as leather garments, pillows, mats, metal boards, and potentially various other thick structures.

讲者简介：

Yunuo is a third year PhD student at the Department of Mathematics, University of California, Los Angeles (UCLA). He is currently working under the supervision of Prof. Chenfanfu Jiang. His research interests include scientific computation and its application in graphics, especially physics-based animation.

讲者主页：https://yunuoch.github.io/

主持人简介：

Yin Yang is currently an Associate Professor with the Kahlert School of Computing at University of Utah. Before joining Clemson, he was a faculty member at University of New Mexico and Clemson University. He received Ph.D. degree of Computer Science from The University of Texas, Dallas in 2013 (the awardee of David Daniel Fellowship Prize). He was a Research/Teaching Assistant at UT Dallas as well as UT Southwestern Medical Center.

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