【GAMES Webinar 2024-348期】
模拟与动画专题
面向复杂仿真的对偶粒子机制与蒙特卡洛方法
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报告题目
A dual-particle approach for incompressible SPH fluids
报告嘉宾
刘树森
中国科学院 · 软件研究所
(人机交互技术与智能信息处理实验室)
报告时间
2024年11月15号 早上10:00-10:25（北京时间）
报告方式
GAMES直播间: https://live.bilibili.com/h5/24617282
报告摘要
Tensile instability is one of the major obstacles to particle methods in fluid simulation, which would cause particles to clump in pairs under tension and prevent fluid simulation to generate small-scale thin features. To address this issue, previous particle methods either use a background pressure or a finite difference scheme to alleviate the particle clustering artifacts, yet still fail to produce small-scale thin features in free-surface flows. In this article, we propose a dual-particle approach for simulating incompressible fluids. Our approach involves incorporating supplementary virtual particles designed to capture and store particle pressures. These pressure samples undergo systematic redistribution at each time step, grounded in the initial positions of the fluid particles. By doing so, we effectively reduce. tensile instability in standard SPH by narrowing down the unstable regions for particles experiencing tensile stress. As a result, we can accurately simulate free-surface flows with rich small-scale thin features, such as droplets, streamlines, and sheets, as demonstrated by experimental results.
嘉宾简介
刘树森，博士毕业于中国科学院大学、中国科学院软件研究所，目前为中国科学院软件研究所特别研究助理（博士后），主要研究方向为计算机图形学、物理仿真等。
个人主页
https://dreliveam.github.io/
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报告题目
A Differential Monte Carlo Solver For the Poisson Equation
报告嘉宾
于子涵
University of California, Irvine
报告时间
2024年11月15号 早上10:20-10:45（北京时间）
报告方式
GAMES直播间: https://live.bilibili.com/h5/24617282
报告摘要
The Poisson equation is an important partial differential equation (PDE) with numerous applications in physics, engineering, and computer graphics. Conventional solutions to the Poisson equation require discretizing the domain or its boundary, which can be very expensive for domains with detailed geometries. To overcome this challenge, a family of grid-free Monte Carlo solutions has recently been developed. By utilizing walk-on-sphere (WoS) processes, these techniques are capable of efficiently solving the Poisson equation over complex domains.
In this paper, we introduce a general technique that differentiates solutions to the Poisson equation with Dirichlet boundary conditions. Specifically, we devise a new boundary-integral formulation for the derivatives with respect to arbitrary parameters including shapes of the domain. Further, we develop an efficient walk-on-spheres technique based on our new formulation---including a new approach to estimate normal derivatives of the solution field. We demonstrate the effectiveness of our technique over baseline methods using several synthetic examples.
嘉宾简介
Zihan Yu is a fifth-year Ph.D. candidate in the School of Information and Computer Science at the University of California, Irvine, advised by Shuang Zhao. His research focuses on physics-based differentiable rendering and simulations using Monte Carlo method, with the goal of developing efficient solutions for inverse problems involving complex geometries to infer material or geometric properties from physical or simulated measurements.
个人主页
https://zihan.me/
主持人简介
王笑琨
北京科技大学
王笑琨，北京科技大学智能科学与技术学院副教授，英国计算机动画中心Marie-Curie Fellow，入选欧盟玛丽居里学者、北科青年学者、北京科协青年人才托举工程。CCF计算机辅助设计与图形学专委会、人机交互专委会，CAAI智慧医疗专委会，CSIG人机交互专委会等委员。主要研究方向包括图形与虚拟现实，智能交互与仿真等，在SIGGRAPH Asia、IEEE VR、EG、SCA、CGF、IJCAI等主流期刊会议上发表论文40余篇。曾获CGI2020最佳论文，CCF CAD & CG2022最佳学生论文，CASA 2022 AniNex最佳论文，中国黄金协会科技进步一等奖，中国电子学会科技进步二等奖等。主持国家科技重大专项课题、国家自然科学基金青年/面上、国家高端外国专家等项目10余项。
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