Category Archives: Uncategorized

Haoxiang Wang, Kui Wu, Hui Qiao, Mattieu Desbrun, Wei Li Kinetic multiphase flow solvers have recently demonstrated exquisitely complex and turbulent fluid phenomena involving splashing and bubbling. However, they require full simulation of both the liquid phase and the air … Continue reading →

Zhiqi Li, Jinjin He, Barnabás Börcsök, Taiyuan Zhang, Duowen Chen, Tao Du, Ming C. Lin, Greg Turk, Bo Zhu This paper presents a novel adjoint solver for differentiable fluid simulation based on bidirectional flow maps. Our key observation is that … Continue reading →

Xiao Sean Zhan, Evan Thompson, Clément Jambon, Kenney Ng, Mina Konaković Luković Generative models have recently demonstrated impressive capabilities in producing high-quality 3D shapes from a variety of user inputs (e.g., text or images). However, generated objects often lack physical … Continue reading →

Yura Hwang, Jenny Han Lin, Jerry Hsu, Benjamin Mastripolito, James McCann, Cem Yuksel Lightweight, mesh-level models of knit fabric behavior are useful for both interactive pattern editing and initialization of yarn-level simulations. However, existing mesh-level simulation methods abstract knitting as … Continue reading →

J. Andreas Bærentzen, Jonàs Martínez, Jeppe Revall Frisvad, Sylvain Lefebvre We introduce a divergence-free nD vector noise defined as the n-dimensional cross product of the gradients of n − 1 noise functions. We show that this vector noise function is … Continue reading →

Yi-Lu Chen, Mickaël Ly, Chris Wojtan The realistic simulation of sand, soil, powders, rubble piles, and large collections of rigid bodies is a common and important problem in the fields of computer graphics, computational physics, and engineering. Direct simulation of … Continue reading →

Otman Benchekroun, Eitan Grinspun, Maurizio Chiaramonte, Philip Allen Etter Designing subspaces for Reduced Order Modeling (ROM) is crucial for accelerating finite element simulations in graphics and engineering. Unfortunately, it’s not always clear which subspace is optimal for arbitrary dynamic simulation. … Continue reading →

Jie Chen, Zherong Pan, Bo Ren We propose a Reinforcement Learning (RL) algorithm that combines several novel techniques to achieve more stable and robust control results for coupled solid-fluid systems. Our method utilizes the twin-delayed actor-critic algorithm to efficiently utilize … Continue reading →

Zhiyang Dou, Chen Peng, Xinyu Lu, Xiaohan Ye, Lixing Fang, Yuan Liu, Wenping Wang, Chuang Gan, Lingjie Liu, Taku Komura Humans possess the ability to master a wide range of motor skills, enabling them to quickly and flexibly adapt to … Continue reading →

Jiwei Wang, Wenbin Song, Yicheng Fan, Yang Wang, Xiaopei Liu Unmanned aerial vehicles (UAVs) have demonstrated remarkable efficacy across diverse fields. Nevertheless, developing flight controllers tailored to a specific UAV design, particularly in environments with strong fluid-interactive dynamics, remains challenging. … Continue reading →