Author Archives: christopherbatty

Peizhuo Li, Tuanfeng Y. Wang, Timur Levent Kesdogan, Duygu Ceylan, Olga Sorkine-Hornung Data driven and learning based solutions for modeling dynamic garments have significantly advanced, especially in the context of digital humans. However, existing approaches often focus on modeling garments … Continue reading →

Xingyu Ye, Xiaokun Wang, Yanrui Xu, Jirí Kosinka, Alexandru C. Telea, Lihua You, Jian Jun Zhang, Jian Chang For vortex particle methods relying on SPH-based simulations, the direct approach of iterating all fluid particles to capture velocity from vorticity can … Continue reading →

Sergio Sancho, Jingwei Tang, Christopher Batty, Vinicius Azevedo An ongoing challenge in fluid animation is the faithful preservation of vortical details, which impacts the visual depiction of flows. We propose the Impulse Particle-In-Cell (IPIC) method, a novel extension of the … Continue reading →

Ryan S. Zesch, Vismay Modi, Shinjiro Sueda, David I.W. Levin We present neural collision fields as an alternative to contact point sampling in physics simulations. Our approach is built on top of a novel smoothed integral formulation for the contact … Continue reading →

Mitsuki Hamamichi, Kentaro Nagasawa, Masato Okada, Ryohei Seto, Yonghao Yue We estimate the three Herschel–Bulkley parameters (yield stress, power-law index, and consistency parameter) for shear-dependent fluid-like materials possibly with large-scale inclusions, for which rheometers may fail to provide a useful … Continue reading →

Otman Benchekroun, Ty Trusty, Eitan Grinspun, Danny M. Kaufman, David I.W. Levin Real-time elastodynamic solvers are well-suited for the rapid simulation of homogeneous elastic materials, with high-rates generally enabled by aggressive early termination of timestep solves. Unfortunately, the introduction of … Continue reading →

Doug L. James, David I.W. Levin Motion control of large-scale, multibody physics animations with contact is difficult. Existing approaches, such as those based on optimization, are computationally daunting, and, as the number of interacting objects increases, can fail to find … Continue reading →

Kinfung Chu, Jiawei Huang, Hidemasa Takan, Yoshifumi Kitamura We present a framework that captures sparse Lagrangian flow information from a volume of real liquid and reconstructs its detailed kinematic information in real time. Our framework can perform flow reconstruction even … Continue reading →

Jiayi Eris Zhang, Jérémie Dumas, Yun (Raymond) Fei, Alec Jacobson, Doug L. James, Danny M. Kaufman Thin shell structures exhibit complex behaviors critical for modeling and design across wide-ranging applications. Capturing their mechanical response requires finely detailed, high-resolution meshes. Corresponding … Continue reading →