Quoc-Minh Ton-That, Paul G. Kry, Sheldon Andrews Traditional mesh-based methods for cutting deformable bodies rely on modifying the simulation mesh by deleting, duplicating, deforming or subdividing its elements. Unfortunately, such topological changes eventually lead to instability, reduced accuracy, or computational efficiency challenges. Hence, state of the art algorithms favor the extended finite element method (XFEM), […]

Yalan Zhang, Long Shen, Yanrui Xu, and Xiaokun Wang, Chao Yao, Jiri Kosinka, Alexandru Telea, Steffen Frey, Xiaojuan Ban We propose a method for simulating viscoelastic non-Newtonian fluids within a multiphase framework. For this, we use mixture models to handle component transport and conformation tensor methods to handle the fluid’s viscoelastic stresses. In addition, we consider a […]

Fabian Löschner, José Antonio Fernández-Fernández, Stefan Rhys Jeske, Jan Bender Continuum-based shell models are an established approach for the simulation of thin deformables in computer graphics. However, existing research in physically-based animation is mostly focused on shear-rigid Kirchhoff-Love shells. In this work we explore three-director Cosserat (micropolar) shells which introduce additional rotational degrees of freedom. […]

Xuan Li, Minchen Li, Xuchen Han, Huamin Wang, Yin Yang, Chenfanfu Jiang This paper presents a novel method to couple Finite Element Methods (FEM), typically employed for modeling Lagrangian solids such as flesh, cloth, hair, and rigid bodies, with Material Point Methods (MPM), which are well-suited for simulating materials undergoing substantial deformation and topology change, […]

Xing Shen, Runyuan Cai, Mengxiao Bi Tangjie Lv The linear conjugate gradient method is widely used in physical simulation, particularly for solving large-scale linear systems derived from Newton’s method. The nonlinear conjugate gradient method generalizes the conjugate gradient method to nonlinear optimization, which is extensively utilized in solving practical large-scale unconstrained optimization problems. However, it […]

Yushan Han, Yizhou Chen, Carmichael Ong, Jingyu Chen, Jennifer Hicks, Joseph Teran We present a comprehensive neural network to model the deformation of human soft tissues including muscle, tendon, fat and skin. Our approach provides kinematic and active correctives to linear blend skinning [Magnenat-Thalmann et al. 1989] that enhance the realism of soft tissue deformation […]

Marcelo Martins, Lucas Morais, Rafael Torchelsen, Luciana Nedel, Anderson Maciel Current endoscopy simulators oversimplify navigation and interaction within tubular anatomical structures to maintain interactive frame rates, neglecting the intricate dynamics of permanent contact between the organ and the medical tool. Traditional algorithms fail to represent the complexities of long, slender, deformable tools like endoscopes and […]

Vismay Modi, Nicholas Sharp, Or Perel, Shinjiro Sueda, David I. W. Levin The proliferation of 3D representations, from explicit meshes to implicit neural fields and more, motivates the need for simulators agnostic to representation. We present a data-, mesh-, and grid-free solution for elastic simulation for any object in any geometric representation undergoing large, nonlinear […]

Yizhou Chen, Yushan Han, Jingyu Chen, Zhan Zhang, Alex Mcadams, Joseph Teran Position based dynamics [Müller et al. 2007] is a powerful technique for simulating a variety of materials. Its primary strength is its robustness when run with limited computational budget. Even though PBD is based on the projection of static constraints, it does not […]