Category Archives: Uncategorized

Tetsuya Takahashi, Christopher Batty We propose a new rest shape optimization framework to achieve sag-free simulations of discrete elastic rods. To optimize rest shape parameters, we formulate a minimization problem based on the kinetic energy with a regularizer while imposing … Continue reading →

L. Fan, Floyd M. Chitalu, Taku Komura The hybrid Lagrangian/Eulerian formulation of continuum shells is highly effective for producing challenging simulations of thin materials like cloth with bending resistance and frictional contact. However, existing formulations are restricted to materials that … Continue reading →

Meng Zhang, Jun Li Achieving efficient, high-fidelity, high-resolution garment simulation is challenging due to its computational demands. Conversely, low-resolution garment simulation is more accessible and ideal for low-budget devices like smartphones. In this paper, we introduce a lightweight, learning-based method … Continue reading →

Huancheng Lin, Floyd M. Chitalu, Taku Komura Anisotropic hyperelastic distortion energies are used to solve many problems in fields like computer graphics and engineering with applications in shape analysis, deformation, design, mesh parameterization, biomechanics and more. However, formulating a robust … Continue reading →

Yuanyuan Tao, Ivan Puhachov, Derek Nowrouzezahrai, Paul Kry High-fidelity simulation of fluid dynamics is challenging because of the high dimensional state data needed to capture fine details and the large computational cost associated with advancing the system in time. We … Continue reading →

Liangwang Ruan , Bin Wang, Tiantian Liu, Baoquan Chen We propose MiNNIE, a simple yet comprehensive framework for real-time simulation of nonlinear near-incompressible elastics. To avoid the common volumetric locking issues at high Poisson’s ratios of linear finite element methods … Continue reading →

Ryoichi Ando This paper presents a new cubic barrier with elasticity-inclusive dynamic stiffness for penetration-free contact resolution and strain limiting. We show that our method enlarges tight strain-limiting gaps where logarithmic barriers struggle and enables highly scalable contact-rich simulation. A … Continue reading →

Honglin Chen, Hseuh-Ti Derek Liu, Alec Jacobson, David I. W. Levin, Changxi Zheng We introduce a novel adaptive eigenvalue filtering strategy to stabilize and accelerate the optimization of Neo-Hookean energy and its variants under the Projected Newton framework. For the … Continue reading →

Aoran Lyu, Shixian Zhao, Chuhua Xian, Zhihao Cen, Hongmin Cai, Guoxin Fang Reduced-order simulation is an emerging method for accelerating physical simulations with high DOFs, and recently developed neural-network-based methods with nonlinear subspaces have been proven effective in diverse applications … Continue reading →