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 for garment dynamic super-resolution, designed to efficiently enhance high-resolution, high-frequency details in low-resolution garment simulations. […]

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 anisotropic energy that is low-order and yet sufficiently non-linear remains a challenging problem for achieving […]

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 present neural implicit reduced fluid simulation (NIRFS), a reduced fluid simulation technique that combines an […]

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 (FEM), we build MiNNIE upon a mixed FEM framework and further incorporate a pressure stabilization […]

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 Cubic Barrier with Elasticity-Inclusive Dynamic Stiffness

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 first time, we show that Newton’s method, Projected Newton with eigenvalue clamping and Projected Newton […]

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 as more concise subspaces can be detected. However, the complexity and landscape of simulation objectives […]

Ty Trusty, Yun (Raymond) Fei, David I.W. Levin, Danny M. Kaufman We construct a subspace simulator that adaptively balances solution improvement against system size. The core components of our simulator are an adaptive subspace oracle, model, and parallel time-step solver algorithm. Our in-time-step adaptivity oracle continually assesses subspace solution quality and candidate update proposals while […]

Xingyu Ni*, Xuwen Chen* (joint 1st authors), Cheng Yu, Bin Wang, Baoquan Chen In this study, we present the bicubic Hermite element method (BHEM), a new computational framework devised for the elastodynamic simulation of thin-shell structures. The BHEM is constructed based on quadrilateral Hermite patches, which serve as a unified representation for shell geometry, simulation, […]

Xuwen Chen, Cheng Yu, Xingyu Ni, Mengyu Chu, Bin Wang, Baoquan Chen Continuous collision detection (CCD) between parametric surfaces is typically formulated as a five-dimensional constrained optimization problem. In the field of CAD and computer graphics, common approaches to solving this problem rely on linearization or sampling strategies. Alternatively,inclusion-based techniques detect collisions by employing 5D […]