Cited By
View all- Park HGrama Srinivasan SCong MKim DKim BSwartz JMuseth KSifakis E(2024)Near-realtime Facial Animation by Deep 3D Simulation Super-ResolutionACM Transactions on Graphics10.1145/367068743:5(1-20)Online publication date: 9-Aug-2024
Neural Stress Fields for Reduced-order Elastoplasticity and Fracture
Authors: 
Zeshun Zong, Xuan Li, Minchen Li, Maurizio M. Chiaramonte, 
Wojciech Matusik, Eitan Grinspun, Kevin Carlberg, 
Chenfanfu Jiang, Peter Yichen ChenAuthors Info & Claims
Zeshun Zong, Xuan Li, Minchen Li, Maurizio M. Chiaramonte, Wojciech Matusik, Eitan Grinspun, Kevin Carlberg, Chenfanfu Jiang, Peter Yichen ChenAuthors Info & ClaimsArticle No.: 78, Pages 1 - 11
Abstract
We propose a hybrid neural network and physics framework for reduced-order modeling of elastoplasticity and fracture. State-of-the-art scientific computing models like the Material Point Method (MPM) faithfully simulate large-deformation elastoplasticity and fracture mechanics. However, their long runtime and large memory consumption render them unsuitable for applications constrained by computation time and memory usage, e.g., virtual reality. To overcome these barriers, we propose a reduced-order framework. Our key innovation is training a low-dimensional manifold for the Kirchhoff stress field via an implicit neural representation. This low-dimensional neural stress field (NSF) enables efficient evaluations of stress values and, correspondingly, internal forces at arbitrary spatial locations. In addition, we also train neural deformation and affine fields to build low-dimensional manifolds for the deformation and affine momentum fields. These neural stress, deformation, and affine fields share the same low-dimensional latent space, which uniquely embeds the high-dimensional simulation state. After training, we run new simulations by evolving in this single latent space, which drastically reduces the computation time and memory consumption. Our general continuum-mechanics-based reduced-order framework is applicable to any phenomena governed by the elastodynamics equation. To showcase the versatility of our framework, we simulate a wide range of material behaviors, including elastica, sand, metal, non-Newtonian fluids, fracture, contact, and collision. We demonstrate dimension reduction by up to 100,000 × and time savings by up to 10 ×.
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- Neural Stress Fields for Reduced-order Elastoplasticity and Fracture
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View all- Park HGrama Srinivasan SCong MKim DKim BSwartz JMuseth KSifakis E(2024)Near-realtime Facial Animation by Deep 3D Simulation Super-ResolutionACM Transactions on Graphics10.1145/367068743:5(1-20)Online publication date: 9-Aug-2024
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