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We propose a hybrid neural network and physics framework for reduced-order modeling of elastoplasticity and fracture.
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A Material Point Method for Elastoplasticity with Ductile Fracture and Frictional Contact
Stephanie Wang. 2020 · 2020
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Ming Gao, Xinlei Wang, Kui Wu, Andre Pradhana, Eftychios Sifakis, Cem Yuksel, and Chenfanfu Jiang. 2018 · 2018
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Hybrid grains: Adaptive coupling of discrete and continuum simulations of granular media
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Zhiqin Chen and Hao Zhang. 2019 · 2019
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Silly rubber: an implicit material point method for simulating non-equilibrated viscoelastic and elastoplastic solids
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Hierarchical optimization time integration for cfl-rate mpm stepping
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A massively parallel and scalable multi-GPU material point method
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High-Order Differentiable Autoencoder for Nonlinear Model Reduction
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Neural Fields in Visual Computing and Beyond
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Implicit Neural Spatial Representations for Time-dependent PDEs
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Model reduction for the material point method via an implicit neural representation of the deformation map
Peter Yichen Chen, Maurizio M Chiaramonte, Eitan Grinspun, and Kevin Carlberg. 2023a · 2023
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Neural Implicit Flow: a mesh-agnostic dimensionality reduction paradigm of spatio-temporal data
Shaowu Pan, Steven L Brunton, and J Nathan Kutz. 2023 · 2023
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A Sparse Distributed Gigascale Resolution Material Point Method
Yuxing Qiu, Samuel Temple Reeve, Minchen Li, Yin Yang, Stuart Ryan Slattery, and Chenfanfu Jiang. 2023 · 2023
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Data-Free Learning of Reduced-Order Kinematics
Nicholas Sharp, Cristian Romero, Alec Jacobson, Etienne Vouga, Paul G Kry, David IW Levin, and Justin Solomon. 2023 · 2023
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