236 citations · 724 across the 10 of their papers we have counts for
11 papers
Geometry-informed neural atlas for boundary value problems of complex 3D geometries
WaiChing Sun
When three-dimensional bodies contain thin features, non-trivial topology, or scan-derived surfaces, volumetric meshing can become the dominant bottleneck in simulation workflows.…
An accelerated hybrid data-driven/model-based approach for poroelasticity problems with multi-fidelity multi-physics data
Bahador Bahmani, WaiChing Sun
We present a hybrid model/model-free data-driven approach to solve poroelasticity problems. Extending the data-driven modeling framework originated from Kirchdoerfer and Ortiz (201…
Sobolev training of thermodynamic-informed neural networks for smoothed elasto-plasticity models with level set hardening
Nikolaos N. Vlassis, WaiChing Sun
We introduce a deep learning framework designed to train smoothed elastoplasticity models with interpretable components, such as a smoothed stored elastic energy function, a yield…
De Giorgi argument for weighted solutions to the non-cutoff Boltzmann equation
R. Alonso, Y. Morimoto, W. Sun +1
This paper gives the first affirmative answer to the question of the global existence of Boltzmann equations without angular cutoff in the -setting. In particular, we sho…
A non-cooperative meta-modeling game for automated third-party calibrating, validating, and falsifying constitutive laws with parallelized adversarial attacks
Kun Wang, WaiChing Sun, Qiang Du
The evaluation of constitutive models, especially for high-risk and high-regret engineering applications, requires efficient and rigorous third-party calibration, validation and fa…
Geometric deep learning for computational mechanics Part I: Anisotropic Hyperelasticity
Nikolaos Vlassis, Ran Ma, WaiChing Sun
This paper is the first attempt to use geometric deep learning and Sobolev training to incorporate non-Euclidean microstructural data such that anisotropic hyperelastic material ma…
ILS-MPM: an implicit level-set-based material point method for frictional particulate contact mechanics of deformable particles
Chuanqi Liu, Waiching Sun
Finite element simulations of frictional multi-body contact problems via conformal meshes can be challenging and computationally demanding. To render geometrical features, unstruct…
A phase field model for cohesive fracture in micropolar continua
Hyoung Suk Suh, WaiChing Sun, Devin O'Connor
While crack nucleation and propagation in the brittle or quasi-brittle regime can be predicted via variational or material-force-based phase field fracture models, these models oft…
A cooperative game for automated learning of elasto-plasticity knowledge graphs and models with AI-guided experimentation
Kun Wang, WaiChing Sun, Qiang Du
We introduce a multi-agent meta-modeling game to generate data, knowledge, and models that make predictions on constitutive responses of elasto-plastic materials. We introduce a ne…
Stress-induced anisotropy in granular materials: fabric, stiffness, and permeability
Matthew R. Kuhn, WaiChing Sun, Qi Wang
The loading of a granular material induces anisotropies of the particle arrangement (fabric) and of the material's strength, incremental stiffness, and permeability. Thirteen measu…
Meta-modeling game for deriving theoretical-consistent, micro-structural-based traction-separation laws via deep reinforcement learning
Kun Wang, WaiChing Sun
This paper presents a new meta-modeling framework to employ deep reinforcement learning (DRL) to generate mechanical constitutive models for interfaces. The constitutive models are…