7 papers
Plasolver: Physics-Informed Neural Operators for Elastoplasticity
Yizheng Wang, Mohammad Sadegh Eshaghi, Huadong Zhang +3
Elastoplastic analysis is computationally demanding because its nonlinear, path-dependent constitutive behavior requires incremental loading and repeated iterative solutions. To ad…
Neural Operators for Immersed-Boundary Soft Swimmers Locomotion
Mohammad Sadegh Eshaghi, Yizheng Wang, Navid Valizadeh +2
High-fidelity immersed-boundary simulation resolves the coupled motion of a deforming swimmer and its surrounding flow, but the resulting cost limits repeated evaluations for engin…
FEVessel: Mesh-Independent Analysis of 3D Pressure Vessels with the Label-Free Pretrained Finite Element Method
Yipin Sun, Yizheng Wang, Yuzhou Lin +3
Pressure vessel analysis in the chemical, nuclear, and new-energy industries requires solving the same elasticity problem across many materials, geometries, and loads, where mesh q…
Dmsh: A Multi-Agent Reinforcement Learning Framework for All-Quad Mesh Generation
Anirudh Kalyan, Cosmin Anitescu, Xiaoying Zhuang +3
Generating high-quality meshes for arbitrary geometries remains a fundamental bottleneck in computational engineering, often demanding heuristic tuning and semi-manual workflows. I…
Replay-Based Continual Learning for Physics-Informed Neural Operators
Yizheng Wang, Mohammad Sadegh Eshaghi, Xiaoying Zhuang +2
Neural operators generally demonstrate strong predictive performance on in-distribution (ID) problems. However, a critical limitation of existing methods is their significant perfo…
A Computational Model for Flexoelectricity-Driven Contact Electrification
Han Hu, Xiaoying Zhuang, Timon Rabczuk
Recent theoretical studies show that nanoscale contact on dielectric substrates can induce flexoelectric polarization large enough to drive electron transfer. This has been support…