3 papers
cs.LG2026
FEM-Informed Hypergraph Neural Networks for Efficient Elastoplasticity
Jianchuan Yang, Xi Chen, Jidong Zhao
Graph neural networks (GNNs) naturally align with sparse operators and unstructured discretizations, making them a promising paradigm for physics-informed machine learning in compu…
math-ph2026
A Virtual Heat Flux Method for Simple and Accurate Neumann Thermal Boundary Imposition in the Material Point Method
Jidu Yu, Jidong Zhao
In the Material Point Method (MPM), accurately imposing Neumann-type thermal boundary conditions, particularly convective heat flux boundaries, remains a significant challenge due…
cond-mat.soft2026
An elasto-viscoplastic thixotropic model for fresh concrete capturing flow-rest transition
Jidu Yu, Bodhinanda Chandra, Christopher Wilkes +2
The flow properties of fresh concrete are critical in the construction industry, as they directly affect casting quality and the durability of the final structure. Although non-New…