197 citations · 229 across the 22 of their papers we have counts for
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cs.CE2026
An improved PINN framework integrating localized collocation scheme and PIKF
Qiang Xi, Wenzhi Xu, Mario Cvetkovic +3
We propose a localized physics-informed kernel function neural network (LPIKFNN), which is an improved physics-informed neural network (PINN) based on physics-informed kernel funct…
cs.CE2024
Energy-based physics-informed neural network for frictionless contact problems under large deformation
Jinshuai Bai, Zhongya Lin, Yizheng Wang +5
Numerical methods for contact mechanics are of great importance in engineering applications, enabling the prediction and analysis of complex surface interactions under various cond…
cs.CE2024
A Pretraining-Finetuning Computational Framework for Material Homogenization
Yizheng Wang, Xiang Li, Ziming Yan +5
Homogenization is a fundamental tool for studying multiscale physical phenomena. Traditional numerical homogenization methods, heavily reliant on finite element analysis, demand si…