1 citations · 1 across the 2 of their papers we have counts for
3 papers
physics.comp-ph2025
Towards Unified AI-Driven Fracture Mechanics: The Extended Deep Energy Method (XDEM)
Yizheng Wang, Yuzhou Lin, Somdatta Goswami +8
Physics-Informed Neural Networks (PINNs) have recently emerged as powerful tools for solving partial differential equations (PDEs), with the Deep Energy Method (DEM) proving especi…
physics.comp-ph2025
LENNs: Locally Enhanced Neural Networks for High-Fidelity Modeling in Solid Mechanics
Zhihong Lai, Luyang Zhao, Qian Shao
Despite prior advances in PINNs, significant challenges remain in localized solid mechanics problems because of the limitations of single network formulations in simultaneous resol…
cs.CE2024★ 1 cited
DEDEM: Discontinuity Embedded Deep Energy Method for solving fracture mechanics problems
Luyang Zhao, Qian Shao
Physics-Informed Neural Networks (PINNs) have aroused great attention for its ability to address forward and inverse problems of partial differential equations. However, approximat…