3 papers
cs.CE2025
A Physics-Informed Neural Network Framework for Simulating Creep Buckling in Growing Viscoelastic Biological Tissues
Zhongya Lin, Jinshuai Bai, Shuang Li +3
Modeling viscoelastic behavior is crucial in engineering and biomechanics, where materials undergo time-dependent deformations, including stress relaxation, creep buckling and biol…
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…
eess.SY2024
Artificial intelligence for partial differential equations in computational mechanics: A review
Yizheng Wang, Jinshuai Bai, Zhongya Lin +9
In recent years, Artificial intelligence (AI) has become ubiquitous, empowering various fields, especially integrating artificial intelligence and traditional science (AI for Scien…