38 citations · 53 across the 11 of their papers we have counts for
5 papers · 1 filter
An E-PINN assisted practical uncertainty quantification for inverse problems
Xinchao Jiang, Xin Wanga, Ziming Wena +2
How to solve inverse problems is the challenge of many engineering and industrial applications. Recently, physics-informed neural networks (PINNs) have emerged as a powerful approa…
A Physics-Data-Driven Bayesian Method for Heat Conduction Problems
Xinchao Jiang, Hu Wang, Yu li
In this study, a novel physics-data-driven Bayesian method named Heat Conduction Equation assisted Bayesian Neural Network (HCE-BNN) is proposed. The HCE-BNN is constructed based o…
A multi-grid sampling multi-scale method for crack initiation and propagation
Zhenxing Cheng, Hu Wang
In this study, a multi-grid sampling multi-scale (MGSMS) method is proposed by coupling with finite element (FEM), extended finite element (XFEM) and molecular dynamics (MD) method…
Fatigue crack propagation in carbon steel using RVE based model
Zhenxing Cheng, Hu Wang, Gui-Rong Liu
A representative volume element (RVE) based multi-scale method is proposed to investigate the mechanism of fatigue crack propagation by the molecular dynamics (MD) and the extended…
Machine Learning based parameter tuning strategy for MMC based topology optimization
Xinchao Jiang, Hu Wang, Yu Li +1
Moving Morphable Component (MMC) based topology optimization approach is an explicit algorithm since the boundary of the entity explicitly described by its functions. Compared with…