10 citations · 16 across the 3 of their papers we have counts for
3 papers
cs.CE2023★ 4 cited
A novel solution for seepage problems using physics-informed neural networks
Tianfu Luo, Yelin Feng, Qingfu Huang +5
A Physics-Informed Neural Network (PINN) provides a distinct advantage by synergizing neural networks' capabilities with the problem's governing physical laws. In this study, we in…
math.NA2021★ 10 cited
A novel method in solving seepage problems implementation in Abaqus based on the polygonal scaled boundary finite element method
Yang Yang, Zongliang Zhang, Yelin Feng
The scaled boundary finite element method (SBFEM) is a semi-analytical computational scheme, which is based on the characteristics of the finite element method (FEM) and combines t…
math.NA2021★ 2 cited
A polygonal scaled boundary finite element method for solving heat conduction problems
Yang Yang, Zongliang Zhang, Yelin Feng +3
This paper presents a steady-state and transient heat conduction analysis framework using the polygonal scaled boundary finite element method (PSBFEM) with polygon/quadtree meshes.…