628 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- State Key Laboratory Breeding Base of Mountain Bridge and Tunnel EngineeringCN11 papers
- Institute of Theoretical PhysicsCN10 papers
- Nanjing Normal UniversityCN10 papers
- Nanjing UniversityCN10 papers
- Beijing Normal UniversityCN8 papers
- China West Normal UniversityCN8 papers
- Chinese Academy of SciencesCN8 papers
- Sichuan UniversityCN6 papers
- Beihang UniversityCN5 papers
- Chongqing UniversityCN5 papers
- National Space Science CenterCN5 papers
- Beijing Computational Science Research CenterCN4 papers
5 papers · 1 filter
Robust residual-based a posteriori error estimators for mixed finite element methods for fourth order elliptic singularly perturbed problems
Shaohong Du, Runchang Lin, Zhimin Zhang
We consider mixed finite element approximation of a singularly perturbed fourth-order elliptic problem with two different boundary conditions, and present a new measure of the erro…
Robust recovery-type a posteriori error estimators for streamline upwind/Petrov Galerkin discretizations for singularly perturbed problems
Shaohong Du, Runchang Lin, Zhimin Zhang
In this paper, we investigate adaptive streamline upwind/Petrov Galerkin (SUPG) methods for singularly perturbed convection-diffusion-reaction equations in a new dual norm presente…
Convergence of adaptive mixed finite element method for convection-diffusion-reaction equations
Shaohong Du, Xiaoping Xie
We prove the convergence of an adaptive mixed finite element method (AMFEM) for (nonsymmetric) convection-diffusion-reaction equations. The convergence result holds from the cases…
Residual-based a posteriori error estimation for multipoint flux mixed finite element methods
Shaohong Du, Shuyu Sun, Xiaoping Xie
A novel residual-type {\it a posteriori} error analysis technique is developed for multipoint flux mixed finite element methods for flow in porous media in two or three space dimen…
Quasi-optimal convergence rate for adaptive mixed finite element methods
Shaohong Du, Xiaoping Xie
For adaptive mixed finite element methods (AMFEM), we first introduce the data oscillation to analyze, without the restriction that the inverse of the coefficient matrix of the par…