3 papers
math.NA2020
Two-level a posteriori error estimation for adaptive multilevel stochastic Galerkin FEM
Alex Bespalov, Dirk Praetorius, Michele Ruggeri
The paper considers a class of parametric elliptic partial differential equations (PDEs), where the coefficients and the right-hand side function depend on infinitely many (uncerta…
math.NA2019
T-IFISS: a toolbox for adaptive FEM computation
Alex Bespalov, Leonardo Rocchi, David Silvester
T-IFISS is a finite element software package for studying finite element solution algorithms for deterministic and parametric elliptic partial differential equations. The emphasis…
math.NA2019
A posteriori error estimation and adaptivity in stochastic Galerkin FEM for parametric elliptic PDEs: beyond the affine case
Alex Bespalov, Feng Xu
We consider a linear elliptic partial differential equation (PDE) with a generic uniformly bounded parametric coefficient. The solution to this PDE problem is approximated in the f…