Adaptive quasi-Monte Carlo finite element methods for parametric elliptic PDEs

M Longo - Journal of Scientific Computing, 2022 - Springer
We introduce novel adaptive methods to approximate moments of solutions of partial
differential Equations (PDEs) with uncertain parametric inputs. A typical problem in …

Adaptive Computation of an Elliptic Eigenvalue Optimization Problem with a Phase-Field Approach

J Li, Y Xu, S Zhu - arXiv preprint arXiv:2310.03970, 2023 - arxiv.org
In this paper, we discuss adaptive approximations of an elliptic eigenvalue optimization
problem in a phase-field setting by a conforming finite element method. An adaptive …

A posteriori error estimation for finite element approximations of fractional Laplacian problems and applications to poro–elasticity

R Bulle - 2022 - orbilu.uni.lu
This manuscript is concerned with a posteriori error estimation for the finite element
discretization of standard and fractional partial differential equations as well as an …

[HTML][HTML] Plain convergence of goal-oriented adaptive FEM

V Helml, M Innerberger, D Praetorius - Computers & Mathematics with …, 2023 - Elsevier
We discuss goal-oriented adaptivity in the frame of conforming finite element methods and
plain convergence of the related a posteriori error estimator for different general marking …

Gradient method with AFEM for parameter-estimation

R Becker - Selecciones Matemáticas, 2023 - revistas.unitru.edu.pe
We consider the adaptive finite element discretization of parameter estimation problems for
nonlinear elliptic partial differential equations. The idea is to use a gradient method on the …

[HTML][HTML] Space-Time Finite Element Methods/Author Dipl.-Ing. Andreas Schafelner

A Schafelner - 2021 - epub.jku.at
We derive space-time finite element methods for parabolic evolution problems on
completely unstructured decompositions of the space-time cylinder $ Q\subset\mathbb …

[PDF][PDF] Adaptive algorithms with a-posteriori Quasi-Monte Carlo estimation for parametric elliptic PDEs

M Longo - SAM Research Report, 2021 - sam.math.ethz.ch
We introduce novel adaptive methods to approximate Partial Differential Equations (PDEs)
with uncertain parametric inputs. A typical problem in Uncertainty Quantification is the …