A Double-Adaptivity Solver for Parabolic PDEs
Gregor Gantner, Robin Smeets, Rob Stevenson
Abstract
We study minimal residual space-time finite element discretizations of linear parabolic initial value problems in canonical space-time variational form. To deal with the arising dual norm, we introduce the Riesz lift of the residual as an additional variable. Quasi-optimality of the primal variable of the mixed system follows from a uniform inf-sup condition. This condition is known to be satisfied for finite element spaces w.r.t. prismatic partitions of the space-time cylinder that allow for a decomposition into time-slabs. We prove that this condition cannot be expected to hold otherwise. To recover stability for general partitions and the data at hand, we derive an a posteriori condition on the error between the exact Riesz lift of the residual and its Galerkin approximation -- being the secondary variable of our system -- under which the primal variable is quasi-optimal. We derive a posteriori error estimators for both variables, and use them in a double-adaptive loop that alternates test-space with trial-space enrichment. We illustrate our findings with numerical experiments in 1+1 and 2+1 dimensions.
Create a lesson
Related papers
Continuous data assimilation in steady Navier-Stokes equations with unknown viscosity: robust and efficient solvers and fast parameter recovery
L. Rebholz, J. Reyes, J. Whitehead
Neural operators approximate strongly continuous convex monotone semigroups
Jonas Blessing, Philipp Schmocker, Alessandro Sgarabottolo
A stable rank-adaptive step-and-truncate finite volume method for Vlasov transport on domains with piecewise linear boundaries
André Uschmajew, Andreas Zeiser
Positivity loss in bandlimited spectral reproduction on spheres
Hao-Ning Wu
Computational study of Proper Orthogonal Decomposition methods for parametric approximations
Bosco García-Archilla, Alicia García-Mascaraque, Julia Novo
Reduced order model for parametric Boltzmann equation and its application to inverse problems
Shanyin Tong, Jingwei Hu, Fengyan Li et al.