Inexpensive polynomial-degree-robust equilibrated flux a posteriori estimates for isogeometric analysis
Gregor Gantner, Martin Vohral\'ik

TL;DR
This paper introduces a cost-effective, polynomial-degree-robust a posteriori error estimator for isogeometric analysis of the Poisson problem, utilizing equilibrated fluxes and hierarchical B-splines to enhance efficiency and robustness.
Contribution
It develops a novel, inexpensive equilibrated flux a posteriori error estimator that is robust with respect to polynomial degree and adaptive mesh refinements in isogeometric analysis.
Findings
Estimator is constant-free in the leading term.
Estimator is locally efficient and robust to polynomial degree.
Numerical experiments confirm theoretical robustness and efficiency.
Abstract
We consider isogeometric discretizations of the Poisson model problem, focusing on high polynomial degrees and strong hierarchical refinements. We derive a posteriori error estimates by equilibrated fluxes, i.e., vector-valued mapped piecewise polynomials lying in the space which appropriately approximate the desired divergence constraint. Our estimates are constant-free in the leading term, locally efficient, and robust with respect to the polynomial degree. They are also robust with respect to the number of hanging nodes arising in adaptive mesh refinement employing hierarchical B-splines. Two partitions of unity are designed, one with larger supports corresponding to the mapped splines, and one with small supports corresponding to mapped piecewise multilinear finite element hat basis functions. The equilibration is only performed on the small supports,…
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Taxonomy
TopicsAdvanced Numerical Analysis Techniques
