2021
DOI: 10.1090/mcom/3667
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β„Žπ‘-version discontinuous Galerkin methods on essentially arbitrarily-shaped elements

Abstract: We extend the applicability of the popular interior-penalty discontinuous Galerkin (dG) method discretizing advection-diffusion-reaction problems to meshes comprising extremely general, essentially arbitrarily-shaped element shapes. In particular, our analysis allows for curved element shapes, without the use of non-linear elemental maps. The feasibility of the method relies on the definition of a suitable choice of the discontinuity penalization, which turns out to be explicitly dependent on the particular el… Show more

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Cited by 22 publications
(14 citation statements)
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“…Inserting the previous bounds into (35) and taking the maximum over t ∈ [0, T ], yields the assertion.…”
Section: Stability and Convergence Resultsmentioning
confidence: 88%
See 2 more Smart Citations
“…Inserting the previous bounds into (35) and taking the maximum over t ∈ [0, T ], yields the assertion.…”
Section: Stability and Convergence Resultsmentioning
confidence: 88%
“…Ξ© p corresponds to the quantity defined in (32). Therefore, to conclude it only remains to bound the right-hand side of (35). To do so, we apply the Cauchy-Schwarz and Young inequalities to infer…”
Section: Stability and Convergence Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…Remark 3.2. Following the recent approach of [24], it is possible to prove the inverse estimates in Lemmata 3.1 and 3.6 using assumptions milder than Assumptions 3.1 and 3.2. Notably, the theory therein presented covers very general geometries, including C 1 -curved faces and possibly the presence of arbitrary number of faces.…”
Section: Generalized Inf-sup Conditionmentioning
confidence: 99%
“…To the best of our knowledge, Assumption 2.1 allows for the most general polytopic meshes for which a posteriori error bounds are proven, for any Galerkin discretization and for any PDE problem. Nevertheless, it is, perhaps inevitably, more restrictive compared to the respective ones required for stability and a priori error analysis of dG methods; see [9], [10, Section 4] and [8], for details. The key advantage of the present setting is that it allows us to be as explicit as possible in the constants involved in the a posteriori error bounds.…”
mentioning
confidence: 99%