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Capitalizing on Superconvergence for More Accurate Multi-Resolution Discontinuous Galerkin Methods
Applied Mathematics and Statistics, Colorado School of Mines, Golden, 80401, CO, United States.ORCID iD: 0000-0002-6252-8199
2022 (English)In: Communications on Applied Mathematics and Computation, ISSN 2096-6385, Vol. 4, no 2, p. 417-436Article in journal (Refereed) Published
Abstract [en]

This article focuses on exploiting superconvergence to obtain more accurate multi-resolution analysis. Specifically, we concentrate on enhancing the quality of passing of information between scales by implementing the Smoothness-Increasing Accuracy-Conserving (SIAC) filtering combined with multi-wavelets. This allows for a more accurate approximation when passing information between meshes of different resolutions. Although this article presents the details of the SIAC filter using the standard discontinuous Galerkin method, these techniques are easily extendable to other types of data.

Place, publisher, year, edition, pages
Springer Nature , 2022. Vol. 4, no 2, p. 417-436
Keywords [en]
Accuracy enhancement, Discontinuous Galerkin, Multi-resolution analysis, Multi-wavelets, Post-processing, Smoothness-Increasing Accuracy-Conserving (SIAC), Superconvergence
National Category
Computational Mathematics
Identifiers
URN: urn:nbn:se:kth:diva-334832DOI: 10.1007/s42967-021-00121-wISI: 000672764500002Scopus ID: 2-s2.0-85132107392OAI: oai:DiVA.org:kth-334832DiVA, id: diva2:1791836
Note

QC 20230828

Available from: 2023-08-27 Created: 2023-08-27 Last updated: 2023-08-28Bibliographically approved

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Ryan, Jennifer K.

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