The value of continuity: Refined isogeometric analysis and fast direct solvers

Daniel Garcia, David Pardo, Lisandro Dalcin, Maciej Paszyński, Nathan Collier, Victor M. Calo

Research output: Contribution to journalArticlepeer-review

28 Scopus citations

Abstract

We propose the use of highly continuous finite element spaces interconnected with low continuity hyperplanes to maximize the performance of direct solvers. Starting from a highly continuous Isogeometric Analysis (IGA) discretization, we introduce . C0-separators to reduce the interconnection between degrees of freedom in the mesh. By doing so, both the solution time and best approximation errors are simultaneously improved. We call the resulting method
Original languageEnglish (US)
Pages (from-to)586-605
Number of pages20
JournalComputer Methods in Applied Mechanics and Engineering
Volume316
DOIs
StatePublished - Aug 26 2016

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: David Pardo and Daniel Garcia have received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie Grant Agreement No. 644602, the Projects of the Spanish Ministry of Economy and Competitiveness with reference MTM2013-40824-P and MTM2016-76329-R, the BCAM Severo Ochoa accreditation of excellence SEV-2013-0323, and the Basque Government through the BERC 2014–2017 program, the Consolidated Research Group Grant IT649-13 on “Mathematical Modeling, Simulation, and Industrial Applications (M2SI)”, and the ICERMAR Project KK-2015/0000097. The work of Maciej Paszyński has been supported by National Science Centre, Poland, Grant No. DEC-2015/17/B/ST6/01867. This publication was made possible in part by a National Priorities Research Program grant 7-1482-1-278 from the Qatar National Research Fund (a member of The Qatar Foundation) and the Center for Numerical Porous Media at King Abdullah University of Science and Technology (KAUST). The J. Tinsley Oden Faculty Fellowship Research Program at the Institute for Computational Engineering and Sciences (ICES) of the University of Texas at Austin has partially supported the visits of VMC to ICES. The authors acknowledge the Texas Advance Computing Center (TACC) at The University of Texas at Austin for providing HPC resources that have contributed to the research results reported in the paper.

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