Optimally refined isogeometric analysis

Daniel Garcia, Michael Barton, David Pardo

Research output: Contribution to journalConference articlepeer-review

6 Scopus citations

Abstract

Performance of direct solvers strongly depends upon the employed discretization method. In particular, it is possible to improve the performance of solving Isogeometric Analysis (IGA) discretizations by introducing multiple C°-continuity hyperplanes that act as separators during LU factorization [8]. In here, we further explore this venue by introducing separators of arbitrary continuity. Moreover, we develop an efficient method to obtain optimal discretizations in the sense that they minimize the time employed by the direct solver of linear equations. The search space consists of all possible discretizations obtained by enriching a given IGA mesh. Thus, the best approximation error is always reduced with respect to its IGA counterpart, while the solution time is decreased by up to a factor of 60.

Original languageEnglish (US)
Pages (from-to)808-817
Number of pages10
JournalProcedia Computer Science
Volume108
DOIs
StatePublished - Jan 1 2017
EventInternational Conference on Computational Science ICCS 2017 - Zurich, Switzerland
Duration: Jun 12 2017Jun 14 2017

Keywords

  • continuity-aware optimal dissection
  • direct solvers
  • multi-frontal solvers
  • refined IsoGeometric Analysis (rIGA)
  • solver-based discretization

ASJC Scopus subject areas

  • Computer Science(all)

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