Adaptive Selection of Primal Constraints for Isogeometric BDDC Deluxe Preconditioners
KAUST DepartmentExtreme Computing Research Center
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AbstractIsogeometric analysis has been introduced as an alternative to finite element methods in order to simplify the integration of computer-aided design (CAD) software and the discretization of variational problems of continuum mechanics. In contrast with the finite element case, the basis functions of isogeometric analysis are often not nodal. As a consequence, there are fat interfaces which can easily lead to an increase in the number of interface variables after a decomposition of the parameter space into subdomains. Building on earlier work on the deluxe version of the BDDC (balancing domain decomposition by constraints) family of domain decomposition algorithms, several adaptive algorithms are developed in this paper for scalar elliptic problems in an effort to decrease the dimension of the global, coarse component of these preconditioners. Numerical experiments provide evidence that this work can be successful, yielding scalable and quasi-optimal adaptive BDDC algorithms for isogeometric discretizations.
CitationDa Veiga LB, Pavarino LF, Scacchi S, Widlund OB, Zampini S (2017) Adaptive Selection of Primal Constraints for Isogeometric BDDC Deluxe Preconditioners. SIAM Journal on Scientific Computing 39: A281–A302. Available: http://dx.doi.org/10.1137/15M1054675.
SponsorsThe work of the first three authors was supported by grants from M.I.U.R. (PRIN 201289A4LX 002) and from the Istituto Nazionale di Alta Matematica (INDAM-GNCS). The work of the fourth author was partially supported by National Science Foundation grant DMS-1522736.