IGA-based multi-index stochastic collocation for random PDEs on arbitrary domains

Joakim Beck, Lorenzo Tamellini, Raul Tempone

Research output: Contribution to journalArticlepeer-review

11 Scopus citations


This paper proposes an extension of the Multi-Index Stochastic Collocation (MISC) method for forward uncertainty quantification (UQ) problems in computational domains of shape other than a square or cube, by exploiting isogeometric analysis (IGA) techniques. Introducing IGA solvers to the MISC algorithm is very natural since they are tensor-based PDE solvers, which are precisely what is required by the MISC machinery. Moreover, the combination-technique formulation of MISC allows the straightforward reuse of existing implementations of IGA solvers. We present numerical results to showcase the effectiveness of the proposed approach.
Original languageEnglish (US)
Pages (from-to)330-350
Number of pages21
JournalComputer Methods in Applied Mechanics and Engineering
StatePublished - Mar 28 2019


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