A priori testing of sparse adaptive polynomial chaos expansions using an ocean general circulation model database

Justin Winokur, Patrick Conrad, Ihab Sraj, Omar Knio, Ashwanth Srinivasan, W. Carlisle Thacker, Youssef Marzouk, Mohamed Iskandarani

Research output: Contribution to journalArticle

28 Scopus citations

Abstract

This work explores the implementation of an adaptive strategy to design sparse ensembles of oceanic simulations suitable for constructing polynomial chaos surrogates. We use a recently developed pseudo-spectral algorithm that is based on a direct application of the Smolyak sparse grid formula and that allows the use of arbitrary admissible sparse grids. The adaptive algorithm is tested using an existing simulation database of the oceanic response to Hurricane Ivan in the Gulf of Mexico. The a priori tests demonstrate that sparse and adaptive pseudo-spectral constructions lead to substantial savings over isotropic sparse sampling in the present setting.

Original languageEnglish (US)
Pages (from-to)899-911
Number of pages13
JournalComputational Geosciences
Volume17
Issue number6
DOIs
StatePublished - Jul 4 2013
Externally publishedYes

Keywords

  • Adaptive sampling
  • Ocean modeling
  • Polynomial chaos
  • Sparse Smolyak quadrature
  • Uncertainty quantification

ASJC Scopus subject areas

  • Computer Science Applications
  • Computers in Earth Sciences
  • Computational Theory and Mathematics
  • Computational Mathematics

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