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*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

35 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 - Dec 2013

Bibliographical note

Funding Information:
Acknowledgments This research was supported by the Office of Naval Research, award N00014-101-0498; by the US Department of Energy, Office of Advanced Scientific Computing Research, award numbers DE-SC0007020, DE-SC0008789, and DE-SC0007099; and by the Gulf of Mexico Research Initiative, contract numbers SA1207GOMRI005 (CARTHE) and SA12GOMRI008 (DEEP-C).

Keywords

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

ASJC Scopus subject areas

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

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