Computational Geosciences

, Volume 17, Issue 6, pp 899–911

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
Original Paper

DOI: 10.1007/s10596-013-9361-3

Cite this article as:
Winokur, J., Conrad, P., Sraj, I. et al. Comput Geosci (2013) 17: 899. doi:10.1007/s10596-013-9361-3

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.

Keywords

Uncertainty quantification Polynomial chaos Sparse Smolyak quadrature Adaptive sampling Ocean modeling 

Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  • Justin Winokur
    • 1
  • Patrick Conrad
    • 2
  • Ihab Sraj
    • 1
  • Omar Knio
    • 1
  • Ashwanth Srinivasan
    • 3
  • W. Carlisle Thacker
    • 4
    • 5
  • Youssef Marzouk
    • 2
  • Mohamed Iskandarani
    • 1
  1. 1.Department of Mechanical Engineeringand Materials ScienceDuke UniversityDurhamUSA
  2. 2.Department of Aeronautics and AstronauticsMassachusetts Insitute of TechnologyCambridgeUSA
  3. 3.Rosenstiel School of Marine and Atmospheric ScienceUniversity of MiamiMiamiUSA
  4. 4.Cooperative Institute of Marine and Atmospheric SciencesMiamiUSA
  5. 5.Atlantic Oceanographic and Meteorological LaboratoryMiamiUSA

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