Gappy data: To Krig or not to Krig?

Hasan Gunes, Sirod Sirisup, George Em Karniadakis*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

109 Citations (Scopus)

Abstract

Data recovery and reconstruction methods for unsteady flow fields with spatio-temporal missing data are studied based on proper orthogonal decomposition (POD) and on Kriging interpolation. It is found that for sufficient temporal resolution, POD-based methods outperform Kriging interpolation. However, for insufficient temporal resolution, large spatial gappiness or for flow fields with black zones, Kriging interpolation is more effective. The comparison is performed based on randomly generated laminar and turbulent flow fields obtained from simulations of uniform flow past a circular cylinder.

Original languageEnglish
Pages (from-to)358-382
Number of pages25
JournalJournal of Computational Physics
Volume212
Issue number1
DOIs
Publication statusPublished - 10 Feb 2006

Funding

H. Gunes gratefully acknowledges the financial support of The Scientific and Technical Research Council of Turkey (TUBITAK). S. Sirisup gratefully acknowledges the DPST (Development and Promotion of Science and Technology Talents) project from Thailand for providing his scholarship during his graduate studies at Brown University. We thank Dr. Steve Dong for helpful discussions. This work was supported by NSF (Dr. F. Darema) and ONR (Dr. T.F. Swean), and computations were performed at the facilities of NCSA (University of Illinois at Urbana-Champaign) and at DoD’s NAVO MSRC.

FundersFunder number
Development and Promotion of Science and Technology Talents
DoD’s NAVO MSRC
TUBITAK
National Science Foundation
Office of Naval Research
Brown University
Türkiye Bilimsel ve Teknolojik Araştirma Kurumu

    Keywords

    • Kriging
    • Proper orthogonal decomposition
    • Unsteady flow

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