Propagation of uncertainty and sensitivity analysis in an integral oil-gas plume model

Handle URI:
http://hdl.handle.net/10754/613016
Title:
Propagation of uncertainty and sensitivity analysis in an integral oil-gas plume model
Authors:
Wang, Shitao; Iskandarani, Mohamed; Srinivasan, Ashwanth; Thacker, W. Carlisle; Winokur, Justin; Knio, Omar
Abstract:
Polynomial Chaos expansions are used to analyze uncertainties in an integral oil-gas plume model simulating the Deepwater Horizon oil spill. The study focuses on six uncertain input parameters—two entrainment parameters, the gas to oil ratio, two parameters associated with the droplet-size distribution, and the flow rate—that impact the model's estimates of the plume's trap and peel heights, and of its various gas fluxes. The ranges of the uncertain inputs were determined by experimental data. Ensemble calculations were performed to construct polynomial chaos-based surrogates that describe the variations in the outputs due to variations in the uncertain inputs. The surrogates were then used to estimate reliably the statistics of the model outputs, and to perform an analysis of variance. Two experiments were performed to study the impacts of high and low flow rate uncertainties. The analysis shows that in the former case the flow rate is the largest contributor to output uncertainties, whereas in the latter case, with the uncertainty range constrained by aposteriori analyses, the flow rate's contribution becomes negligible. The trap and peel heights uncertainties are then mainly due to uncertainties in the 95% percentile of the droplet size and in the entrainment parameters.
KAUST Department:
Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division
Citation:
Propagation of uncertainty and sensitivity analysis in an integral oil-gas plume model 2016 Journal of Geophysical Research: Oceans
Publisher:
Wiley-Blackwell
Journal:
Journal of Geophysical Research: Oceans
Issue Date:
27-May-2016
DOI:
10.1002/2015JC011365
Type:
Article
ISSN:
21699275
Sponsors:
We thank the two anonymous reviewers for their constructive suggestions which improve this manuscript. This work was made possible in part by a grant from BP/ The Gulf of Mexico Research Initiative, and by the Office of Naval Research, Award N00014-101-0498. J. Winokur and O. M. Knio were also supported in part by the U.S. Department of Energy (DOE), Office of Science, Office of Advanced Scientific Computing Research, under Award DE-SC0008789. This research was conducted in collaboration with and using the resources of the University of Miami Center for Computational Science. The model data are publicly available in the Gulf of Mexico Research Initiative Information and Data Cooperative (GRIIDC) repository (https://data. gulfresearchinitiative.org/data/R4.x265. 252:0002/).
Additional Links:
http://doi.wiley.com/10.1002/2015JC011365
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Full metadata record

DC FieldValue Language
dc.contributor.authorWang, Shitaoen
dc.contributor.authorIskandarani, Mohameden
dc.contributor.authorSrinivasan, Ashwanthen
dc.contributor.authorThacker, W. Carlisleen
dc.contributor.authorWinokur, Justinen
dc.contributor.authorKnio, Omaren
dc.date.accessioned2016-06-14T09:15:43Z-
dc.date.available2016-06-14T09:15:43Z-
dc.date.issued2016-05-27-
dc.identifier.citationPropagation of uncertainty and sensitivity analysis in an integral oil-gas plume model 2016 Journal of Geophysical Research: Oceansen
dc.identifier.issn21699275-
dc.identifier.doi10.1002/2015JC011365-
dc.identifier.urihttp://hdl.handle.net/10754/613016-
dc.description.abstractPolynomial Chaos expansions are used to analyze uncertainties in an integral oil-gas plume model simulating the Deepwater Horizon oil spill. The study focuses on six uncertain input parameters—two entrainment parameters, the gas to oil ratio, two parameters associated with the droplet-size distribution, and the flow rate—that impact the model's estimates of the plume's trap and peel heights, and of its various gas fluxes. The ranges of the uncertain inputs were determined by experimental data. Ensemble calculations were performed to construct polynomial chaos-based surrogates that describe the variations in the outputs due to variations in the uncertain inputs. The surrogates were then used to estimate reliably the statistics of the model outputs, and to perform an analysis of variance. Two experiments were performed to study the impacts of high and low flow rate uncertainties. The analysis shows that in the former case the flow rate is the largest contributor to output uncertainties, whereas in the latter case, with the uncertainty range constrained by aposteriori analyses, the flow rate's contribution becomes negligible. The trap and peel heights uncertainties are then mainly due to uncertainties in the 95% percentile of the droplet size and in the entrainment parameters.en
dc.description.sponsorshipWe thank the two anonymous reviewers for their constructive suggestions which improve this manuscript. This work was made possible in part by a grant from BP/ The Gulf of Mexico Research Initiative, and by the Office of Naval Research, Award N00014-101-0498. J. Winokur and O. M. Knio were also supported in part by the U.S. Department of Energy (DOE), Office of Science, Office of Advanced Scientific Computing Research, under Award DE-SC0008789. This research was conducted in collaboration with and using the resources of the University of Miami Center for Computational Science. The model data are publicly available in the Gulf of Mexico Research Initiative Information and Data Cooperative (GRIIDC) repository (https://data. gulfresearchinitiative.org/data/R4.x265. 252:0002/).en
dc.language.isoenen
dc.publisherWiley-Blackwellen
dc.relation.urlhttp://doi.wiley.com/10.1002/2015JC011365en
dc.rightsArchived with thanks to Journal of Geophysical Research: Oceansen
dc.titlePropagation of uncertainty and sensitivity analysis in an integral oil-gas plume modelen
dc.typeArticleen
dc.contributor.departmentComputer, Electrical and Mathematical Science and Engineering (CEMSE) Divisionen
dc.identifier.journalJournal of Geophysical Research: Oceansen
dc.eprint.versionPublisher's Version/PDFen
dc.contributor.institutionRosenstiel School of Marine and Atmospheric Science; University of Miami; Miami FL USAen
dc.contributor.institutionTendral LLC; Miami FL USAen
dc.contributor.institutionMiami FL USAen
dc.contributor.institutionSandia National Laboratories; Albuquerque New Mexico USAen
dc.contributor.institutionDepartment of Mechanical Engineering and Material Science, Duke University, Durham, North Carolina, USAen
dc.contributor.affiliationKing Abdullah University of Science and Technology (KAUST)en
kaust.authorKnio, Omaren
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