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Front shape similarity measure for shape-oriented sensitivity analysis and data assimilation for Eikonal equation

hal.structure.identifierCentre Européen de Recherche et de Formation Avancée en Calcul Scientifique [CERFACS]
dc.contributor.authorROCHOUX, Mélanie
hal.structure.identifierModélisation Mathématique pour l'Oncologie [MONC]
dc.contributor.authorCOLLIN, Annabelle
hal.structure.identifierDepartment of Fire Protection Engineering [College Park]
dc.contributor.authorZHANG, Cong
hal.structure.identifierDepartment of Fire Protection Engineering [College Park]
dc.contributor.authorTROUVÉ, Arnaud
hal.structure.identifierLaboratoire d'Informatique pour la Mécanique et les Sciences de l'Ingénieur [LIMSI]
dc.contributor.authorLUCOR, Didier
hal.structure.identifierMathematical and Mechanical Modeling with Data Interaction in Simulations for Medicine [M3DISIM]
dc.contributor.authorMOIREAU, Philippe
dc.date.accessioned2024-04-04T03:08:16Z
dc.date.available2024-04-04T03:08:16Z
dc.date.issued2018
dc.identifier.issn2267-3059
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/193513
dc.description.abstractEnWe present a shape-oriented data assimilation strategy suitable for front-tracking problems through the example of wildfire. The concept of " front " is used to model, at regional scales, the burning area delimitation that moves, undergoes shape and topological changes under heterogeneous orography, biomass fuel and micrometeorology. The simulation-observation discrepancies are represented using a front shape similarity measure deriving from image processing and based on the Chan-Vese contour fitting functional. We show that consistent corrections of the front location and uncertain physical parameters can be obtained using this measure applied on a level-set fire growth model solving for an eikonal equation. This study involves a Luenberger observer for state estimation, including a topological gradient term to track multiple fronts, and of a reduced-order Kalman filter for joint parameter estimation. We also highlight the need – prior to parameter estimation – for sensitivity analysis based on the same discrepancy measure, and for instance using polynomial chaos metamodels, to ensure a meaningful inverse solution is achieved. The performance of the shape-oriented data assimilation strategy is assessed on a synthetic configuration subject to uncertainties in front initial position, near-surface wind magnitude and direction. The use of a robust front shape similarity measure paves the way toward the direct assimilation of infrared images and is a valuable asset in the perspective of data-driven wildfire modeling.
dc.language.isoen
dc.publisherEDP Sciences
dc.title.enFront shape similarity measure for shape-oriented sensitivity analysis and data assimilation for Eikonal equation
dc.typeArticle de revue
dc.identifier.doi10.1051/proc/201863258
dc.subject.halInformatique [cs]/Modélisation et simulation
dc.subject.halMathématiques [math]/Equations aux dérivées partielles [math.AP]
dc.subject.halMathématiques [math]/Optimisation et contrôle [math.OC]
bordeaux.journalESAIM: Proceedings and Surveys
bordeaux.page258 - 279
bordeaux.hal.laboratoriesInstitut de Mathématiques de Bordeaux (IMB) - UMR 5251*
bordeaux.institutionUniversité de Bordeaux
bordeaux.institutionBordeaux INP
bordeaux.institutionCNRS
bordeaux.peerReviewedoui
hal.identifierhal-01625575
hal.version1
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-01625575v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=ESAIM:%20Proceedings%20and%20Surveys&rft.date=2018&rft.spage=258%20-%20279&rft.epage=258%20-%20279&rft.eissn=2267-3059&rft.issn=2267-3059&rft.au=ROCHOUX,%20M%C3%A9lanie&COLLIN,%20Annabelle&ZHANG,%20Cong&TROUV%C3%89,%20Arnaud&LUCOR,%20Didier&rft.genre=article


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