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dc.contributor.authorIglesias, Marco
dc.contributor.authorSawlan, Zaid A
dc.contributor.authorScavino, Marco
dc.contributor.authorTempone, Raul
dc.contributor.authorWood, Christopher
dc.date.accessioned2018-09-03T06:44:43Z
dc.date.available2017-12-28T07:32:13Z
dc.date.available2018-09-03T06:44:43Z
dc.date.issued2018-05-22
dc.identifier.citationIglesias M, Sawlan Z, Scavino M, Tempone R, Wood C (2018) Ensemble-marginalized Kalman filter for linear time-dependent PDEs with noisy boundary conditions: application to heat transfer in building walls. Inverse Problems 34: 075008. Available: http://dx.doi.org/10.1088/1361-6420/aac224.
dc.identifier.issn0266-5611
dc.identifier.issn1361-6420
dc.identifier.doi10.1088/1361-6420/aac224
dc.identifier.urihttp://hdl.handle.net/10754/626490
dc.description.abstractIn this work, we present the ensemble-marginalized Kalman filter (EnMKF), a sequential algorithm analogous to our previously proposed approach (Ruggeri et al 2017 Bayesian Anal. 12 407-33, Iglesias et al 2018 Int. J. Heat Mass Transfer 116 417-31), for estimating the state and parameters of linear parabolic partial differential equations in initial-boundary value problems when the boundary data are noisy. We apply EnMKF to infer the thermal properties of building walls and to estimate the corresponding heat flux from real and synthetic data. Compared with a modified ensemble Kalman filter (EnKF) that is not marginalized, EnMKF reduces the bias error, avoids the collapse of the ensemble without needing to add inflation, and converges to the mean field posterior using or less of the ensemble size required by EnKF. According to our results, the marginalization technique in EnMKF is key to performance improvement with smaller ensembles at any fixed time.
dc.description.sponsorshipZ Sawlan, M Scavino and R Tempone are members of the KAUST SRI Center for Uncertainty Quantification in Computational Science and Engineering. R Tempone received support from the KAUST CRG3 Award Ref: 2281 and the KAUST CRG4 Award Ref: 2584.
dc.publisherIOP Publishing
dc.relation.urlhttp://iopscience.iop.org/article/10.1088/1361-6420/aac224/meta
dc.rightsThis is an author-created, un-copyedited version of an article accepted for publication/published \nin Inverse Problems. IOP Publishing Ltd is not responsible for any errors or omissions in this version of the manuscript or any version derived from it. The Version of Record is available online at http://doi.org/10.1088/1361-6420/aac224
dc.subjectensemble Kalman filter
dc.subjectheat capacity
dc.subjectheat equation
dc.subjectheat flux measurements
dc.subjectlinear PDEs
dc.subjectnuisance boundary parameters marginalization
dc.subjectthermal resistance
dc.titleEnsemble-marginalized Kalman filter for linear time-dependent PDEs with noisy boundary conditions: application to heat transfer in building walls
dc.typeArticle
dc.contributor.departmentApplied Mathematics and Computational Science Program
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.identifier.journalInverse Problems
dc.eprint.versionPost-print
dc.contributor.institutionSchool of Mathematical Sciences, University of Nottingham, Nottingham, , United Kingdom
dc.contributor.institutionInstituto de Estadística (IESTA), Universidad de la República, Montevideo, , Uruguay
dc.contributor.institutionDepartment of Architecture and Built Environment, University of Nottingham, Nottingham, , United Kingdom
dc.identifier.arxivid1711.09365
kaust.personScavino, Marco
kaust.personSawlan, Zaid A
kaust.personTempone, Raul
kaust.grant.number2281
kaust.grant.number2584
refterms.dateFOA2018-06-14T05:31:50Z
dc.date.published-online2018-05-22
dc.date.published-print2018-07-01
dc.date.posted2017-11-26


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