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dc.contributor.authorBaker, E
dc.contributor.authorChallenor, P
dc.contributor.authorEames, M
dc.date.accessioned2021-02-19T15:41:11Z
dc.date.issued2020-12-19
dc.description.abstractHow can one design a building that will be sufficiently protected against overheating and sufficiently energy efficient, whilst considering the expected increases in temperature due to climate change? We successfully manage to address this question—greatly reducing a large set of initial candidate building designs down to a small set of acceptable buildings. We do this using a complex computer model, statistical models of said computer model (emulators), and a modification to the history matching calibration technique. This modification tackles the problem of level‐set estimation (rather than calibration), where the goal is to find input settings which lead to the simulated output being below some threshold. The entire procedure allows us to present a practitioner with a set of acceptable building designs, with the final design chosen based on other requirements (subjective or otherwise).en_GB
dc.description.sponsorshipEngineering and Physical Sciences Research Council (EPSRC)en_GB
dc.identifier.citationPublished online 19 December 2020en_GB
dc.identifier.doihttps://doi.org/10.1111/rssc.12461
dc.identifier.urihttp://hdl.handle.net/10871/124819
dc.language.isoenen_GB
dc.publisherWiley / Royal Statistical Societyen_GB
dc.rights© 2020 The Authors. Journal of the Royal Statistical Society: Series C (Applied Statistics) published by John Wiley & Sons Ltd on behalf of Royal Statistical Society. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.en_GB
dc.subjectbuilding performance simulationen_GB
dc.subjectGaussian processesen_GB
dc.subjecthistory matchingen_GB
dc.subjectlevel set estimationen_GB
dc.subjectstochastic simulationen_GB
dc.subjectuncertainty quantificationen_GB
dc.titleFuture proofing a building design using history matching inspired level‐set techniquesen_GB
dc.typeArticleen_GB
dc.date.available2021-02-19T15:41:11Z
dc.identifier.issn0035-9254
dc.descriptionThis is the final version. Available on open access from Wiley via the DOI in this record. en_GB
dc.identifier.eissn1467-9876
dc.identifier.journalJournal of the Royal Statistical Society: Series C (Applied Statistics)en_GB
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_GB
dcterms.dateAccepted2020-11-09
exeter.funder::Engineering and Physical Sciences Research Council (EPSRC)en_GB
rioxxterms.versionVoRen_GB
rioxxterms.licenseref.startdate2020-12-19
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2021-02-19T15:33:15Z
refterms.versionFCDVoR
refterms.dateFOA2021-02-19T15:41:16Z
refterms.panelBen_GB


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© 2020 The Authors. Journal of the Royal Statistical Society: Series C (Applied Statistics) published by John Wiley & Sons Ltd on behalf of Royal Statistical Society.

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
Except where otherwise noted, this item's licence is described as © 2020 The Authors. Journal of the Royal Statistical Society: Series C (Applied Statistics) published by John Wiley & Sons Ltd on behalf of Royal Statistical Society. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.