Future proofing a building design using history matching inspired level‐set techniques
dc.contributor.author | Baker, E | |
dc.contributor.author | Challenor, P | |
dc.contributor.author | Eames, M | |
dc.date.accessioned | 2021-02-19T15:41:11Z | |
dc.date.issued | 2020-12-19 | |
dc.description.abstract | How 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.sponsorship | Engineering and Physical Sciences Research Council (EPSRC) | en_GB |
dc.identifier.citation | Published online 19 December 2020 | en_GB |
dc.identifier.doi | https://doi.org/10.1111/rssc.12461 | |
dc.identifier.uri | http://hdl.handle.net/10871/124819 | |
dc.language.iso | en | en_GB |
dc.publisher | Wiley / Royal Statistical Society | en_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.subject | building performance simulation | en_GB |
dc.subject | Gaussian processes | en_GB |
dc.subject | history matching | en_GB |
dc.subject | level set estimation | en_GB |
dc.subject | stochastic simulation | en_GB |
dc.subject | uncertainty quantification | en_GB |
dc.title | Future proofing a building design using history matching inspired level‐set techniques | en_GB |
dc.type | Article | en_GB |
dc.date.available | 2021-02-19T15:41:11Z | |
dc.identifier.issn | 0035-9254 | |
dc.description | This is the final version. Available on open access from Wiley via the DOI in this record. | en_GB |
dc.identifier.eissn | 1467-9876 | |
dc.identifier.journal | Journal of the Royal Statistical Society: Series C (Applied Statistics) | en_GB |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | en_GB |
dcterms.dateAccepted | 2020-11-09 | |
exeter.funder | ::Engineering and Physical Sciences Research Council (EPSRC) | en_GB |
rioxxterms.version | VoR | en_GB |
rioxxterms.licenseref.startdate | 2020-12-19 | |
rioxxterms.type | Journal Article/Review | en_GB |
refterms.dateFCD | 2021-02-19T15:33:15Z | |
refterms.versionFCD | VoR | |
refterms.dateFOA | 2021-02-19T15:41:16Z | |
refterms.panel | B | en_GB |
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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.