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Future proofing a building design using history matching inspired level‐set techniques

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  • Evan Baker
  • Peter Challenor
  • Matt Eames

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).

Suggested Citation

  • Evan Baker & Peter Challenor & Matt Eames, 2021. "Future proofing a building design using history matching inspired level‐set techniques," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(2), pages 335-350, March.
    • Handle: RePEc:bla:jorssc:v:70:y:2021:i:2:p:335-350
    DOI: 10.1111/rssc.12461
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    References listed on IDEAS

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    1. I. Andrianakis & I. Vernon & N. McCreesh & T. J. McKinley & J. E. Oakley & R. N. Nsubuga & M. Goldstein & R. G. White, 2017. "History matching of a complex epidemiological model of human immunodeficiency virus transmission by using variance emulation," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 66(4), pages 717-740, August.
    2. Ioannis Andrianakis & Ian R Vernon & Nicky McCreesh & Trevelyan J McKinley & Jeremy E Oakley & Rebecca N Nsubuga & Michael Goldstein & Richard G White, 2015. "Bayesian History Matching of Complex Infectious Disease Models Using Emulation: A Tutorial and a Case Study on HIV in Uganda," PLOS Computational Biology, Public Library of Science, vol. 11(1), pages 1-18, January.
    3. Schnieders, Jurgen & Hermelink, Andreas, 2006. "CEPHEUS results: measurements and occupants' satisfaction provide evidence for Passive Houses being an option for sustainable building," Energy Policy, Elsevier, vol. 34(2), pages 151-171, January.
    4. Jeremy Oakley, 2002. "Bayesian inference for the uncertainty distribution of computer model outputs," Biometrika, Biometrika Trust, vol. 89(4), pages 769-784, December.
    5. James M. Salter & Daniel Williamson, 2016. "A comparison of statistical emulation methodologies for multi‐wave calibration of environmental models," Environmetrics, John Wiley & Sons, Ltd., vol. 27(8), pages 507-523, December.
    6. Marc C. Kennedy & Anthony O'Hagan, 2001. "Bayesian calibration of computer models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 63(3), pages 425-464.
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