Calibration and validation of building simulation models for overheating risk predictions: a case study of a matched pair of test houses in the UK

Abstract

Increasing global temperatures and more frequent heatwaves pose a growing indoor overheating risk. To address this issue, building simulation models are commonly used to predict indoor overheating risks and implement effective mitigation strategies during the design phase. However, concerns have arisen due to evidence of discrepancies between simulated and real building performance, casting doubt on their reliability. This study seeks to enhance the accuracy of building simulation models in predicting overheating risks through a case study of matched-pair test houses, synthetically occupied and unoccupied, using Bayesian calibration. The findings underscore discrepancies between simulated and measured data, where simulated results did not exceed the TM59 criteria while observed data surpassed the threshold. Among calibration iterations, weather data, especially those associated with solar radiation, plays a pivotal role in improving the accuracy of indoor temperature predictions through the novel approach of incorporating uncertainties into weather variables.

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ORCID for Stephanie Gauthier: orcid.org/0000-0002-1720-1736

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