A dataset from synthetically occupied test houses for validating model predictions of overheating

Enhanced guidance on the processes by which indoor temperatures are predicted by dynamic thermal models will improve the reliability of overheating risk assessments. This is especially important now that dynamic thermal models are used to test compliance with overheating regulations. A new empirical dataset has been created to validate and calibrate overheating models. A matched pair of synthetically occupied test houses were instrumented to measure indoor dry bulb, surface, and operative temperature at 87 different locations in the houses. Synthetic occupancy replicated window operation, blind position, door opening, and CIBSE TM59 internal heat gains. Tracer gas tests measured infiltration and ventilation. The outdoor weather conditions, which included two heatwaves, were measured at the test house site, and nearby at three other stations. The empirical dataset is made publicly available to allow others to test the reliability of dynamic thermal models for predicting overheating.