Characterizing spatial variability in the temperature field to support thermal model validation in a naturally ventilated building

Abstract

ABSTRACT Night-time passive cooling is an energy-efficient cooling strategy, but the design of passive cooling systems relies on imperfect computational models, which require validation. This paper assesses the importance of spatial variability in the temperature field when performing model validation. Full-scale temperature measurements in a three story atrium building reveal spatial variability of up to on each floor during the natural ventilation process. Validation of a dynamic thermal model with uncertainty quantification reveals accurate volume-averaged air temperature predictions. Discrepancies are on the order of the sensor accuracy (), and are primarily due to slightly under-predicted cooling rates in the model. Importantly, this trend would be identified incorrectly when validating the model against the building's built-in sensors, which consistently record 0.05–1.63 higher temperatures than the volume-averaged air temperature. These findings highlight the importance of spatial variability and careful temperature sensor placement in naturally ventilated buildings.