Evaluation of a Coupled Model to Predict the Impact of Adaptive Behaviour in the Thermal Sensation of Occupants of Naturally Ventilated Buildings in Warm-Humid Regions

Improving indoor environment quality and making urban centres in tropical regions more sustainable has become a challenge for which computational models for the prediction of thermal sensation for naturally ventilated buildings (NVBs) have major role to play. This work performed analysis on thermal sensation for non-residential NVBs located in Brazilian tropical warm-humid climate and tested the effectiveness of suggested adaptive behaviours to mitigate warm thermal sensation. The research method utilized transient computational fluid dynamics models coupled with a dynamic model for human thermophysiology to predict thermal sensation. The calculated results were validated with comparison with benchmark values from questionnaires and from field measurements. The calculated results for dynamic thermal sensation (DTS) seven-point scale showed higher agreement with the thermal sensation vote than with the predicted mean vote. The test for the suggested adaptive behaviours considered reducing clothing insulation values from 0.18 to 0.32 clo (reducing DTS from 0.1 to 0.9), increasing the air speed in 0.9 m/s (reducing DTS from 0.1 to 0.9), and applying both suggestions together (reducing DTS from 0.1 to 1.3) for five scenarios with operative temperatures spanning 34.5–24.0 °C. Results quantified the tested adaptive behaviours’ efficiency showing applicability to improve thermal sensation from slightly-warm to neutral.