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A probabilistic prediction model for window opening during transition seasons in office building

Liu, J., Yao, R. and McCloy, R. (2019) A probabilistic prediction model for window opening during transition seasons in office building. IOP Conference Series: Earth and Environmental Science, 310. 022017. ISSN 1755-1315

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To link to this item DOI: 10.1088/1755-1315/310/2/022017

Abstract/Summary

Window operation of occupants in building has close relationship with indoor air quality, indoor thermal environment and building energy performance. The objective of this study was to understand occupants' interaction with window opening in transition seasons considering the influence of subject type (e.g. active and passive respondents) and to develop corresponding predictive models. An investigation was carried out in non-air-conditioned building in the UK covering the period from September to November. Outdoor temperature in this study was determined as good predictor for window operation. The differences in window opening probabilities between active and passive subjects were significant. Active occupants preferred to open window for fresh air or for indoor thermal condition adjustment, even though the outdoor air temperature sometimes were less than 12 °C. Proper utilization of windows in transition seasons contributed significantly to building energy saving and further improve energy efficiency in buildings.

Item Type:Article
Refereed:Yes
Divisions:Henley Business School > Leadership, Organisations and Behaviour
ID Code:89791
Publisher:IOP

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