2 research outputs found

    Development of stochastic models of window state changes in educational buildings

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    How people would like to interact with surrounding environment will subsequently influence indoor thermal conditions and further impact building energy performance. In order to understand occupants' adaptive behaviours in terms of environmental control utilization from the point of view of quantification, an investigation on windows operation was carried out in non-air-conditioned educational buildings in the UK during summer time considering the effects of occupant type (active and passive) and the time of a day. Outdoor air temperature was a better predictor or window operation than indoor air temperature. Window operation was found to be time-evolving event. The purpose or criteria of adjusting window states were different at different occupancy stages. Active occupants were more willing to change windows states in response to outdoor air temperature variations. Sub-models predicting transition probabilities of window state for different occupant type and occupancy stages were developed. The results derived from this field study are helpful with improving building simulation accuracy by integrating sub-models into simulation software and further providing guideline on building energy reduction without sacrificing indoor thermal comfort

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

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    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
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