Stochastic behavioural models of occupants' main bedroom window operation for UK residential buildings
dc.contributor.author | Jones, RV | en |
dc.contributor.author | Fuertes, A | en |
dc.contributor.author | Gregori, E | en |
dc.contributor.author | Giretti, A | en |
dc.date.accessioned | 2017-03-28T09:17:13Z | |
dc.date.issued | 2017-06-01 | en |
dc.identifier.issn | 0360-1323 | en |
dc.identifier.uri | http://hdl.handle.net/10026.1/8698 | |
dc.description.abstract |
This paper presents the development of stochastic models of occupants' main bedroom window operation based on measurements collected in ten UK dwellings over a period of a year. The study uses multivariate logistic regression to understand the probability of opening and closing windows based on indoor and outdoor environment factors (physical environmental drivers) and according to the time of the day and season (contextual drivers). To the authors' knowledge, these are the first models of window opening and closing behaviour developed for UK residential buildings. The work reported in this paper suggests that occupants' main bedroom window operation is influenced by a range of physical environmental (i.e. indoor and outdoor air temperature and relative humidity, wind speed, solar radiation and rainfall) and contextual variables (i.e. time of day and season). In addition, the effects of the physical environmental variables were observed to vary in relation to the contextual factors. The models provided in this work can be used to calculate the probability that the main bedroom window will be opened or closed in the next 10 min. These models could be used in building performance simulation applications to improve the inputs for occupants' window opening and closing behaviour and thus the predictions of energy use and indoor environmental conditions of residential buildings. | en |
dc.format.extent | 144 - 158 | en |
dc.language.iso | en | en |
dc.subject | Window opening behaviour | en |
dc.subject | Occupant behaviour | en |
dc.subject | Behavioural modelling | en |
dc.subject | Residential buildings | en |
dc.subject | Statistical modelling | en |
dc.subject | Building energy performance simulation | en |
dc.title | Stochastic behavioural models of occupants' main bedroom window operation for UK residential buildings | en |
dc.type | Journal Article | |
plymouth.volume | 118 | en |
plymouth.publication-status | Published | en |
plymouth.journal | Building and Environment | en |
dc.identifier.doi | 10.1016/j.buildenv.2017.03.033 | en |
plymouth.organisational-group | /Plymouth | |
plymouth.organisational-group | /Plymouth/Faculty of Arts, Humanities and Business | |
plymouth.organisational-group | /Plymouth/Faculty of Arts, Humanities and Business/School of Art, Design and Architecture | |
plymouth.organisational-group | /Plymouth/REF 2021 Researchers by UoA | |
plymouth.organisational-group | /Plymouth/REF 2021 Researchers by UoA/UoA13 Architecture, Built Environment and Planning | |
plymouth.organisational-group | /Plymouth/Users by role | |
plymouth.organisational-group | /Plymouth/Users by role/Academics | |
dcterms.dateAccepted | 2017-03-21 | en |
dc.rights.embargodate | 2018-03-22 | en |
dc.rights.embargoperiod | 12 months | en |
rioxxterms.versionofrecord | 10.1016/j.buildenv.2017.03.033 | en |
rioxxterms.licenseref.uri | http://www.rioxx.net/licenses/under-embargo-all-rights-reserved | en |
rioxxterms.licenseref.startdate | 2017-06-01 | en |
rioxxterms.type | Journal Article/Review | en |