Interactions with window openings by office occupants

Interactions with window openings by office occupants Based on almost seven years of continuous measurements, we have analysed in detail the influence of occupancy patterns, indoor temperature and outdoor climate parameters (temperature, wind speed and direction, relative humidity and rainfall) on window opening and closing behaviour. In this we have also considered the variability of behaviours between individuals. This paper begins by presenting some of the key findings from these analyses. We go on to develop and test several modelling approaches, including logistic probability distributions, Markov chains and continuous-time random processes. Based on detailed statistical analysis and cross-validation of each variant, we propose a hybrid of these techniques which models stochastic usage behaviour in a comprehensive and efficient way. We conclude by describing an algorithm for implementing this model in dynamic building simulation tools. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Building and Environment Elsevier

Interactions with window openings by office occupants

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Publisher
Elsevier
Copyright
Copyright © 2009 Elsevier Ltd
ISSN
0360-1323
DOI
10.1016/j.buildenv.2009.03.025
Publisher site
See Article on Publisher Site

Abstract

Based on almost seven years of continuous measurements, we have analysed in detail the influence of occupancy patterns, indoor temperature and outdoor climate parameters (temperature, wind speed and direction, relative humidity and rainfall) on window opening and closing behaviour. In this we have also considered the variability of behaviours between individuals. This paper begins by presenting some of the key findings from these analyses. We go on to develop and test several modelling approaches, including logistic probability distributions, Markov chains and continuous-time random processes. Based on detailed statistical analysis and cross-validation of each variant, we propose a hybrid of these techniques which models stochastic usage behaviour in a comprehensive and efficient way. We conclude by describing an algorithm for implementing this model in dynamic building simulation tools.

Journal

Building and EnvironmentElsevier

Published: Dec 1, 2009

References

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