An integrated adaptive model for overheating risk prediction
Based on results from a field survey campaign, this paper describes three new developments which have been integrated to provide for a comprehensive basis l'or the evaluation of overheating risk in offices. Firstly, a set of logistic regression equations have been derived to predict the probability of office occupants' adaptation of personal and environmental characteristics. Secondly, empirical adaptive increments (offsets in comfort temperature) have been derived for each of these modes of adaptation. Thirdly, these adaptive increments are used to derive adapted degree-days of overheating stimuli for input to a new model to predict overheating risk. Based on analogy between the charging and discharging of humans' tolerance to overheating stimuli and that of charge in an electrical capacitor, this analytical model uses empirical coefficients to tune its (dis)charging time constants to a given population and situation. This paper introduces these developments and discusses scope for their further development.