Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.
DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.
Based on the results from a field survey campaign, this article describes three new developments which have been integrated to provide a comprehensive basis for 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 degreedays of overheating stimuli for input to a new model to predict overheating risk. Based on the 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 article introduces these developments and how they may be coupled to building simulation programs to predict the risk that proposed design solutions will overheat. Scope for further development, as well as possible alternatives to the presented approach, are also discussed.
Jean-Paul Richard Kneib, Mathieu Salzmann, Frédéric Dux, Belén Yu Irureta-Goyena Chang