A review of thermal comfort

摘要

Thermal comfort is defined as “that state of mind which expresses satisfaction with the thermal environment” (ANSI/ASHRAE, 2017). The definition of thermal comfort leaves open as to what is meant by condition of mind or satisfaction, but it correctly emphasizes that the judgment of comfort is a cognitive process involving many inputs related to physical, physiological, psychological, and other factors (Lin amp; Deng, 2008). People are always in an internal or external thermal environment. The human body produces heat and exchanges heat with the external environment. During normal activities these processes result in an average core body temperature of approximately 37 °C (Prek, 2005). This stable core body temperature is essential for our health and well-being. Our thermal interaction with the environment is directed towards maintaining this stability in a process called “thermoregulation” (Nicol, Humphreys, amp; Roaf, 2012).Thermal comfort plays an important role in the energy consumption of buildings. So, researchers spent decades to find the appropriate approaches and models which evaluate and predict thermal comfort. A literature review of the current knowledge on thermal comfort shows two different approaches for thermal comfort, each one with its potentialities and limits: the heat-balance model and the adaptive model (Doherty amp; Arens, 1988). The heat-balance approach is based on analysis of the heat flows in and around the body and resulted in a model based on physics and physiology. Data from climate chamber studies was used to support this model. The best wellknown heat-balance models are the predicted mean vote (PMV) (Fanger, 1970) and the standard effective temperature (SET) (Gagge, Fobelets, amp; Berglund, 1986). The PMV model is particularly important because it forms the basis for most national and international comfort standards. The adaptive approach is based on field surveysnbsp;of people’s response to the environment, using statistical analysis and leads to an “empirical” model (Nicol et al., 2012).