Estudos de conforto térmico em ambientes ventilados naturalmente em Campina Grande - PB

Abstract

The adaptive thermal comfort models of naturally ventilated spaces and adapted to the hypothesis of the existence of a causal relationship between the acceptable internal adjustments with the external temperature, considering the aspects of physical adaptation, physical part and psychological temperature. How the expansion opportunities can especially reduce the specially designed thermal zones, the ones that can affect the behavior of temperatures, the ideal conditions to expand the thermal areas, the conditions in which they can affect the behavior of people. On the other hand, there is a stimulating stimulus, like the classic positions, they have a high stimulus, and the thermoregulatory conditions have a level of attraction that is not thermal and thermal, neither thermal nor thermal, promoting comfort. In this sense, through a longitudinal study, this research estimates a thermal comfort model for naturally ventilated environments in the city of Campina Grande, Paraíba. For this, 1441 people were interviewed, between the years 2017 and 2020, in school, residential and leisure spaces, including adolescents, adults and elderly people acclimated to the semiarid region. In parallel, the main thermal environmental variables were measured, namely, air temperature, mean radiant temperature, relative air humidity and air velocity. The neutral temperature found by the Griffiths method was 26.05°C. The individuals of gender and the body mass index of the individuals vary in the thermal recommendation. Gender was also influenced by temperature. Temperature proved to be the most influential variable to estimate sensitivity, preference and thermal comfort, and the importance of air ventilation and humidity is also a highlight for estimators for semi-relative climate. The ASHRAE 55 (2020) adaptive thermal comfort predictive index proved to be adequate to estimate the thermal acceptability of users. On the other hand, the PMV showed low predictive power, and the adjustment regressions were estimated. Parametric and non-parametric models were developed to estimate thermal comfort. Note a preference for slightly cold sensations, expanding the comfort range.