Predictions of Indoor Thermal Comfort Level using Fuzzy Logic

Abstract

Prediction of Thermal Comfort Level (TCL) is one of the intricate observable facts to understand. This is due the fact that thermal comfort level is quite complicated to demonstrate precisely in view of the fact that the factual procedure has involvement of the human beings. For analytical principles, it can be believed that the individual is a "black box" which obtains inputs as atmospheric provisions and personage variables, while the output is the subjective acuity of thermal comfort level. Interior comfort state of a building relies on the peripheral ambiance and thermo-physical properties of the materials employed in the building. The outer climatologically constraints can be collective as a sole constraint known as Sol Air Temperature (SAT). Similarly, internal and open air surface heat transfer coefficients and thermal properties of the materials employed in the buildings are united in a single feature, termed as Overall Thermal Transmittance (OTT). In the present study, a fuzzy logic move towards achieving the suitable thermal comfort level is being employed assuming the SAT and OTT as input constraints. The complication of the human intellectual and the imprecision of linguistic expressions are taken into the deliberation. A comprehensive clarification of the relevance uniting linguistic approach to the optimization under numerous thermal provision principles is presented in this study.