Dynamic predictive clothing insulation models based on outdoor air and indoor operative temperatures

摘要: Clothing affects people’s perception of the thermal environment. Two dynamic predictive models clothing insulation were developed based on 6,333 selected observations 23,475 available in ASHRAE RP-884 and RP-921 databases. The used to statistically analyze influence 20 variables insulation. results show that median is 0.59 clo (0.50 (n=3,384) summer 0.69 (n=2,949) winter). winter value significantly smaller than suggested international standards (1.0 clo). California data (n= 2,950) shows occupants dress equally naturally mechanically conditioned buildings all has female male dressing with quite similar levels. correlated outdoor air (r = 0.45) indoor operative (r=0.3) temperatures, relative humidity (r=0.26) An index predict presence a code developed. multivariable linear mixed In first one function temperature measured at 6 o’clock, second adds temperature. able 19 22% total variance, respectively. Climate explain only small part human behavior; nonetheless, allow more precise comfort calculation, energy simulation, HVAC sizing building operation previous practice keeping values equal 0.5 cooling season 1 heating season.