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

Abstract

The results show that the median clothing insulation is 0.59 clo (0.50 clo (n=3,384) in summer and 0.69 clo (n=2,949) in winter). The median winter clothing insulation value is significantly smaller than the value suggested in the international standards (1.0 clo). The California data (n= 2,950) shows that occupants dress equally in naturally and mechanically conditioned buildings and all the data has female and male dressing with quite similar clothing insulation levels. Clothing insulation is correlated with outdoor air (r = 0.45) and indoor operative (r=0.3) temperatures, and relative humidity (r=0.26) An index to predict the presence of a dress code is developed.Two multivariable linear mixed models were developed. In the first one clothing is a function of outdoor air temperature measured at 6 o'clock, and the second one adds the influence of indoor operative temperature. The models were able to predict 19 and 22% of the total variance, respectively. Climate variables explain only a small part of human clothing behavior; nonetheless, the predictive models allow more precise thermal comfort calculation, energy simulation, HVAC sizing and building operation than previous practice of keeping the clothing insulation values equal to 0.5 in the cooling season and 1 in the heating season. Highlights• We developed two models to dynamically predict clothing insulation levels, R 2 adj =0.19-0.22 • Winter clothing insulation values are significantly lower than 1.0 clo • In California occupants dress equally in naturally and mechanically conditioned • Clothing values are correlated with outdoor air and indoor operative temperatures • Climate variables explain only a small part of human clothing behavior KEYWORDS Clothing, behavior modeling, thermal comfort, dress code, occupant behavior, indoor climate INTRODUCTIONThe amount of thermal insulation worn by a person has a substantial impact on thermal comfort [1]. Clothing adjustment is a behaviour that directly affects the heat-balance. The thermal insulation provided by garments and clothing ensembles is expressed in a unit named clo, where 1 clo is equal to 0.155 m 2 K/W. For near-sedentary activities where the metabolic rate is approximately 1.2 met, the effect of changing clothing insulation on the optimum operative temperature is approximately 6°C per clo. For example, adding a thin, long-sleeve sweater to a clothing ensemble increases clothing insulation by approximately 0.25 clo. Adding this insulation would lower the optimum operative temperature by approximately 6°C/clo × 0.25 clo = 1.5°C [1]. Clothing adjustment is perhaps the most important of all the thermal comfort adjustments available to occupants in office buildings [2].

Influence of Three Dynamic Predictive Clothing Insulation Models on Building Energy Use, HVAC Sizing and Thermal Comfort

“…Two new predictive clothing insulation models were developed by Schiavon and Lee [13] based on 6333 selected observations taken from the ASHRAE RP-884 and RP-921 databases. There are a variety of possible variables that may affect the clothing insulation such as metabolic activity, sex, HVAC system type, indoor operative temperature, relative humidity, outdoor condition, air velocity, season and location, etc.…”

“…There are a variety of possible variables that may affect the clothing insulation such as metabolic activity, sex, HVAC system type, indoor operative temperature, relative humidity, outdoor condition, air velocity, season and location, etc. The full list of the variables that were investigated for the screening process is summarized in [13]. A multivariable mixed model method was used to develop the regression equations.…”

“…In order to evaluate the validity of the new models, they have been fully tested in the database. For more details on the new models' development and validation process, refer to [13]. The Equations (1) and (2) do not include the insulation effect of the chair.…”

“…Therefore, the clothing insulation variation should be captured during the building simulation to realistically model HVAC systems. In order to overcome the limitations of the constant clothing insulation assumption, three new predictive clothing insulation models were developed by Schiavon and Lee based on 6333 selected observations taken from ASHRAE RP-884 and RP-921 databases [12][13][14][15]. The first and third models vary the clothing insulation as a function of outdoor air temperature measured at 6 o'clock and the second model takes into account both 6 o'clock outdoor air temperature and indoor operative temperature when adjusting the clothing insulation [13].…”

“…The difference among Cases 6, 7, and 8 is not strong, but Cases 7 and 6 are the most alike. Case 7 can be arguably considered the most precise (it use Equation (2) that gives the best predict abilities [13]). …”