Dynamic predictive clothing insulation models based on outdoor air and indoor operative temperatures
Dynamic predictive clothing insulation models based on outdoor air and indoor operative temperatures
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DOI：
10.1016/j.buildenv.2012.08.024
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发表时间：
2013
影响因子：
7.4
通讯作者：
S. Schiavon;K. Lee
中科院分区：
文献类型：
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作者：
S. Schiavon;K. Lee
服装影响人们对热环境的感知。基于 ASHRAE RP-884 和 RP-921 数据库中 23,475 个数据中的 6333 个选定观察结果，开发了两种服装隔热动态预测模型。利用观察结果统计分析 20 个变量对服装隔热性的影响。结果显示，服装隔热效果的中位数为 0.59 克洛（夏季为 0.50 克洛 (n = 3384)，冬季为 0.69 克洛 (n = 2949)）。冬季服装隔热值中值明显小于国际标准建议值（1.0 clo）。加利福尼亚州的数据（n = 2950）显示，居住者在自然和机械空调建筑中的着装是相同的，并且所有数据中女性和男性的着装具有非常相似的服装隔热水平。服装隔热性与室外空气 (r = 0.45) 和室内工作温度 (r = 0.3) 以及相对湿度 (r = 0.26) 相关。开发了一个预测着装规范是否存在的指数。开发了两个多变量线性混合模型。第一个中，衣服是 6 点测量的室外气温的函数，第二个中添加了室内工作温度的影响。模型能够分别预测总方差的 19% 和 22%。气候变量只能解释人类着装行为的一小部分；尽管如此，与之前在制冷季节保持服装隔热值等于 0.5 和在采暖季节保持衣服隔热值等于 1 的做法相比，预测模型允许更精确的热舒适性计算、能源模拟、HVAC 尺寸和建筑运行。
Clothing affects people's perception of the thermal environment. Two dynamic predictive models of clothing insulation were developed based on 6333 selected observations of the 23,475 available in ASHRAE RP-884 and RP-921 databases. The observations were used to statistically analyze the influence of 20 variables on clothing insulation. The results show that the median clothing insulation is 0.59 clo (0.50 clo (n = 3384) in summer and 0.69 clo (n = 2949) 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 = 2950) 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.