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Evaluation of thermal sensation models for predicting thermal comfort in dynamic outdoor and indoor environments
Energy and Buildings ( IF 6.7 ) Pub Date : 2021-02-27 , DOI: 10.1016/j.enbuild.2021.110847
Xiaojie Zhou , Dayi Lai , Qingyan Chen

Thermal sensation models are commonly used to assess thermal perception in various indoor environments. Our previous work developed a new model to predict thermal sensation in cars that uses gradual change in thermal load on the face, sudden change in solar radiation on the face, mean skin temperature and outdoor air temperature as predictors. The present investigation selected 11 outdoor scenarios and 20 indoor scenarios from the literature to further verify the accuracy of the thermal sensation model. Four other thermal models, the predicted mean vote (PMV) model, the dynamic thermal sensation (DTS) model, a model from the University of California, Berkeley (UCB), and a transient outdoor thermal comfort model (Lai's) were compared with the new model for the 32 scenarios. The results confirmed the validity of the new model in an outdoor environment with sudden change in solar radiation. The new model was able to predict the trend of thermal changes, but the accuracy was not as good as that of the PMV model in an environment with indoor temperature gradient/sudden changes.



中文翻译:

评估热感模型以预测动态室外和室内环境中的热舒适度

热感模型通常用于评估各种室内环境中的热感。我们之前的工作开发了一种新的模型来预测汽车的热感,该模型利用面部的热负荷的逐渐变化,面部太阳辐射的突然变化,平均皮肤温度和室外空气温度作为预测因子。本研究从文献中选择了11种室外场景和20种室内场景,以进一步验证热敏模型的准确性。将其他四个热模型,预测的平均投票(PMV)模型,动态热感(DTS)模型,加利福尼亚大学伯克利分校(UCB)的模型和瞬态室外热舒适模型(Lai's)进行了比较。 32种方案的新模型。结果证实了该新模型在户外环境中的有效性,该环境具有太阳辐射的突然变化。新模型能够预测热变化趋势,但是在室内温度梯度/突然变化的环境中,其精度不如PMV模型。

更新日期:2021-03-08
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