Probabilistic adaptive thermal comfort for resilient design
Probabilistic adaptive thermal comfort for resilient design
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弹性设计的概率自适应热舒适度
DOI：
10.1016/j.buildenv.2017.06.050
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发表时间：
2017
影响因子：
7.4
通讯作者：
Coley D
中科院分区：
文献类型：
--
作者：
Coley D
适应性热舒适理论已经成为人们思考如何判断自由运动环境是否适合人类职业的基础。在设计工作中，热模型预测的条件，当模型与一个可能的年度天气时间序列（参考年），比较人类舒适的限制。如果温度在舒适范围内，则该建筑物被判定为合适。然而，许多地方的天气可能会每年有相当大的变化，这就引出了一个问题，即自适应舒适理论的预测在建筑物使用的许多年里可能有多稳健？我们使用五个主要柯本气候分类中每个地区长达30年的天气数据来回答这个问题。我们发现，在每年的时间序列的变化是如此之大，预测的舒适温度经常位于参考年给出的可接受的范围之外。为每个位置计算时间序列偏移的重现期。然后使用世界上最长的温度记录验证一个位置的结果。这些结果表明，工业界和学术界将最好的建议，以转移到概率的方法，如所提出的，当使用自适应舒适理论来判断建筑物内的可能条件。由于气候迅速变暖，人们对建筑物中死亡率和发病率增加的担忧提供了额外的相关性。
Adaptive thermal comfort theory has become the bedrock of much thinking about how to judge if a free-running environment is suitable for human occupation. In design work, the conditions predicted by a thermal model, when the model is presented with one possible annual weather time series (a reference year), are compared to the limits of human comfort. If the temperatures are within the comfort limits, the building is judged to be suitable. However, the weather in many locations can vary year-on-year by a considerable margin, and this begs the question, how robust are the predictions of adaptive comfort theory likely to be over the many years a building might be in use? We answer this question using weather data recorded for up to 30 years for locations within each of the five major Köppen climate classifications. We find that the variation in the annual time series is so great that the predicted comfort temperature frequently lies outside the acceptable range given by the reference year. Return periods for the excursions of the time series are calculated for each location. The results for one location are then validated using the world's longest temperature record. These results suggest that industry and academia would be best advised to move to a probabilistic methodology, like the proposed one, when using adaptive comfort theory to judge the likely conditions within a building. Extra pertinence is provided by concerns over increases in mortality and morbidity in buildings due to a rapidly warming climate.
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影响因子：
2.7
作者：
Joo-Young Lee;Mohamed Saat;Chin-Mei Chou;N. Hashiguchi;Titis Wijayanto;Hitoshi Wakabayashi;Y. Tochihara
通讯作者：
Joo-Young Lee;Mohamed Saat;Chin-Mei Chou;N. Hashiguchi;Titis Wijayanto;Hitoshi Wakabayashi;Y. Tochihara
英国新测试参考年和设计夏季年的分析和算法
DOI：
--
发表时间：
2006
期刊：
影响因子：
--
作者：
G. Levermore;J. Parkinson
通讯作者：
J. Parkinson
根据变形的观测天气创建的未来天气与天气生成器创建的未来天气的比较
影响因子：
7.4
作者：
Eames M
通讯作者：
Eames M
CIBSE 设计夏季方法在提供代表性近极端夏季天气条件方面的局限性
影响因子：
1.7
作者：
Jentsch M
通讯作者：
Jentsch M
使用 UKCP09 概率气候预测生成建筑能源模拟夏季设计的方法
影响因子：
1.7
作者：
Smith S
通讯作者：
Smith S