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A satisfaction-range approach for achieving thermal comfort level in a shared office

机译:在共享办公室中达到热舒适水平的满意范围方法

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A personal comfort assessment model predicts occupants' thermal comfort responses, specific to each individual, as an alternative to the mean response of a large population. However, current air conditioning systems rely on a fixed set-point based on the maximum occupancy assumptions which may cause discomfort for occupants. In addition, securing consistent comfort level for occupants in a shared space is challenging due to the difference of preference thermal comfort of individuals. This research proposes a method which is not only relying on individuals' survey participation but also utilizing the advantages of the comfort level modelling. Computational fluid dynamics (CFD) was used to evaluate thermal comfort through modelling of the predicted mean vote (PMV) and the predicted percentage dissatisfied (PPD) in several scenarios and the consequential thermal zones and their corresponding occupants were identified. A fuzzy-based approach is used to develop a personal thermal preference profile. Based on the present occupants in the room, a boundary of temperatures for HVAC set-points is estimated and used for controlling the HVAC system. The implementation of the proposed method shows the mean margin error of 12.95 percent for the prediction of preference temperatures of nine occupants in a shared space. The result shows that the proposed approach has a significant potential of maintaining most of the occupants in a reasonable thermal comfort range.
机译:个人舒适度评估模型可预测每个人的居住者的热舒适度响应,以代替大批人的平均响应。然而,当前的空调系统基于基于最大占用假设的固定设定点,这可能会引起乘客的不适。另外,由于个人偏好的热舒适度的差异,在共享空间中确保乘员的一致舒适度水平也是一项挑战。这项研究提出了一种方法,该方法不仅依赖于个人的调查参与,而且还利用了舒适水平建模的优势。在几种情况下,使用计算流体动力学(CFD)通过对预测平均投票(PMV)和预测不满意百分比(PPD)进行建模来评估热舒适度,并确定相应的热区及其相应的居住者。基于模糊的方法用于建立个人的热偏好曲线。根据房间中的当前居住者,估算HVAC设定点的温度边界,并将其用于控制​​HVAC系统。所提出的方法的执行结果显示,对于共享空间中的九个居住者的偏好温度的预测,平均裕度误差为12.95%。结果表明,所提出的方法具有将大多数乘员保持在合理的热舒适范围内的巨大潜力。

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