夏季自然通风降温策略设计与分析方法

R. Yao, K. Steemers, N. Baker
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引用次数: 8

摘要

在四节点热阻网络模型中,结合英国标准的单区域自然通风计算方法,建立了一种简化的热阻通风模型(TRV)。通过将TRV的结果与ESP-r程序的结果进行比较,并对TRV参数值进行调整,可以获得较好的相关性。提出了一种两阶段自然通风策略设计与分析方法。第一阶段计算恒定风量(CAR)并进行参数化研究,以提出满足热舒适的设计策略和适当的开放区域。第二阶段计算动态空气率(DAR)和内部温度,并对所提出的设计进行分析研究。本文介绍了一个使用此两阶段流程的示例案例。结果表明,本文提出的方法简单明了,适用于自然通风的策略设计。此外,它还演示了如何使用简化的方法来生成基于自动和行为控制模型的详细和稳健的舒适性数据。实际应用:本文描述了一种两阶段的方法来进行参数化和分析研究的自然通风为夏季降温。该方法简单直接,适用于自然通风的策略性设计。它演示了如何使用简化的方法来生成基于自动和行为控制模型的详细和稳健的舒适数据。
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Strategic design and analysis method of natural ventilation for summer cooling
A simplified coupled thermal and airflow model has been developed by integrating the British Standard natural ventilation calculation method for a single zone within a four-node thermal resistance network model, which is called the thermal resistance ventilation model (TRV). By comparison of the results from the TRV with that of the ESP-r program, and subsequently tuning the TRV parameter values, good correlation can be obtained. A two-stage method is proposed for natural ventilation strategic design and analysis. The first stage calculates the constant air rate (CAR) and performs parametric studies in order to propose a design strategy and the appropriate opening area which satisfies thermal comfort. The second stage calculates the dynamic air rate (DAR) and internal temperature and performs analytic studies of the proposed design. An example case has been introduced using this two-stage process. It shows that the method proposed in this paper is simple and straightforward and it is suitable for the strategic design of natural ventilation. Furthermore, it demonstrates how the simplified method can be used to generate detailed and robust comfort data based on both an automatic and a behavioural control model. Practical appilcation: This paper describes a two-stage method to perform parametric and analytic studies of natural ventilation for summer cooling. This method is simple and straightforward, which is suitable for strategic design of natural ventilation. It demonstrates how the simplified method can be used to generate detailed and robust comfort data based on both automatic and behavioural control models.
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