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建筑能耗分析已经成为大部分建筑设计的一个重要环节,为此各类模拟工具被开发用来计算室内热湿环境以及建筑的热负荷。准确的负荷计算应当考虑到建筑围护结构内的热湿耦合传递以及围护结构和环境间的热湿交换,然而在通常的能耗计算中围护结构的湿缓冲效应常常被忽视,这会对模拟结果造成较大误差。本文以Energy Plus为平台,对比分析了3种热湿耦合模型(传递函数模型CTF、热湿耦合传递模型HAMT、有效湿渗透深度模型EMPD)在模拟室内温湿度和预测建筑能耗方面的精确度,并评价了其在3种典型气候下的适用性。结果表明,在湿热气候下,CTF模型由于较短的运算耗时和合理的结果误差可在HAMT模型外被采用;在温和气候下,CTF模型和EMPD模型可根据不同的换气次数应用于快速模拟过程,换气次数较小时EMPD模型的模拟误差更小,而CTF模型在高换气次数下更适用;在干热气候下,建筑材料的湿缓冲效应十分有限,运算速度成为影响适用性的主导因素,此时CTF模型最为合适。
Building energy analysis has become an important part of most architectural designs. For this reason, various types of simulation tools have been developed to calculate indoor thermal and humid environments and the heat load of buildings. Accurate load calculations should take into account the transfer of heat and moisture within the building envelope and the heat and moisture exchange between the envelope and the environment. However, in the usual calculation of energy consumption, the wet buffer effect of the envelope is often neglected. A large error in the simulation results. This paper uses Energy Plus as a platform to compare and analyze the accuracy of the three heat and moisture coupling models (transfer function model CTF, heat and moisture transfer model HAMT, and effective wet penetration depth model EMPD) in simulating indoor temperature and humidity and predicting building energy consumption. , and evaluated its applicability in three typical climates. The results show that under the hot and humid climate, the CTF model can be used outside the HAMT model due to the short time-consuming operation and reasonable results. In mild climates, the CTF model and the EMPD model can be applied to fast according to different ventilation times. In the simulation process, when the number of air changes is small, the simulation error of the EMPD model is smaller, and the CTF model is more applicable under the high ventilation rate; in the dry and hot climate, the wet buffering effect of the building material is very limited, and the calculation speed becomes the impact applicability. Dominant factors, the CTF model is most appropriate at this time.