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Review of external convective heat transfer coefficient models in building energy simulation programs: Implementation and uncertainty

机译:建筑能耗模拟程序中外部对流传热系数模型的回顾:实现和不确定性

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Convective heat transfer coefficients for external building surfaces (h_(c,ext)) are essential in building energy simulation (BES) to calculate convective heat gains and losses from building facades and roofs to the environment. These coefficients are complex functions of, among other factors, building geometry, building surroundings, building facade roughness, local air flow patterns and temperature differences. Previous research on h_(c,ext) has led to a number of empirical models, many of which are implemented in BES programs. This paper first provides an extensive overview of such models for h_(c,ext) calculation implemented in BES programs together with the corresponding assumptions. Next, the factors taken into account by each model are listed, in order to clarify model capabilities and deficiencies. Finally, the uncertainty related to the use of these models is discussed by means of a case study, where the use of different models shows deviations up to ±30% in the yearly cooling energy demand (in relation to the average result) and ±14% in the hourly peak cooling energy demand of an isolated, well-insulated building, while deviations in yearly heating energy demand are around ±6%. The paper concludes that each model has a specific range of application, which is identified in this review paper. It also concludes that there is considerable uncertainty in the prediction of h_(c,ext), which can be transferred to the BES results. This large uncertainty highlights the importance of using an appropriate convection model for simulations of a specific building, certainly for calculating cooling demands and related important performance indicators such as indoor temperatures, indoor relatively humidity, thermal comfort, etc.
机译:建筑物外部表面的对流传热系数(h_(c,ext))在建筑能耗模拟(BES)中非常重要,以计算从建筑物外墙和屋顶到环境的对流热损。这些系数是建筑物几何形状,建筑物周围环境,建筑物外墙粗糙度,局部气流模式和温度差异等因素的复杂函数。以前对h_(c,ext)的研究导致了许多经验模型,其中许多是在BES程序中实现的。本文首先提供在BES程序中实现的h_(c,ext)计算模型的广泛概述以及相应的假设。接下来,列出了每个模型考虑的因素,以阐明模型的功能和不足。最后,通过案例研究讨论了与使用这些模型相关的不确定性,其中使用不同的模型显示年度冷却能量需求(相对于平均结果)的偏差最大为±30%,而偏差为±14。隔离的,隔热良好的建筑物的每小时峰值制冷能源需求的百分比,而年度供暖能源需求的偏差约为±6%。本文的结论是,每种模型都有特定的应用范围,本综述文件对此进行了介绍。还得出结论,在h_(c,ext)的预测中存在很大的不确定性,可以将其转移到BES结果中。这种巨大的不确定性凸显了使用合适的对流模型来模拟特定建筑物的重要性,当然这对于计算制冷需求和相关的重要性能指标(例如室内温度,室内相对湿度,热舒适度等)也很重要。

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