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室内气候对季节进程的依赖关系以及从长期测量中得出的回归关系。

Dependencies of the indoor climate on the course of the seasons and derivation of regressions from long-term measurements.

机构信息

Fachgebiet Bauphysik/Energetische Gebäudeoptimierung, Technische Universität Kaiserslautern, Kaiserslautern, Germany.

School of Architecture, Wood and Civil Engineering, Bern University of Applied Sciences, Biel 6, Switzerland.

出版信息

Indoor Air. 2022 Jun;32(6):e13058. doi: 10.1111/ina.13058.

Abstract

A building's indoor climate is an essential input variable for a variety of building physics computational models, simulations, and analyses. Precise knowledge of the indoor climate is necessary to minimize the risk of mold or moisture damage and is required to ensure minimum heat insulation standards in buildings. Detailed data are especially necessary for the progressive application of transient calculations, for example, concerning thermal comfort or energy consumption. While the properties of building materials and the (local) outdoor climate are known, only rudimentary information about the dynamic indoor climate is available. Most existing information in the literature about indoor climate is fairly general and forgoes a differentiation between climatic region, occupancy profile, and the utilization of rooms. In this paper, we report on indoor climate measurements in naturally ventilated apartments over a period of 1 year. The measurement results complement the existing data to provide accurate indoor climate data in buildings. The measured values of indoor temperature and relative humidity serve to derive the dew point temperature and moisture load whereby dynamic time-dependent regression functions are determined for these parameters. The evaluations are carried out separately according to room use. The comparison of living rooms and bedrooms indicates a great influence of room use on the indoor climate in residential buildings. The determined indoor climate model can be used for the planning of buildings and simulations. The classification into living rooms and bedrooms makes it possible to take user behavior into account more realistically in building physics simulations. The minimum thermal insulation in residential buildings can also be checked and designed based on realistic data. The prediction interval describes the limits in which residential rooms are free of damage with a high probability. In this way, the indoor climate model describes an approach to examine and evaluate simulation results regarding condensation risk and mold damage in naturally ventilated rooms.

摘要

建筑物的室内气候是各种建筑物理计算模型、模拟和分析的重要输入变量。精确了解室内气候对于降低霉菌或潮湿损坏的风险是必要的,也是确保建筑物达到最低隔热标准的要求。详细的数据对于瞬态计算的逐步应用尤其重要,例如涉及热舒适度或能耗的计算。虽然建筑材料的特性和(当地)室外气候是已知的,但关于动态室内气候的信息却很少。文献中关于室内气候的大多数现有信息都相当笼统,没有区分气候区域、占用情况和房间的使用情况。在本文中,我们报告了自然通风公寓 1 年内的室内气候测量结果。这些测量结果补充了现有数据,为建筑物提供了准确的室内气候数据。测量得到的室内温度和相对湿度值用于推导出露点温度和湿负荷,从而确定这些参数的动态时变回归函数。评估结果根据房间使用情况分别进行。客厅和卧室的比较表明,房间使用情况对住宅建筑室内气候有很大影响。确定的室内气候模型可用于建筑物规划和模拟。将其分类为客厅和卧室可以更真实地考虑用户行为在建筑物理模拟中的影响。也可以根据实际数据检查和设计住宅建筑的最低隔热要求。预测区间描述了住宅房间在很大概率下无损坏的范围。通过这种方式,室内气候模型描述了一种方法,可以检查和评估自然通风房间的冷凝风险和霉菌损坏的模拟结果。

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