A comprehensive benchmark dataset for the validation of building component heat, air, and moisture (HAM) models

IF 6.1 1区 工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY
Xinyuan Dang, Hans Janssen, Staf Roels
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引用次数: 0

Abstract

Numerical heat, air and moisture (HAM) modeling allows predicting hygrothermal responses of building components with higher efficiency and less effort than laboratory experiments and field measurements. However, inaccuracy and/or incorrectness may appear in the predictions for the same case through different HAM models, primarily due to limitations or deviations in the description of physical phenomena and/or the implementation of mathematical algorithms. User preferences, biases, and/or mistakes with respect to implementing material properties, boundary conditions and other factors may also yield disparity. While a correct implementation of the numerical models is typically verified by the developers, the validity of the HAM models may remain questionable without the confrontation with experimental datasets. However, well-determined criteria and well-documented datasets for establishing the correct prediction of the transient hygrothermal responses of building components by HAM models remain very scarce. To address this issue, a dedicated benchmark experiment was conducted in the hot box-cold box (HB-CB) setup at KU Leuven, Belgium, on four wall assemblies composed of calcium silicate board, mineral wool, wood fiber board, and vapour barrier in different orders. Temperature, relative humidity, heat fluxes and moisture masses, as hygrothermal responses, were monitored under quasi-steady state boundary conditions. Full-scale characterization of the materials from the same batch was performed, along with a determination of the surface transport coefficients within the HB-CB setup. This comprehensive dataset allows a proper model validation by incorporating experimental datasets of material properties and surface transport coefficients and by confronting simulated hygrothermal responses with experimental evidence. In addition, sensitivity analysis can be performed to obtain insights into the impact of uncertainties in characterizing material properties on hygrothermal simulation predictions.

用于验证建筑物热量、空气和湿度(HAM)模型的综合基准数据集
与实验室实验和实地测量相比,数值热量、空气和湿度(HAM)模型可以更高效、更省力地预测建筑组件的湿热反应。然而,主要由于物理现象描述和/或数学算法实施方面的限制或偏差,通过不同的 HAM 模型对相同情况的预测可能会出现不准确和/或不正确的情况。用户的偏好、偏差和/或在执行材料属性、边界条件和其他因素方面的错误也可能造成差异。虽然数值模型的正确实施通常由开发人员验证,但如果不与实验数据集进行对比,HAM 模型的有效性可能仍然值得怀疑。然而,通过 HAM 模型对建筑部件的瞬态湿热响应进行正确预测的既定标准和有据可查的数据集仍然非常缺乏。为了解决这个问题,我们在比利时鲁汶大学的热箱-冷箱(HB-CB)装置中,对由硅酸钙板、矿棉、木纤维板和防潮层按不同顺序组成的四种墙体组件进行了专门的基准实验。在准稳态边界条件下,对温度、相对湿度、热通量和湿气质量等湿热响应进行了监测。对同一批次的材料进行了全尺寸表征,并确定了 HB-CB 设置内的表面传输系数。通过这种全面的数据集,可以结合材料特性和表面传输系数的实验数据集,并将模拟的湿热反应与实验证据进行对比,从而对模型进行适当的验证。此外,还可以进行敏感性分析,以深入了解材料特性表征的不确定性对湿热模拟预测的影响。
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来源期刊
Building Simulation
Building Simulation THERMODYNAMICS-CONSTRUCTION & BUILDING TECHNOLOGY
CiteScore
10.20
自引率
16.40%
发文量
0
审稿时长
>12 weeks
期刊介绍: Building Simulation: An International Journal publishes original, high quality, peer-reviewed research papers and review articles dealing with modeling and simulation of buildings including their systems. The goal is to promote the field of building science and technology to such a level that modeling will eventually be used in every aspect of building construction as a routine instead of an exception. Of particular interest are papers that reflect recent developments and applications of modeling tools and their impact on advances of building science and technology.
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