Inverse modeling of simplified hygrothermal building models to predict and characterize indoor climates
Inverse modeling of simplified hygrothermal building models to predict and characterize indoor climates
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DOI：
10.1016/j.buildenv.2013.06.001
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发表时间：
2013-10-01
影响因子：
7.4
通讯作者：
Schellen, Henk
中科院分区：
文献类型：
--
作者：
Kramer, Rick;van Schijndel, Jos;Schellen, Henk
对纪念性建筑的计算研究产生了当前使用的详细建筑模型的三个问题：建模繁琐、模拟运行时间相对较长、难以通过模型参数来表征建筑物。提出了一种新的状态空间形式的简化湿热建筑模型，并采用逆建模技术来识别其参数。根据文献综述，开发了 10 个热模型和 5 个湿模型。使用优化例程使模型的输出适合典型纪念性建筑区域的长期每小时测量结果以及通过经过验证的模拟工具模拟的虚构室内气候。通过三个标准评估模型性能并选择最佳模型。所选热和湿模型的验证包括将模型的输出拟合到四个纪念性建筑区域的室内气候测量值、残差分析和参数分析。结果表明，简化的湿热模型能够准确地再现大多数室内气候。此外，状态空间模型可以实现快速模拟：在普通计算机（i5 处理器）上，每小时采样 100 年只需 0.45 秒。参数值的表征和验证具有挑战性，需要额外的测量和研究。 (c) 2013 Elsevier Ltd. 保留所有权利。
Computational research on monumental buildings yields three problems regarding currently used detailed building models: tedious modeling, relatively long simulation run times, difficulties to characterize a building by its model parameters. A new simplified hygrothermal building model in state space form is presented with an inverse modeling technique to identify its parameters. Based on a literature review, 10 thermal models and 5 hygric models were developed. An optimization routine was used to fit the output of the models to long term hourly measurements of a typical monumental building zone and to a fictive indoor climate that was simulated by a validated simulation tool. The model performance was assessed by three criteria and the best models were selected. The validation of the selected thermal and hygric models consisted of fitting the models' output to indoor climate measurements of four monumental building zones, a residual analysis and parameter analysis. The results show that the simplified hygrothermal model is capable of reproducing most indoor climates accurately. Moreover, the state space model results in fast simulations: 100 years with hourly samples was simulated in 0.45 s on an ordinary computer (i5-processor). Characterization and validation of the parameter values are challenging and requires additional measurements and research. (c) 2013 Elsevier Ltd. All rights reserved.