A simplified dynamic model of building structures integrated with shape-stabilized phase change materials
发布时间：2023-04-22
点击次数：
- 论文类型：
- 文章
- 第一作者：
- 朱娜
- 通讯作者：
- 王盛卫
- 合写作者：
- 徐新华,马贞俊
- 发表刊物：
- International Journal of Thermal Science
- 收录刊物：
- SCI
- 所属单位：
- 香港理工大学
- 刊物所在地：
- India
- 学科门类：
- 工学
- 一级学科：
- 土木工程
- 项目来源：
- Hong Kong Research Grants Council
- 文献类型：
- J
- 卷号：
- 49
- 页面范围：
- 1722-1731
- ISSN号：
- 1290-0729
- 关键字：
- Simplified model; Phase change material; Building structure; Parameter identification; Genetic algorithm
- DOI码：
- 10.1016/j.ijthermalsci.2010.03.020
- 发表时间：
- 2010-09-01
- 影响因子：
- 4.779
- 摘要：
- The use of phase change materials (PCM) to enhance the building energy performance has attracted increasing attention of researchers and practitioners over the last few years. Thermodynamic models of building structures using PCMs are essential for analyzing their impacts on building energy performance at different conditions and using different control strategies. There are few PCM models of detailed physics providing good accuracy in simulating thermodynamic behavior of building structures integrated with PCM layers. However, simplified models with acceptable accuracy and good reliability are preferable in many practical applications concerning computation speed and program size particularly when involving large buildings or models are used for online applications. A simplified physical dynamic model of building structures integrated with SSPCM (shaped-stabilized phase change material) is developed and validated in this study. The simplified physical model represents the wall by 3 resistances and 2 capacitances and the PCM layer by 4 resistances and 2 capacitances respectively while the key issue is the parameter identification of the model. The parameters of the simplified model are identified using genetic algorithm (GA) on the basis of the basic physical properties of the wall and PCM layer. Two GA-based preprocessors are developed to identify the optimal parameters (resistances and capacitances) of the model by frequency-domain regression and time-domain regression respectively. Validation results show that the simplified model can represent light walls and median walls integrated with SSPCM with good accuracy. (C) 2010 Elsevier Masson SAS