干旱区生态环境知识资源中心(Arid): Performance prediction and optimization of cross-flow indirect evaporative cooler by regression model based on response surface methodology

Arid

DOI	10.1016/j.energy.2023.128636
	Performance prediction and optimization of cross-flow indirect evaporative cooler by regression model based on response surface methodology
	Shi, Wenchao; Yang, Hongxing; Ma, Xiaochen; Liu, Xiaohua
通讯作者	Shi, WC
来源期刊	ENERGY
ISSN	0360-5442
EISSN	1873-6785
出版年	2023
卷号	283
英文摘要	In recent years, indirect evaporative cooling has rapidly developed with high-accuracy numerical models. As the application of this technology expands from hot-arid areas to hot-humid regions, there is still a lack of regression models of the cross-flow indirect evaporative cooler (IEC) that can be used in different climate regions. Regression models can not only improve prediction efficiency but also be helpful for engineering design. In this study, the regression models of the cross-flow IEC were established based on the response surface methodology (RSM). Eight essential factors, including the inlet air properties, geometric size, and operating parameters, were determined as the input factors, while five indicators were selected as the output responses. The central composite design was employed to generate the matrix for the RSM-based model, and the matrix response data were obtained from an established numerical IEC model validated by the experimental results. The effects of the single and interactive factors are analyzed for each response. Furthermore, the developed models are evaluated by comparing the anticipated results with the on-site measurement data in a real project, and then the multiobjective optimization is conducted for the prediction of IEC performances in five typical cities of China. In summary, the regression models can forecast the cross-flow IEC in a more straightforward approach, which may also assist the design and optimization.
英文关键词	Air conditioning Indirect evaporative cooling Response surface methodology Performance prediction Optimization
类型	Article
语种	英语
收录类别	SCI-E
WOS记录号	WOS:001060178400001
WOS关键词	CONDENSATION
WOS类目	Thermodynamics ; Energy & Fuels
WOS研究方向	Thermodynamics ; Energy & Fuels
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/396066
推荐引用方式 GB/T 7714	Shi, Wenchao,Yang, Hongxing,Ma, Xiaochen,et al. Performance prediction and optimization of cross-flow indirect evaporative cooler by regression model based on response surface methodology[J],2023,283.
APA	Shi, Wenchao,Yang, Hongxing,Ma, Xiaochen,&Liu, Xiaohua.(2023).Performance prediction and optimization of cross-flow indirect evaporative cooler by regression model based on response surface methodology.ENERGY,283.
MLA	Shi, Wenchao,et al."Performance prediction and optimization of cross-flow indirect evaporative cooler by regression model based on response surface methodology".ENERGY 283(2023).