Volumen 49,
Ausgabe 10, 2018,
pp. 915-927
DOI: 10.1615/HeatTransRes.2018020335
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Dan Wang
Department of Building Environment and Facility Engineering, College of Architecture and Civil
Engineering, Beijing University of Technology, No. 100 Pingleyuan, Chaoyang District, Beijing
100124, China; Beijing Key Laboratory of Green Built Environment and Energy Efficient Technology, China
Yuying Sun
Department of Building Environment and Facility Engineering, College of Architecture and Civil
Engineering, Beijing University of Technology, No. 100 Pingleyuan, Chaoyang District, Beijing
100124, China; Beijing Key Laboratory of Green Built Environment and Energy Efficient Technology, China
Wei Wang
Department of Building Environment and Facility Engineering, College of Architecture and Civil
Engineering, Beijing University of Technology, No. 100 Pingleyuan, Chaoyang District, Beijing
100124, China; Beijing Key Laboratory of Green Built Environment and Energy Efficient Technology, China
Qingci Guo
Department of Building Environment and Facility Engineering, College of Architecture and Civil
Engineering, Beijing University of Technology, No. 100 Pingleyuan, Chaoyang District, Beijing
100124, China; Beijing Key Laboratory of Green Built Environment and Energy Efficient Technology, China; China Railway Fifth Survey and Design Institute Group Co., Ltd., China
Jingdong Liu
Department of Building Environment and Facility Engineering, College of Architecture and Civil
Engineering, Beijing University of Technology, No. 100 Pingleyuan, Chaoyang District, Beijing
100124, China; Beijing Key Laboratory of Green Built Environment and Energy Efficient Technology, China
ABSTRAKT
Frosting is an undesired phenomenon for air source heat pumps (ASHPs), and numerical correlations are valuable for predicting the dynamic frosting properties. However, the applicable ranges of current correlations greatly deviate from the practical frosting conditions of ASHPs. To solve the above-mentioned problem, this paper develops a set of semiempirical dimensionless correlations under the practical frosting conditions of ASHPs. The sample data is generated from an improved generalized frost formation model. With these data, semiempirical dimensionless correlations are developed by the multiple linear regression method. Frosting properties are regressed as functions of the Reynolds number, Fourier number, relative humidity, and of dimensionless temperature. The proposed correlations are validated by the sample data within an error of ± 10% and examined by experimental data from open literature with good agreements of ± 15%. The results indicate that the proposed semiempirical dimensionless correlations can predict the frosting properties under practical frosting conditions of ASHPs.