建立了适用于大范围几何参数和流动参数的R32制冷剂管内流动沸腾传热和摩擦压降计算关联式.从公开文献中收集了R32传热和摩擦压降的数据源构建两个组合数据库.其中,传热数据库由来自8个文献的1 489个数据点组成,涵盖的水力直径为1~6.3 mm,压降数据库由来自8个文献的496个数据点组成,涵盖水力直径范围为0.643~6 mm.以上述数据库为基础,利用无量纲参数分析预测法并考虑参数主导作用,建立了新的传热系数关联式和摩擦压降关联式.此外,利用现有的关联式对新关联式进行评估.结果表明,现有的几个关联式均具有较大的平均绝对误差(MAE)和最大绝对误差(MAX).而新的传热系数计算关联式具有良好的预测精度,其MAE为14.59%,有90.85%的数据点在±30%误差带以内;新的压降关联式预测精度高,其MAE为17.86%.总之,上述两个新关联式都具有较广的应用范围和良好的预测精度,非常适用于分析工质为R32的换热器的传热和压降性能.

The objective of this study is to establish generalized correlations for R32 flow boiling heat transfer and frictional pressure drop in channels with wide ranges of geometric and flow parameters. In this paper, two consolidated databases for heat transfer and frictional pressure drop were amassed from open literature, which involved R32 as working fluid. The heat transfer database consisted of 1 489 data points from 8 sources, with hydraulic diameters of 1—6.3 mm, while the pressure drop database included 496 data points from 8 sources, which covered hydraulic diameters of 0.643—6 mm. A new heat transfer coefficient correlation and a frictional pressure drop correlation were developed based on the prediction technique of dimensionless parameter analysis considering the governing force effect. Moreover, the existing correlations were also introduced to perform assessment. The validation results show that the existing correlations have poor results of mean absolute errors (MAE) and significantly high maximum absolute errors (MAX), but the new heat transfer coefficient correlation provides a superior prediction accuracy with a MAE of 14.59% and 90.85% of data within ±30% error bands. In addition, the new pressure drop correlation exhibits the best performance, which yields a MAE of 17.86%. The two new correlations have a broad application range and satisfactory prediction accuracy, which are applicable to analyze the heat transfer and pressure drop performance of heat exchangers with refrigerant R32.