There is great interest in predicting flow condensation heat transfer for lower global warming potential (GWP) fluids. This paper analyzes the efficacy of common flow condensation correlations developed for particular fluids in order to identify their suitability to predict heat transfer performance of low GWP fluids. Condensation heat transfer data were extracted from the literature, including 19 papers and 1,473 data points for natural refrigerants [i.e., ammonia (R717), CO₂ (R744), propane (R290), isobutane (R600a)] and 35 papers and 5,030 data points for synthetic refrigerants [i.e., R12, R1234yf, R1234ze(E), R1234ze(Z), R22, R32, R41, R123, R125, R134a, R142b, R152a, R161, R404A, R410A, R448A, R449A, R450A, R452B, R454C, R455A, R513A] encompassing tube diameters of 0.1–11.5 mm, mass fluxes of 55–1200 kg/m²s, and saturation temperatures of -25°C–65°C. Correlations analyzed included Akers et al. (1959), Cavallini et al. (2006, 2011), Kim and Mudawar (2013), Macdonald and Garimella (2016), Shah (1979, 2009, 2013, 2016) and Traviss et al. (1973) for smooth tubes and Chamra et al. (2005) and Kedzierski and Goncalves (1999) for enhanced tubes. Since most studies did not report wall temperature, correlations which relied on wall temperature directly or indirectly were excluded from the analysis. For synthetic refrigerants, mean average error (MAE) ranged from 6%–257%, and Cavallini et al. (2011) and Kim and Mudawar (2013) were the best predictors for emerging synthetic refrigerants. The Kim and Mudawar (2013) correlation was found to best predict the heat transfer performance for propane and R600a data, but most correlations did not accurately predict ammonia and CO₂ flow condensation.

人们对预测较低全球变暖潜势 (GWP) 流体的流动冷凝传热非常感兴趣。本文分析了为特定流体开发的常见流动冷凝相关性的功效，以确定它们对预测低 GWP 流体传热性能的适用性。冷凝传热数据是从文献中提取的，包括 19 篇论文和 1,473 个天然制冷剂数据点 [即氨 (R717)、CO ₂ (R744)、丙烷 (R290)、异丁烷 (R600a)] 和 35 篇论文和 5,030 个数据合成制冷剂的点 [即，R12、R1234yf、R1234ze(E)、R1234ze(Z)、R22、R32、R41、R123、R125、R134a、R142b、R152a、R161、R404A、R445A、R445A、R454B , R454C, R455A, R513A] 包括直径为 0.1–11.5 mm、质量通量为 55–1200 kg/m 的管²s 和 -25°C–65°C 的饱和温度。分析的相关性包括 Akers 等人。(1959)，Cavallini 等人。（2006、2011）、Kim 和 Mudawar（2013）、Macdonald 和 Garimella（2016）、Shah（1979、2009、2013、2016）和 Traviss 等人。(1973) 用于光滑管和 Chamra 等人。(2005) 以及 Kedzierski 和 Goncalves (1999) 用于增强管。由于大多数研究没有报告壁温，因此分析中排除了直接或间接依赖于壁温的相关性。对于合成制冷剂，平均误差 (MAE) 范围为 6%–257%，Cavallini 等人。(2011) 和 Kim 和 Mudawar (2013) 是新兴合成制冷剂的最佳预测指标。发现 Kim 和 Mudawar (2013) 相关性最能预测丙烷和 R600a 数据的传热性能，₂流冷凝。