Flow condensation heat transfer performance of natural and emerging synthetic refrigerants
Flow condensation heat transfer performance of natural and emerging synthetic refrigerants
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DOI：
10.1016/j.ijrefrig.2021.09.014
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发表时间：
2021-12-03
影响因子：
3.9
通讯作者：
Derby, Melanie M.
中科院分区：
文献类型：
--
作者：
Morrow, Jordan A.;Huber, Ryan A.;Derby, Melanie M.
预测低全球升温潜能值流体的流动凝结换热是一个非常有意义的问题。本文分析了为特定流体开发的通用流动冷凝关联式的有效性，以确定其是否适合预测低GWP流体的传热性能。冷凝传热数据摘自文献，包括19篇论文和1,473个天然制冷剂的数据点[即，氨（R717）、CO2（R744）、丙烷（R290）、异丁烷（R600 a）]和合成制冷剂的35篇论文和5，030个数据点[即，R12、R1234 yf、R1234 ze（E）、R1234 ze（Z）、R22、R32、R41、R123、R125、R134 a、R142 b、R152 a、R161、R404 A、R410 A、R448 A、R449 A、R450 A、R452 B、R454 C、R455 A、R513 A]，包括0.1-11.5 mm的管直径，质量通量为55-1200 kg/m（2）s，饱和温度为-25 ℃-65 ℃。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）和（Chamra等人，2005）和（Kedzierski和Goncalves，1999）用于增强管。由于大多数研究没有报告壁温，直接或间接依赖于壁温的相关性被排除在分析之外。对于合成制冷剂，平均误差（MAE）在6%至257%的范围内，并且（Cavallini等人，2011年）和（Kim和Mudawar，2013年）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R600 a数据的传热性能，但大多数相关性不能准确预测氨和CO2流冷凝。
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 [Le., 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/m(2)s, and saturation temperatures of -25 degrees C-65 degrees 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% to 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.