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Two-Phase Flow Heat Transfer in Micro-Fin Tubes
Heat Transfer Engineering ( IF 1.6 ) Pub Date : 2019-12-23 , DOI: 10.1080/01457632.2019.1703076
Yuansheng Lin 1 , Junye Li 2 , Zengchao Chen 2, 3 , Wei Li 2 , Zhiwu Ke 1 , Hanbing Ke 1
Affiliation  

Abstract An experimental investigation of single-phase and two-phase (evaporation and condensation) heat transfer and pressure drop characteristics is performed for five micro-fin tubes with various geometries using refrigerant R22 as the working fluid. The mass flux is in the range of 130–550 kg/m2s. Evaporation tests are conducted at 6 °C saturation temperature, 0.1 inlet quality and 0.9 outlet quality, while condensation tests are carried out at 45 °C saturation temperature, 0.8 inlet quality and 0.1 outlet quality. The results suggest that the micro-fin tubes single-phase heat transfer coefficients increased by 46.3%–63.6% compared to smooth tubes. Tube geometries that have the best evaporation or condensation heat transfer performance are identified. A new evaporation heat transfer correlation that takes the micro-fin effects and heat transfer mechanisms into consideration is developed, which predicts the experimental data within 15% error compared with the previously reported correlations which show prediction errors beyond 30%. The new model is applied to intermittent and annular flow patterns in micro-fin tubes. As for condensation, the Choi et al. correlation well predicts the pressure drop within 20% error, and the Yu and Koyama correlation provides the best heat transfer predictions within 25% error.

中文翻译:

微型翅片管中的两相流传热

摘要 使用制冷剂 R22 作为工作流体,对具有各种几何形状的五个微翅片管进行了单相和两相(蒸发和冷凝)传热和压降特性的实验研究。质量通量在 130–550 kg/m2s 的范围内。蒸发试验在6℃饱和温度、0.1入口质量和0.9出口质量下进行,而冷凝试验在45℃饱和温度、0.8入口质量和0.1出口质量下进行。结果表明,与光滑管相比,微翅片管单相传热系数提高了 46.3%~63.6%。确定具有最佳蒸发或冷凝传热性能的管几何形状。开发了一种新的考虑了微翅片效应和传热机制的蒸发传热关联式,与之前报道的关联式预测误差超过 30% 相比,该关联式预测实验数据误差在 15% 以内。新模型应用于微翅片管中的间歇和环形流动模式。至于冷凝,Choi 等人。相关性很好地预测了 20% 误差内的压降,Yu 和 Koyama 相关性提供了 25% 误差内的最佳传热预测。至于冷凝,Choi 等人。相关性很好地预测了 20% 误差内的压降,Yu 和 Koyama 相关性提供了 25% 误差内的最佳传热预测。至于冷凝,Choi 等人。相关性很好地预测了 20% 误差内的压降,Yu 和 Koyama 相关性提供了 25% 误差内的最佳传热预测。
更新日期:2019-12-23
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