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  • 中国标准连:ISSN1005-2895
  • 续出版物号: CN 33-1180/TH
  • 主管单位:轻工业杭州机电设计研究院有限公司
  • 主办单位:轻工业杭州机电设计研究院有限公司、中国轻工机械协会、中国轻工业机械总公司
  • 社  长:刘安江
  • 主  编:黄丽珍
  • 地  址:杭州市余杭区高教路970号西溪联合科技广场4-711
  • 电子邮件:qgjxzz@126.com
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李庆普, 陶乐仁, 毛舒适, 吴生礼.水平圆管内R410A的凝结换热特性研究[J].轻工机械,2018,36(3):67-72
水平圆管内R410A的凝结换热特性研究
Study of Flow Condensation Heat Transfer Characteristics of R410A in Horizontal Circular Tube
  
DOI:10.3969/j.issn.1005 2895.2018.03.013
中文关键词:  空调系统  制冷剂R410A  流动冷凝  换热系数  压降  关联式
英文关键词:air conditioning system  refrigerants R410A  flow condensation  heat transfer coefficient  pressure drop  correlation
基金项目:
作者单位
李庆普, 陶乐仁, 毛舒适, 吴生礼 上海理工大学 能源与动力工程学院 上海200093 
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中文摘要:
      在一管内冷凝换热实验台上进行R410A流动冷凝换热实验,旨在研究水力工况、测试管管径对管内换热特性的影响进行探究。实验选用测试水雷诺数表征 水力工况,选取换热系数、压降作为管内换热特性的衡量指标;并将实验数据与经典关联式预测值进行比较,扩展关联式的适用范围。实验结果显示:换热系数 及压降均随着质量流速的增加、管径的减小逐渐增大,虽然换热系数随着测试水雷诺数的增加而减小,但测试水雷诺数对压降影响很小;Shah关联式和Thome关 联式能够较好的预测实验数据,平均预测误差分别为18.83%和6.28%,而Akers关联式的预测值的平均误差达31.04%,足以证明其并不能准确预测实验数据。
英文摘要:
      To study the effect of hydraulic conditions and inner diameter of the test tube on the heat transfer characteristics inside the tube, the experiment of flow condensation heat transfer of R410A was operated on an internal condensation heat transfer experiment platform. Water testing Re was used to characterize the hydraulic conditions, heat transfer coefficient and pressure drop were selected as the measurement indexes in the experiment. The experimental data was also compared with the predictive value of some correlations in the experiment, extending the range of correlations application. Experimental results show: heat transfer coefficient and pressure drop increase with increasing mass flow and decreasing inner diameter of the test tube, although the heat transfer coefficient decreases with increasing water testing Re, water testing Re has a small influence on the pressure drop. The correlations of Shah and Thome can better predict the experimental data with average predictive error 18.83% and 6.28%, respectively; however, the average predictive error of Akers correlation reaches up to 31.04%, which is enough to prove that it does not accurately predict the data.
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