文章摘要
王定标,王光辉,彭旭,向飒.双向扭曲管传热与流阻特性及其多目标优化[J].,2018,17(5):380-386
双向扭曲管传热与流阻特性及其多目标优化
Heat transfer and flow resistance characteristics of bidirectional twisted tube and multi-objective optimization
投稿时间:2017-06-06  修订日期:2017-11-14
DOI:10.13738/j.issn.1671-8097.217051
中文关键词: 双向扭曲管  强化换热  多目标优化  关系式拟合
英文关键词: bidirectional twisted tube  heat transfer enhancement  multi - objective optimization  relation fitting
基金项目:基于流体拓扑优化方法的新型换热器强化传热和流动减阻机理研究,国家自然科学基金项目(面上项目,重点项目,重大项目)
作者单位E-mail
王定标* 郑州大学化工与能源学院 wangdb@zzu.edu.cn 
王光辉 郑州大学化工与能源学院 wanggh9111@163.com 
彭旭 郑州大学化工与能源学院  
向飒 郑州大学化工与能源学院  
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中文摘要:
      以水为工质,对双向扭曲管湍流状态下传热与流阻特性进行数值计算和准确性实验验证,分析了其强化换热机理及截面尺寸a与导程S对其传热流阻的影响,并在其基础上对双向扭曲管结构参数进行多目标优化以及努塞尔数和阻力系数的关系式拟合。结果表明:相同工况下,双向扭曲管的综合换热性能优于光管和扭曲管,在Re小于20000时具有较好的强化效果,且高出扭曲管3.92%;流体旋转流动的方向周期性改变,进一步强化了对流传热;当a增加到一定程度,管内的湍流程度不再增加;相同Re下,PEC、Nu和f对导程S的变化反应较灵敏。在Re=2300~20000,介质为水时,拟合关系式具有较高的准确性,且通过优化得到了结构的最优组合。
英文摘要:
      Using water as the working medium, studying the heat transfer and flow resistance properties of the bidirectional twisted tube in turbulent flow and the accuracy of the experimental verification, analyzing the effect of the heat transfer mechanism and the influence of a and the S on its heat transfer resistance, on the basis of which,multi-objective optimization and relational expression of nusselt number and resistance coefficient are done. The results show that: Under the same conditions, the PEC of bidirectional twisted tube is better than that of the smooth pipe and the twisted tube and higher than the twist tube 3.92%. when Re is less than 20000, it has better strengthening effect; The direction of the fluid rotation flow is periodically changed, the convective heat transfer is further strengthened; When a increases to a certain extent, the degree of turbulence in the tube is no longer increased; In the same Re, PEC ,Nu and f are more sensitive to the change of S; In the case of Re = 2300 ~ 20000, the medium is water, the fitting relation has high accuracy and the optimal combinations of the structure is obtained by optimization
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