4.7 Article

Sensitivity analysis and multi-objective optimization of a heat exchanger tube with conical strip vortex generators

期刊

APPLIED THERMAL ENGINEERING
卷 122, 期 -, 页码 642-652

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.applthermaleng.2017.05.046

关键词

Sensitivity analysis; Multi-objective optimization; Conical strip vortex generator; Thermal-hydraulic performance

资金

  1. National Key Basic Research Program of China (973 Program) [2013CB228302]
  2. National Natural Science Foundation of China [51376069, 51606073]

向作者/读者索取更多资源

This paper exhibited the results of sensitivity analysis and multi-objective optimization of a heat exchanger tube with conical strip vortex generators. The design parameters included the Reynolds number (Re), the conical strip filling ratio (C) and the pitch ratio (P*), and the objective functions were the Nusselt number ratio and the friction factor ratio. The main aim of this study was to identify the optimum design parameters for the maximum heat transfer enhancement with the minimum pressure drop augmentation. Response Surface Methodology (RSM) was, firstly, applied to approximate objective functions. Based on RSM, sensitivity analyses of the responses to design parameters were carried out. Results indicated that both the heat transfer rate and the pressure drop increased with an increment in the conical strip filling ratio and Reynolds number and a reduction in the pitch ratio, but the pressure drop was more sensitive to these design parameters compared to the heat transfer rate. Furthermore, the Non dominated Sorting Genetic Algorithm II (NSGA-II) was employed to optimize the objective functions, and the most compromising solution (i.e. Re = 1468, C= 035, and P* = 3.97) was finally selected from the Pareto front attained by the multi-objective optimization. The associated Nusselt number ratio and friction factor ratio for this solution were 6.56 and 7.07, respectively. The findings of this work may provide practical guidelines for researchers to design efficient heat exchangers. (C) 2017 Elsevier Ltd. All rights reserved.

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