Sensitivity analysis and multi-objective optimization of a heat exchanger tube with conical strip vortex generators. (25th July 2017)

• Record Type: Journal Article
• Authors: Zheng, Nianben; Liu, Peng; Shan, Feng; Liu, Zhichun; Liu, Wei
• Is Part Of: Applied thermal engineering. Volume 122(2017)
• Page Start: 642
• Page End: 652
• Publication Date: 2017-07-25
• Subjects: Sensitivity analysis -- Multi-objective optimization -- Conical strip vortex generator -- Thermal-hydraulic performance; Heat engineering -- Periodicals; Heating -- Equipment and supplies -- Periodicals; Periodicals; 621.40205
• DOI: 10.1016/j.applthermaleng.2017.05.046
• Languages: English
• ISSNs: 1359-4311

Abstract

Highlights: A modified conical strip vortex generator was proposed to enhance heat transfer. A sensitivity analysis was carried out. The optimum design parameters was obtained by NSGA-II and TOPSIS. The temperature and flow fields were presented and analyzed. Abstract: 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 = 0.35, 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.