Efficient Sensitivity Analysis for Enhanced Heat Transfer Performance of Heat Sink with Swirl Flow Structure under One-Side Heating

Ling Tao (), Yuanlai Xie and Chundong Hu
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Ling Tao: School of Energy and Power Engineering, Nanjing University of Science and Technology, Nanjing 210094, China
Yuanlai Xie: Institute of Plasma Physics, Chinese Academy of Sciences, Hefei 230031, China
Chundong Hu: Institute of Plasma Physics, Chinese Academy of Sciences, Hefei 230031, China

Energies, 2022, vol. 15, issue 19, 1-19

Abstract: Excellent heat transfer performance has increasingly become a key issue that needs to be solved urgently in the development process of large-scale fusion equipment. The study of heat transfer performance improvement to scientifically and reasonably determine the design parameters of the high heat flow (HHF) components of fusion reactors based on the efficient in-depth analysis of the heat transfer mechanism and its sensitive factors is of great significance. In this paper, a liquid-vapor two-phase flow model with subcooled boiling for a large length-diameter ratio swirl tube structure in the HHF calorimeter component is proposed to analyze the effects of key design parameters (such as inlet temperature of cooling water flow, swirl tube structure parameters, etc.) on its heat transfer performance. Then, considering the high computational cost of the liquid-vapor two-phase flow model, and in order to improve the efficiency of the sensitivity analysis of these design parameters, the polynomial response surface surrogate model of heat transfer performance function was constructed based on Latin hypercube sampling. On this basis, by combining the proposed surrogate model, the sensitivity index of each design parameter could be obtained efficiently using the Sobol global sensitivity analysis method. This method could greatly improve the calculation efficiency of the design parameter sensitivity analysis of HHF components in the fusion reactor, which provides vital guidance for the subsequent rapid design optimization of related components.

Keywords: swirl tube; sensitivity analysis; response surface method; subcooled boiling; enhanced heat transfer (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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