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Experimental investigation and optimization of heat pipe heat exchanger performance under two distinct heat transport mediums through TOPSIS approach

热交换器 板翅式换热器 热管 微型热交换器 板式换热器 热撒布器 机械工程 材料科学 散热片 热力学 动态刮削表面换热器 机械 传热 工程类 传热系数 物理 临界热流密度
作者
Ramasamy Sethuraman,Thambidurai Muthuvelan,Sivasubramanian Mahadevan,S. Raman
出处
期刊:Engineering research express [IOP Publishing]
卷期号:6 (2): 025518-025518 被引量:1
标识
DOI:10.1088/2631-8695/ad3d30
摘要

Abstract This paper presents a comprehensive thermal performance analysis of the heat pipe heat exchanger by varying the input process parameters and optimizing the best condition for waste heat recovery through the TOPSIS technique. In this work, the heat pipe is constructed with a copper tube and segmented into evaporator and condenser sections carrying hot and cold fluids with a half-fill ratio. The heat pipe is oriented in 0° horizontally with the wick material made from stainless steel and works based on the capillary principle. The efficiency of the HPHE is evaluated by varying the input operational parameters, namely heat input, mass flow rate of hot fluid, inlet temperature of hot fluid, and mass flow rate of cold fluid, on response variables, specifically thermal resistance, energy balance ratio, universal heat transfer coefficient, and effectiveness. The experiment was designed for four factors at three levels as per Taguchi’s L27 orthogonal array, and the best optimising condition was determined by employing the multi-objective technique for order preference by similarity to ideal solution (TOPSIS) approach. The best input condition found was A3B1C1D3, in which the heat input was at 90 W, the mass flow rate of hot fluid was at 0.2 kg min −1 , the mass flow rate of cold fluid was at 0.1 kg min −1 , and the inlet temperature was at 60 °C. The effect of process parameters and their significance on output responses was analysed by executing an analysis of variance (ANOVA) statistical method. The mathematical regression model was generated, and validation was made to investigate the prediction error percentage.

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