An experimental and optimization of heat transfer between two-disk systems

IF 1.8 4区 工程技术 Q3 ENGINEERING, MECHANICAL
Rakesh Kumar Yadu, Achhaibar Singh, Dinesh Kumar Singh
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Abstract

This research focuses on experimentally investigating and optimizing heat transfer between two parallel disks, a prevalent system extensively utilized in engineering devices and various machinery. Analyzing heat transfer in this configuration is of paramount interest to researchers and engineers. An experimental setup was built to explore heat transfer between two parallel disks. Local Nusselt number and average Nusselt number were calculated to analyze heat transfer characteristics. The study delved into the effects of vital parameters such as the gap ratio, Reynolds number, and heat flux on heat transfer between two parallel disks. The analysis revealed that the Nusselt number increases with an increase in the gap between two disks up to a certain level, beyond which an inverse effect is observed. Moreover, the Nusselt number demonstrates a positive correlation with the Reynolds number. An in-depth analysis of local and average Nusselt numbers indicated that heat flux initially has a positive effect, followed by an adverse effect after reaching a certain level. To ascertain the optimum solution, three different techniques were employed: Response Surface Method (RSM), Cuckoo Search Algorithm (CS), and Genetic Algorithm (GA). The predicted optimum values for the gap ratio, Reynolds number, and heat flux using GA, CS, and RSM were as follows: gap ratio (17.36, 17.36, and 17.36), Reynolds number (100, 100, and 98.2), and heat flux (689.36, 694.5, and 682.449), respectively. Correspondingly, the resulting average Nusselt numbers were projected to be 48.59, 48.36, and 48.5271. To validate the obtained results, experiments were conducted and compared with the predicted values. The comparison among these techniques indicated that all results fell within an acceptable margin of error. Specifically, RSM exhibited an error of 1.917%, CS showed an error of 0.962%, and GA displayed an error of 0.8931%.
双盘系统间热传递的实验与优化
这项研究的重点是通过实验研究和优化两个平行盘之间的传热,这是一种广泛应用于工程设备和各种机械的普遍系统。分析这种配置下的热传递是研究人员和工程师最感兴趣的问题。我们建立了一个实验装置来探索两个平行盘之间的热传递。通过计算局部努塞尔特数和平均努塞尔特数来分析传热特性。研究深入探讨了间隙比、雷诺数和热通量等重要参数对两个平行盘之间热传递的影响。分析结果表明,努塞尔特数随着两个盘之间间隙的增大而增大,直至达到一定程度,超过一定程度后会出现反向效应。此外,努塞尔特数与雷诺数呈正相关。对局部努塞尔特数和平均努塞尔特数的深入分析表明,热通量最初具有正效应,达到一定水平后会产生负效应。为了确定最佳解决方案,采用了三种不同的技术:响应面法(RSM)、布谷鸟搜索算法(CS)和遗传算法(GA)。采用 GA、CS 和 RSM 预测的间隙比、雷诺数和热通量的最佳值分别为:间隙比(17.36、17.36 和 17.36)、雷诺数(100、100 和 98.2)和热通量(689.36、694.5 和 682.449)。相应地,推算出的平均努塞尔特数分别为 48.59、48.36 和 48.5271。为了验证所获得的结果,进行了实验并与预测值进行了比较。这些技术之间的比较表明,所有结果都在可接受的误差范围内。具体来说,RSM 的误差为 1.917%,CS 的误差为 0.962%,GA 的误差为 0.8931%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
3.80
自引率
10.00%
发文量
625
审稿时长
4.3 months
期刊介绍: The Journal of Mechanical Engineering Science advances the understanding of both the fundamentals of engineering science and its application to the solution of challenges and problems in engineering.
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