Purpose

In the present study, the thermal performance of engine radiator using conventional coolant and nanofluid is determined experimentally for the different flow rates. Further, the study implemented the Integrated Taguchi-GRA-PCA for optimising the heat transfer performance.

Design/methodology/approach

Nanofluids were prepared by taking ethylene glycol and water (25:75 by volume) with volume fraction of 0.01, 0.03 and 0.05% of TiO₂ nanopowder. Experimental Data were collected based on the design of experiments (DOE) L9 orthogonal array using Taguchi method. Statistical analysis via Grey relation analysis (GRA) and principal component analysis (PCA) were done to determine the role of experimental parameters on heat transfer coefficient and rate of heat transfer. Impact of three control factors, vol. % of TiO₂ concentration (φ), flow rate (LPH), and sonication time (min) on the performance characteristics on heat transfer coefficient and ratio of heat transfer rate is analysed to get the best combination of the parameters involved.

Findings

Analysis revealed the importance of parameters on heat transfer coefficient and can be sorted in terms of contributions from higher to lower degree. Finally, ANOVA test has been conducted to validate the effect of process parameters. The major controllable parameter is φ (concentration), contributing about 32.74%, then flow rate contributing 32.5% and finally sonication time showing small contribution of 18.57%.

Originality/value

A grey relational analysis integrated with principal component analyses (PCA) are implemented to get the optimum heat transfer coefficient and ratio of heat transfer rate. The novelty of the work is to adopt and implement the Integrated Taguchi-GRA-PCA first time for the purpose of thermal performance analysis of engine nano-coolant for radiator.

中文翻译：

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集成Taguchi-GRA-PCA可优化汽车冷却系统中纳米流体的传热性能

目的

在本研究中，通过实验确定了不同流速下使用常规冷却剂和纳米流体的发动机散热器的热性能。此外，该研究还采用了集成Taguchi-GRA-PCA来优化传热性能。

设计/方法/方法

通过取乙二醇和水（体积比为25:75）制备纳米流体，体积分数为0.01、0.03和0.05％的TiO ₂纳米粉。使用Taguchi方法根据实验设计（DOE）L9正交阵列收集实验数据。通过灰色关联分析（GRA）和主成分分析（PCA）进行统计分析，以确定实验参数对传热系数和传热速率的作用。三个控制因素的影响，第一卷。分析了TiO ₂浓度百分比（φ），流速（LPH）和超声处理时间（min）对传热系数和传热率比的性能特性的影响，以得到所涉及参数的最佳组合。

发现

Analysis revealed the importance of parameters on heat transfer coefficient and can be sorted in terms of contributions from higher to lower degree. Finally, ANOVA test has been conducted to validate the effect of process parameters. The major controllable parameter is φ (concentration), contributing about 32.74%, then flow rate contributing 32.5% and finally sonication time showing small contribution of 18.57%.

Originality/value

A grey relational analysis integrated with principal component analyses (PCA) are implemented to get the optimum heat transfer coefficient and ratio of heat transfer rate. The novelty of the work is to adopt and implement the Integrated Taguchi-GRA-PCA first time for the purpose of thermal performance analysis of engine nano-coolant for radiator.