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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 TiO 2 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 TiO 2 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.
Seraj et al. (2020) studied this question.