Optimization of Heat Transfer Coefficient for Al2O3 (75%) – CuO (25%) / Water Hybrid Nanofluid using Taguchi
K. Prashanth Reddy1, Bhramara Panitapu2, Ramesh Chilukuri3, R. Karthikeyan4, A. Kalyan Kumar5

1K. Prashanth Reddy*, Research Scholar, Department of Mechanical Engineering, JNTUH, Hyderabad (Telangana) India.
2Bhramara Panitapu, Professor, Department of Mechanical Engineering, JNTUCEH, Hyderabad (Telangana) India.
3Ramesh Chilukuri, PG, Department of Mechanical Engineering, GRIET, Hyderabad (Telangana) India.
4R. Karthikeyan, Professor, Department of Mechanical Engineering, GRIET, Hyderabad (Telangana) India.
5A. Kalyan Kumar, PG, Department of Mechanical Engineering, GRIET, Hyderabad (Telangana) India.
Manuscript received on November 22, 2019. | Revised Manuscript received on December 15, 2019. | Manuscript published on December 30, 2019. | PP: 2440-2444 | Volume-9 Issue-2, December, 2019. | Retrieval Number:  B3925129219/2019©BEIESP | DOI: 10.35940/ijeat.B3925.129219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: To have the maximum benefits of nanofluid for high heat transfer coefficient, like hybrid composite materials in the material’s revolution, the hybrid nanofluid was prepared and its performance was realized by experimentation. In this investigation, the prepared Al2O3 (75%)– CuO (25%) / Water hybrid nanofluid was used as a coolant for making pen barrel in injection molding machine. For experimentation, the three process parameters viz., Volume Fraction (VF), Volume Flow Rate (VFR) and Temperature (Temp) were controlled and optimized by using Taguchi’s L9 orthogonal array to yield the maximum heat transfer coefficient. To optimize it, total nine different experiments were conducted by controlling these factors. The considered all three parameters were kept three levels. Regression equation was established to predict heat transfer coefficient by incorporating independently controllable process parameters. Based on the optimization result, it was found that the high heat transfer coefficient was achieved at 0.2 %, 6 LPM and 35 °C of VF, VFR and Temp of hybrid nanofluid respectively.
Keywords: Al2O3 – CuO, hybrid nanofluid, heat transfer coefficient, optimization.