Citation

Kadirgama, G. and Ramasamy, D. and Kadirgama, K. and Samylingam, L. and Aslfattahi, Navid and Chalak Qazani, Mohammad Reza and Kok, Chee Kuang and Yusaf, Talal and Schmirler, Michal (2025) Characterization and machine learning analysis of hybrid alumina-copper oxide nanoparticles in therminol 55 for medium temperature heat transfer fluid. Scientific Reports, 15 (1). ISSN 2045-2322

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Abstract

Efficient heat dissipation is crucial for various industrial and technological applications, ensuring system reliability and performance. Advanced thermal management systems rely on materials with superior thermal conductivity and stability for effective heat transfer. This study investigates the thermal conductivity, viscosity, and stability of hybrid Al2O3-CuO nanoparticles dispersed in Therminol 55, a medium-temperature heat transfer fluid. The nanofluid formulations were prepared with CuO-Al2O3 mass ratios of 10:90, 20:80, and 30:70 and tested at nanoparticle concentrations ranging from 0.1 wt% to 1.0 wt%. Experimental results indicate that the hybrid nanofluids exhibit enhanced thermal conductivity, with a maximum improvement of 32.82% at 1.0 wt% concentration, compared to the base fluid. However, viscosity increases with nanoparticle loading, requiring careful optimization for practical applications. To further analyze and predict thermal conductivity, a Type-2 Fuzzy Neural Network (T2FNN) was employed, demonstrating a correlation coefficient of 96.892%, ensuring high predictive accuracy. The integration of machine learning enables efficient modeling of complex thermal behavior, reducing experimental costs and facilitating optimization. These findings provide insights into the potential application of hybrid nanofluids in solar thermal systems, heat exchangers, and industrial cooling applications.

Item Type:	Article
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK4601-4661 Electric heating
Divisions:	Faculty of Engineering and Technology (FET)
Depositing User:	Ms Suzilawati Abu Samah
Date Deposited:	10 Apr 2025 03:19
Last Modified:	10 Apr 2025 03:19
URII:	http://shdl.mmu.edu.my/id/eprint/13679

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