Hybrid nanocomposites impact on heat transfer efficiency and pressure drop in turbulent flow systems: application of numerical and machine learning insights

• Published in: Scientific reports Vol. 14; no. 1; pp. 19882 - 22
• Main Authors: Tao, Hai, Aldlemy, Mohammed Suleman, Homod, Raad Z., Aksoy, Muammer, Mohammed, Mustafa K. A., Alawi, Omer A., Togun, Hussein, Goliatt, Leonardo, Khan, Md. Munir Hayet, Yaseen, Zaher Mundher
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 27.08.2024; Nature Publishing Group; Nature Portfolio
• Subjects: 639/166/988; 639/705/1042; 639/766/189; Flow system; Fluid dynamics; Fluid flow; Graphene nanoplatelets (GNPs); Heat transfer; Humanities and Social Sciences; Hydrodynamics; Machine learning; Multi-walled carbon nanotubes (MWCNTs); multidisciplinary; Nanocomposites; Nanotechnology; Nanotubes; Neural networks; Pressure drop; Science; Science (multidisciplinary); Transfer learning; Turbulent flow; Multi-walled carbon nanotubes (MWCNTs); Graphene nanoplatelets (GNPs); Turbulent flow; Pressure drop; Heat transfer; Machine learning
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-024-69648-1

This research explores the feasibility of using a nanocomposite from multi-walled carbon nanotubes (MWCNTs) and graphene nanoplatelets (GNPs) for thermal engineering applications. The hybrid nanocomposites were suspended in water at various volumetric concentrations. Their heat transfer and pressure drop characteristics were analyzed using computational fluid dynamics and artificial neural network models. The study examined flow regimes with Reynolds numbers between 5000 and 17,000, inlet fluid temperatures ranging from 293.15 to 333.15 K, and concentrations from 0.01 to 0.2% by volume. The numerical results were validated against empirical correlations for heat transfer coefficient and pressure drop, showing an acceptable average error. The findings revealed that the heat transfer coefficient and pressure drop increased significantly with higher inlet temperatures and concentrations, achieving approximately 45.22% and 452.90%, respectively. These results suggested that MWCNTs-GNPs nanocomposites hold promise for enhancing the performance of thermal systems, offering a potential pathway for developing and optimizing advanced thermal engineering solutions.