Thermal performance and flow characteristics of methanol based Fe3O4-CoFe2O4-Co3O4 nanofluid systems: numerical and ANN approaches
Arab Journal of Basic and Applied Sciences, cilt.33, sa.1, ss.445-465, 2026 (Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 33 Sayı: 1
- Basım Tarihi: 2026
- Doi Numarası: 10.1080/25765299.2026.2719976
- Dergi Adı: Arab Journal of Basic and Applied Sciences
- Derginin Tarandığı İndeksler: Scopus
- Sayfa Sayıları: ss.445-465
- Anahtar Kelimeler: artificial neural network, convergent-divergent channels, numerical simulation, porous medium, Ternary hybrid nanofluid, thermal exchange
- İstanbul Gelişim Üniversitesi Adresli: Evet
Özet
The study examines the thermal transport and fluid flow characteristics of Fe3O4, CoFe2O4 and Co3O4 nanoparticles suspended in methanol within convergent-divergent channels. This paper investigates two different flow regions: Region I, which considers the presence of radiation and heat generation/absorption mechanisms along with wall expansion-contraction phenomena, and Region II, which incorporates the additional effects of magnetohydrodynamics and porous media. The partial differential equations describing the system are transformed into ordinary differential equations by introducing similarity variables. Numerical solutions are obtained using the Runge-Kutta method, while complex nanofluid dynamic predictions are generated using a hybrid Artificial Neural Network framework. Results demonstrate that when the Reynolds number is doubled, flow velocity increases within converging channels while decreasing in diverging channels, particularly at elevated Hartmann numbers ((Formula presented.)). Increased heat sinks ((Formula presented.)) reduce the maximum temperature, while higher thermal radiation ((Formula presented.)) decreases the temperature profiles. Viscous heating causes the Brinkman number ((Formula presented.)) to increase the temperature in both channels. The ANN model shows greater than 98% accuracy compared with numerical solutions. This paper provides fundamental insights into optimizing hybrid nanofluid thermal performance for applications in microfluidic systems, electronic cooling and energy conversion devices.