Optimization of double-diffusive mixed convection for a hybrid nanofluid system: A numerical and statistical coupled approach
Year: 2026
Type: article
Abstract: There has been a lot of research on nanofluid convection, but not much on the impacts of double-diffusive mixed convection, hybrid nanofluids, and complex geometries like L -shaped cavities using combined statistical and numerical approaches. To fill that important gap, the aim is to investigate the effect of major nondimensional variables Ri , Br , and Le on the system’s performance in terms of heat and mass transfer. To achieve this, a statistical approach using RSM was employed, coupled with numerical computation relayed on the FEM for solving governing equations. The results for the average rate of heat transfer ( Nu avg ) and the average rate of mass transfer ( Sh avg ) exhibit a proportional correlation to Br and Ri , while an inversion was observed for Le . Moreover, the statistical study demonstrates that Nu grows with the increase in Ri and Br but drops for Le , whereas Sh rises with each of the three variables. The Nu avg increases by 9.05% as ϕ hnf is increased from 1% to 4%, but decreases by 17.01% as Le is increased from 0.01 to 10. The statistical assessment of the framework shows high R² values (98.75% for Nu avg and 96.57% for Sh avg ), ensuring the accuracy of the framework in predicting the output. This research gives helpful guidance for improving the transfer of heat and mass in nanofluid industries.
Source: Next Materials
Authors: M. Al-Amin, A.K. Azad, M.S.R. Chowdhury, M.F. Karim, M.M. Rahman
Language: English
Subfield: Biomedical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,280
OpenAlex ID: W7213971548