In this paper, we study the unsteady magnetohydrodynamic (MHD) flow and the heat and mass transfer of a Williamson tri-hybrid nanofluid (THNF) composed of water and Al$_2$O$_3$, TiO$_2$ and Cu nanoparticles over a stretching sheet. The model incorporates thermal radiation, activation energy, chemical reaction, a heat s...
Abdul Hafeez, Javed Khan, Xiao Ying· ICCK Journal of Applied Math...· 0 citations
Artificial neural network (ANN) techniques have emerged as powerful data-driven tools for their effectiveness in analysis, modeling, and simulation. These supervised learning approaches are designed to reduce the error between predicted and observed data, providing accurate approximations of complex physical systems. T...
Haider Ali, Aaqib Majeed, T. Saidani et al.· Discover Nano· 0 citations
This study uses an artificial neural network (ANN) architecture in combination with the Levenberg-Marquardt backpropagation (LMBP) method to investigate the impact of heat radiation on the hybrid nanofluid flow through a variable porous medium beneath a stretchy Riga plate. The purpose of this work is driven by the inc...
Shajar Abbas, Syeda Farzeen Fatima Gilani, I. Siddique et al.· Discover Nano· 0 citations
This study aims to numerically investigate steady two-dimensional MHD Darcy–Forchheimer mixed convection flow of a Boger nanofluid (Cu/H2O) with coupled heat and mass transfer inside a Y-shaped hourglass cavity containing a cylindrical obstacle, incorporating thermal radiation, Cattaneo–Christov heat flux, Soret ef...
Faisal, Qadeer Raza, Zainab Bibi et al.· International Journal of Num...· 0 citations
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