Unsteady flow of a ternary nanofluid over a slow-rotating disk subject to uniform suction and backpropagated neural network

The purpose of the proposed research work is to explore the heat source or sink impact on the unsteady three-dimensional flow of ternary-hybrid nanofluid through a rotating disk. The magnetohydrodynamic flow of ternary-hybrid nanofluid under the impact of radiative heat transfer and uniform suction is also discussed in this study. The partial differential equations of the flow problem are reduced into ordinary differential equations by employing apt similarity transformation and solved numerically using the Runge-Kutta Fehlberg fourth-fifth order method. The various nondimensional parameters' effects on velocity and thermal profiles are illustrated using graphs. In addition, a Levenberg Marquardt backpropagated neural network is employed for determining the Nusselt number and skin friction model. The outcomes of the developed Levenberg Marquardt backpropagated neural network models are indicated through the performance metrics. Result reveals that a rise in the suction parameter decreases the velocity profiles. The thermal profile increases with higher values of thermal radiation and heat source/sink parameters. In addition, the presented Levenberg Marquardt backpropagated neural network models' scheme is found to be a perfect tool for estimating heat transfer and surface drag force models.

Automated summary

The purpose of this research is to investigate the impact of heat source or sink on the unsteady three-dimensional flow of ternary-hybrid nanofluid through a rotating disk. The study also discusses the magnetohydrodynamic flow of ternary-hybrid nanofluid under the influence of radiative heat transfer and uniform suction. Numerical solutions are obtained using the Runge-Kutta Fehlberg method, and the effects of various nondimensional parameters on velocity and thermal profiles are illustrated using graphs. A neural network model is employed to determine the Nusselt number and skin friction, and the results show that it is a reliable tool for estimating heat transfer and surface drag force models.