Blood plasma is potentially considered a non-Newtonian liquid. In this paper, the influence of the melting effect on the radiative flow of micropolar fluid in the presence of blood-based hybrid Cu-CuO nanofluids with the characteristics of heat transport through a moving plate is investigated numerically. Also, the mixed convection towards a stagnation point is incorporated to capture the deviations of cooling/heating.
The leading equations presented in partial differential equations are changed into ordinary differential equations by implementing the similarity factors. These equations are solved through the boundary value problem of a fourth-order solver and the neural network model (NNM) based on the Levenberg–Marquardt backpropagation technique algorithm. The proposed artificial neural networks algorithm was shown to be consistent in all modes, such as testing, training and validation, and it could easily handle nonlinear data with minimal error.
The results indicate that the free-stream velocity is higher than the velocity of the stretching sheet due to the larger values of. On the other hand, the angular velocity profile and temperature profile shrink owing to the bigger change values of. In addition, it is examined that for the higher values of, and the shear stress and the couple-stress coefficient are significantly increased.
Based on the study, there has not been any published research on the impact of melting heat transfer towards buoyancy flow near a stagnation point by incorporating micropolar hybrid nanofluids subject to a movable flat plate. In addition, the Levenberg–Marquardt Backpropagation scheme is employed to find a solution of transformed equations, which is a novel aspect that has not been considered before with these effects. Furthermore, a novel comparison between the numerical values and the predicted values is illustrated in this work to authenticate the proposed scheme.
