Heat and Mass Transfer Analysis for Unsteady Three-Dimensional Flow of Hybrid Nanofluid Over a Stretching Surface Using Supervised Neural Networks - Shoaib, Muhammad; Abukhaled, Marwan; Raja, Muhammad Asif Zahoor; Khan, Muhammad Abdul Rehman; Sabir, Muhammad Tauseef; Nisar, Kottakkaran Sooppy; Iltaf, Iqra (Frontiers in Physics, 2022)
Application of hybrid nanomaterial to improve the thermal efficiency of the base fluid has gained the attention of researchers in the past few decades. The prime objective of this research is to explore the flow characteristics along with heat transfer in an unsteady three-dimensional flow of hybrid nanofluid over a stretchable and rotatory sheet (3D-UHSRS). Flow model in the form of PDEs are reduced to set of ODEs by utilizing the appropriate transformations of similarity. Influence of rotation parameter, unsteadiness parameter, stretching parameter, radiation parameter and Prandtl number, Rotation parameter on velocities and thermal profile has been graphically studied. A reference solution in the form of data set points for 3D-UHSRS model are computed with the help of renowned Lobatto IIIA solver and this solution is exported to MATLAB for the proper implementation of proposed solution methodology based on Levenberg–Marquardt Supervised Neural Networks (LM-SNNs). Graphical and numerical results based on mean square error (MSEs), time series response, error distribution plots and regression plots endorse the precision, validity and consistency of the proposed solution methodology. MSE up to the level of 10^-12 confirms the accuracy of the achieved results.