Artificial neural network analysis for heat and mass transfer in flow with slip conditions

Research about heat and mass transfer is important through its significance for technological and industrial sectors. Here attention is given to magnetohydrodynamic (MHD) flow due to coaxial cylinders. An inner cylinder stretches whereas the outer rotates. Simultaneously effects of heat and mass transfer are taken. Analysis with pollutant concentration for thermal and concentration slip conditions is made. Correct version of velocity slip condition for outer cylinder is utilized. Resulting problems are computed by BVP4c LM-BNNs. This creates a reference dataset for scenario-based, specific cases. For LM-BNNs, the approximate solutions are interpreted in different cases following validation and checking across training testing and validation phase. Importance of LM-BNNs has been assessed from performance measures like Mean Square Error (MSE), correlation index, regression analysis and error histogram. Velocity, temperature and concentration are analyzed.