Prediction of bio-heat and mass transportation in radiative MHD Walter-B nanofluid using MANFIS model

Abstract

This research article discusses the heat and mass transportation of magnetohydrodynamic (MHD) flow of Walter-B nanofluid containing the gyrotactic microorganisms over a curved surface with warm radiation. The mathematical model of the physical flow problem has been formulated, and the analog equations have been normalized into dimensionless equations through similarity practice. The succeeding equations resolved analytically by Homotopy Perturbation Method (HPM) and numerically by Runge–Kutta–Fehlberg’s fourth fifth-order (RKF-45) technique by adopting shooting method via MATLAB and MAPLE software The impacts of various involved parameters on speed, temperature, focus and motile microorganisms of density distributions have been delineated through graphs. The patterns of skin friction coefficient Cfx, Nusselt number (Nux), Sherwood number (Shx) and motile microorganisms’ flux (Nhx) have been examined via tables and graphs. Finally, analyses of Cfx, Nux, Shx and Nhx executed with the aid of Multi output adaptive neuro fuzzy inference system (MANFIS). In MANFIS, the grid partitioning method (GPM) and subtractive clustering method (SCM) have been used to calculate the physical quantities (Cfx, Nux, Shx and Nhx), and the stability analysis has been performed with the assistance of GPM and SCM. The predicted results show that MANFIS-SCM is more accurate and efficient compared to the other existing technique.