Aspects of inclined magnetohydrodynamics and heat transfer in a non‐Newtonian tri‐hybrid bio‐nanofluid flow past a wedge‐shaped artery utilizing artificial neural network scheme

Abstract The incorporation of three distinct nanoparticles in blood within the context of cubic autocatalysis holds significant potential for enhancing biomedical applications, particularly in targeted drug delivery and therapeutic interventions. The increased reaction rate improves the efficiency of catalytic processes within the bloodstream. This research investigates the thermal transport characteristics of a trihybrid Carreau nanofluid (blood) containing copper (Cu), titanium dioxide (TiO 2 ), and aluminum oxide (Al 2 O 3 ), nanoparticles in the context of a wedge‐shaped artery under the influence of autocatalytic cubic autocatalysis. Effects of thermal radiation, and heat generation are used for heat transport analysis, heterogeneous‐homogeneous chemical process included for blood concentration, and an inclined magnetic field is imposed for securitization of blood velocity. Also, the generated PDEs from the physical model are handled through similarity transformations and converted into ODEs. Bvp4c, a numerical technique is used to get the solution and then Levenberg‐Marquardt neural network (LM‐NN), a multilayer neural network scheme is used to train and predict the solution for each parameter. In addition, the numerical values of volumetric friction of coefficients enhance the thermal conductivity, and the heat transport rate is increased. The magnetic parameter, radiation and chemical processes enhance the rate of heat transport while the Weissenberg number reduces the velocity profile.