Neural intelligent approach for heat transfer applications of trihybrid cross bio-nanofluid over wedge geometry

Abstract

Significance: Heat transport in the blood within a wedge-shaped artery is significant in biomedical engineering field like develop therapeutic strategies, drug delivery to specific regions of the artery, vicinity of narrowed or blocked arteries and catheter-based treatments such as angioplasty or thermal ablation. Motive: This study investigates the heat transport analysis of trihybrid nanofluid (blood) over wedge-shaped artery with mathematical model of Cross fluid. This study incorporates three nanoparticles, graphene oxide (GO), titanium dioxide (TiO2), and aluminum oxide (Al2O3) in base fluid blood. The wedge-shaped artery is chosen due to its relevance to biomedical applications and it reflects the nature of blood flow in real vascular structures. Heat transport is scrutinized through thermal radiations and flow rate is inspected through inclined magnetic field. Methodology: The bvp4c and Levenberg–Marquardt Neural Network (LM-NN) supervised neural scheme is used to predict the numerical outcome of this study. Findings: Incorporation of nanoparticles made rapid heat transport of blood in wedge-shaped artery. Velocity of blood is decreased with high Weissenberg number and magnetic force. The temperature of a blood in a wedge-shaped artery increases with positive non-uniform heat source/sink parameters and decreases with negative non-uniform heat source/sink parameters.