A neural network approach to explore bioelectromagnetics aspects of blood circulation conveying tetra-hybrid nanoparticles and microbes in a ciliary artery with an endoscopy span

Abstract

Bioelectromagnetics is gaining remarkableness due to its wide-ranging applications in medical and biochemical industries. Our proposed model delves into the bioelectromagnetics aspects of blood circulation in a scenario involving tetra-hybrid nanoparticles and gyrotactic microbes within a ciliated arterial annulus, particularly one mimicking an endoscopic environment. Our model takes into account influential factors, including cilia beating, buoyancy force, heat source, viscous and Joule warming, arterial wall properties, chemical reaction, and bioconvection. Different geometric shapes of suspended tetra-hybrid nanoparticles (spheres, bricks, cylinders, and platelets) are incorporated into the model formation. The close-form solution of the Poisson equation is found in terms of Bessel’s functions. The homotopy perturbation methodology (HPM) is implemented to track down the rapidly convergent series solutions of the highly non-linear coupled flow equations arising. The hemodynamical attributes of distinct evolving factors on the different dimensionless hemodynamic profiles and entities of interest are elucidated evocatively via a sort of graphs and charts. Our results prove that the factors related to electroosmosis have a dual effect on the blood flow pattern. The bloodstream rapidity is alleviated or boosted for the assisting or opposing electroosmosis process. Cooling of blood within the annulus is achieved with a larger cilia length. The Peclet number positively correlates with the gyrotactic microbes’ density. Blood infused with tetra-hybrid nanoparticles exhibits a superior heat transmission rate across the arterial wall compared to others. Additionally, an artificial neural network (ANN) model, developed using HPM-derived data, accurately predicts shearing stress (SS), achieving high accuracy rates of 99.98% in testing and 100% in validation for MB flow. The model’s new findings could be noteworthy for engineers and medical device designers to develop innovative medical devices and technologies based on bioelectromagnetic principles.