Fractional Mathematical Modelling of Blood Flow Dynamics in Arterial Segments for The Treatment of Cardiovascular Diseases

Mukhtar Abubakar Maiwada¹ , Adamu Garba Tahiru² , Isah Abdullahi³ , Idris Babaji Muhammad⁴

Section:Research Paper, Product Type: Journal-Paper
Vol.11 , Issue.1 , pp.34-42, Feb-2024

Online published on Feb 28, 2024

Copyright © Mukhtar Abubakar Maiwada, Adamu Garba Tahiru, Isah Abdullahi, Idris Babaji Muhammad . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

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Abstract :
This study presents a comprehensive numerical analysis of electro-magneto-hydrodynamic (EMHD) blood flow through arterial segments with a focus on potential implications for cardiovascular therapeutics. The investigation encompasses the impact of various parameters, including electrokinetic width, particle concentration, chemical reaction, and heat source, on blood velocity, nanoparticle velocity, and concentration profiles. The findings reveal the potential for enhanced targeting and delivery of therapeutic nanoparticles through the manipulation of magnetic fields, indicating promising prospects for targeted drug delivery in cardiovascular disease treatments. Additionally, the complex interplay between chemical reactions and blood flow dynamics underscores the need for a refined understanding of these interactions for potential therapeutic interventions. The study also highlights the significance of considering heat transfer dynamics in EMHD blood flow, offering insights into potential implications for cardiovascular health and disease management. Overall, the numerical analysis provides valuable insights into the rheological behaviour of blood and its potential applications in cardiovascular therapeutics, emphasizing the need for further research in this critical area of study.

Key-Words / Index Term :
Nano Particles, Arterial Segment, Cardiovascular Diseases, Time-Fractional Derivative

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