Abstract
With regards to the current scenario in the biomedical research, the blood flow phenomena are vital due to its vast applications. Further, instead of using traditional fluid the implementation of nanoparticles enhances the flow properties. Therefore, the present article aims to explore how the inclusion of Darcy–Forchheimer inertial drag influences the flow characteristics of electrically conducting blood-based nanofluid, coupled with single-wall carbon nanotubes, between rotating parallel discs set within a permeable medium. The impact of dissipative heat in conjunction with the particle concentration is useful for various applications like drug delivery processes, peristaltic pumping, etc. The flow phenomena governed by the set of equations are distorted into ordinary by the implementation of a suitable similarity rule and then these are handled numerically with the help of Runge–Kutta fourth-order combined with shooting technique. Along with the flow properties, the behaviour of the standard factors involved in the flow properties is discussed briefly. Further, the validation of the result with the earlier investigation is obtained and shows a good agreement. However, the important outcomes of the current investigation are laid down as; the single wall carbon nanotube solid volume fraction combined with the stretching parameter augments the fluid velocity and the resistivity due to the interaction of the magnetic field overshoots the shear rate near the surface significantly.
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All the authors have equally contributed to complete the manuscript, i.e. RB has formulated the problem, SP has verified the problem statement, and completed the introduction section, PKP has computed and simulated the numerical results and finally, SRM checked the similarity with grammar with results and discussion section and checked the overall.
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Baithalu, R., Panda, S., Pattnaik, P.K. et al. Blood-Based CNT Nanofluid Flow Over Rotating Discs for the Impact of Drag Using Darcy–Forchheimer Model Embedding in Porous Matrix. Int. J. Appl. Comput. Math 10, 96 (2024). https://doi.org/10.1007/s40819-024-01733-5
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DOI: https://doi.org/10.1007/s40819-024-01733-5