Fluid-solid interaction analysis of blood flow in the atherosclerotic carotid artery using the Eulerian-Lagrangian approach

This study aims to simulate pulsatile blood flow in the carotid artery with different stenosis severities and pulse rates. The effects of different severities of stenosis, pulse rates, and arterial wall properties on the surrounding fluid are investigated by using fluid-structure interaction (FSI) and arbitrary Lagrangian-Eulerian (ALE) methods. Carreau-Yasuda non-Newtonian and modified Mooney-Rivin hyperelastic models are applied for blood with non-Newtonian behavior and hyperelastic blood vessel’s wall, respectively. Results are presented in terms of wall radial displacement, pressure distribution, the axial velocity profile, and wall shear stress for blood. By increasing the stenosis severities, there would be a change in several parameters. Axial velocity, variation of blood pressure, the maximum wall shear stress, and wall radial displacement experience a growth. Furthermore, when the pulse rate grows in the stenosis severity of 75%, the maximum flow rate moments, maximum values for wall radial displacement, pressure, axial velocity, and wall shear stress increase as well. Using a hyperelastic model for the arterial wall, as opposed to elastic and rigid models, and treating the surrounding fluid as non-Newtonian and unsteady, allows us to achieve a more realistic simulation. In the stenosis having up to 50% of severity, red blood cells are under the enforcement of insignificant damage, while hemolysis is observed in the severe stenosis of 75%. By improving atherosclerosis, which leads to the development of elastic modulus from 500 kPa to 2 MPa, the 65% growth of the maximum value of shear stress at 60 bpm pulse rate and in the stenosis with 75% severity has been noticed. It can be demonstrated that hyperelastic models of the arterial walls lead to lower axial velocity, lower blood pressure, lower shear stress, and higher radial displacement, as opposed to rigid and elastic arterial walls.