Computer modeling of pulsatile blood flow in elastic artery using a software program for application in biomedical engineering. (August 2020) - Sharifzadeh, Bahador; Kalbasi, Rasool; Jahangiri, Mehdi; Toghraie, Davood; Karimipour, Arash
Highlights: k − ω model predicted the collapse of the artery greater than that by the k − ε model. k-ω model predicts a larger part of the post-stenotic region to be disease prone. k − ε model predicted a higher rate of plaque growth. k − ω model predicted a much more intense reverse flow region than the k − ε model. Turbulence model play an important role in predicting the status of atherosclerosis. Abstract: Background and objective: Atherosclerosis-a condition in which an artery is constricted-alters blood flow in the artery, that can exacerbate the condition. Focusing on previous studies, it can be seen that the k-ε model has been used in the simulation. Therefore, the reverse flow on the back of stenosis is not well represented. In this study, the simulated results are much closer to clinical results, relying on the use of physiological pulses, and considering elasticity of the vessel wall, and the applying k-ω model. It can therefore be claimed that a much more accurate prediction will be made regarding the formation, development and progression of the disease. Methods: Modeling biological systems usually contain many parameters, which cannot be calculated experimentally, or are too costly and time consuming. In addition, it is occasionally required to examine the influence of different physical variables, which, given the complexity of the governing equations, make analytical methods feasible (or very limited). The present study is an attempt to investigate the turbulent pulsatile blood flow in an elastic artery with single and double stenoses using a finite element software program, ADINA 8.8. Results: According to the results, the k  − ω turbulence model predicted a larger reverse flow in the post-stenotic region and between the two stenoses in comparison with the k  − ε model. In other words, the k  − ω model results suggest that a larger region is prone to atherosclerosis. In addition, that the k  − ε model predicted a greater maximum shear stress at the throat and a shorter reverse flow region (Mean WSS < 0) in both stenosis scenarios. In other words, relative to the k  − ε model, the k  − ω model underestimated the damage to the plaque and the risk of its rupture though it predicted new stenosis developing behind the previous one. It was observed that the presence of a double stenosis causes the upstream pressure to reach the critical value in less time. Velocity profiles revealed that in the stenosis throat, the maximum velocity exceeds the normal biological state, which may cause disorders in the blood circulation. Conclusions: The artery wall displacement results are suggestive of the greater difference between the two turbulence models in the case with double stenosis compared with single stenosis. Moreover, the difference between the two turbulence models in double stenosis is minimized in both post-stenotic and pre-stenotic regions.