Numerical study of unsteady stenosis flow: parametric evaluation of power-law model.
Currently the best indicator for surgical treatment of arterio-sclerosis is the degree of stenosis. Although X-ray angiography is currently the standard, cost and morbidity are distinct disadvantages. By modelling stenosis and studying its biofluid mechanics, one can apply its results in the field of arterial disease research. This formed the motivation for this work. A non-Newtonian (power law) incompressible Navier-Stokes (N-S) solver was developed using the method of operator splitting and artificial compressibility. The vehicle used is the computational fluid dynamics (CFD) numerical library FASTFLO. The power-law model developed is then used to do a parametric study of the effect of 'n' on blood flow mechanics where 'n' is the power index that determines the haematocrit of blood. A pulsatile pressure wave over a cardiac cycle of a second was used to simulate transient flow over a hypothetical two-dimensional stenotic geometry. By comparing the different velocity pressure, wall shear stress and viscosity profiles, it has been found when 'n' increases, the vortex formation and peak wall shear stress decreases (magnitudes of < 1.5 Pa). Since the formation of vortices and low oscillatory wall shear stress on the stenotic wall is detrimental to the well-being of the arterial tract, it can therefore be inferred that there might be a relationship between the diseased state of blood (power law) and early genesis of atherosclerosis. However, the conclusion of this paper marks the advent of new research directions in this field of study.
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School of Mechanical and Production Engineering, Nanyang Technological University, 50, Nanyang Avenue, Singapore 639798. mykng@ntu.edu.sg
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D001161:Arteriosclerosis / Q000503:physiopathology*; D001783:Blood Flow Velocity; D003198:Computer Simulation; D003251:Constriction, Pathologic / Q000503:physiopathology; D006400:Hematocrit / Q000379:methods / Q000706:statistics & numerical data; D006801:Humans; D008955:Models, Cardiovascular; D015233:Models, Statistical; D013314:Stress, Mechanical