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Flow diverting stents are deployed to reduce the blood flow into the aneurysm, which would thereby induce thrombosis in the aneurysm sac; the stents prevent its rupture. The present study aimed to examine and quantify the impacts of different flow stents on idealized configurations of the cerebral artery. In our study, we considered a spherical sidewall aneurysm located on curved and tortuous idealized artery vessels and three stents with different porosities (70, 80 and 90%) for deployment. Using computational fluid dynamics, the local hemodynamics in the presence and absence of the stents were simulated, respectively, under the assumption that the blood flow was unsteady and non-Newtonian. The hemodynamic parameters, such as the intra-aneurysmal flow, velocity field and wall shear stress and its related indices, were examined and compared among the 12 cases simulated. The results illustrated that with the stent deployment, the intra-aneurysmal flow and the wall shear stress and its related indices were considerably modified depending on both stent and aneurysm/artery geometries, and that the intra-aneurysmal relative residence time increased rapidly with decreasing stent porosity in all the vessel configurations. These results also inform the rationale for selecting stents for treating aneurysms of different configurations.

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At low Reynolds numbers, the flow through a pipe with a sudden expansion is characterized by the localized occurrence of flow instabilities, with the formation of a so-called turbulence puff. In the literature, physical experiments typically predict earlier occurrence of turbulence than computational fluid dynamics simulations. However, the behaviour of ‘natural’ transition to turbulence without perturbations, and the dependence of transition to turbulence on perturbations, are not yet fully understood, particularly for the simulations. The purpose of the present study is therefore to investigate this flow, including possible sources of perturbation in numerical simulations, and to evaluate their effect on transition to turbulence. Through the exploration of different flow rates, numerical settings and inlet perturbation amplitudes, and by evaluating coarse and refined simulations, insights into low-Reynolds-number transitional turbulent flows are obtained. The turbulence kinetic energy budget of the turbulence puff or slug characteristic of this flow is also evaluated. In conclusion, even when perturbations are not intentionally added, there can still be significant sources of numerical perturbation and error that trigger turbulence in simulations, but perturbations will need to be added in refined simulations in order to produce turbulence. Finally, the results agree with the notion that there may not be a scenario where the flow transitions naturally to turbulence without any perturbation.