Abstract

Aneurysms are abnormal expansion of weakened blood vessels which can cause mortality or long-term disability upon rupture. Several studies have shown that inflow conditions spatially and temporally influence aneurysm flow behavior. The objective of this investigation is to identify impact of inflow conditions on spatio-temporal flow behavior in an aneurysm using dynamic mode decomposition (DMD). For this purpose, low-frame rate velocity field measurements are performed in an idealized aneurysm model using particle image velocimetry (PIV). The inflow conditions are precisely controlled using a ViVitro SuperPump system where nondimensional fluid parameters such as peak Reynolds number (Rep) and Womersely number (α) are varied from 50–270 and 2–5, respectively. The results show the ability of DMD to identify the spatial flow structures and their frequency content. Furthermore, DMD captured the impact of inflow conditions, and change in mode shapes, amplitudes, frequency, and growth rate information is observed. The DMD low-order flow reconstruction also showed the complex interplay of flow features for each inflow scenario. Furthermore, the low-order reconstruction results provided a mathematical description of the flow behavior in the aneurysm which captured the vortex formation, evolution, and convection in detail. These results indicated that the vortical structure behavior varied with the change in α while its strength and presence of secondary structures are influenced by the change in Rep.

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