Chaotic flow in an aortic aneurysm

Abstract

Oscillatory flow in straight and deformed geometries is seen in various biomedical applications. The nature of flow plays a significant role in the pathogenesis of an abdominal aortic aneurysm. The present study examines the onset of chaotic flow inside a bulged tube under oscillating flow conditions. An experimental facility is set up for generating the oscillatory flow field inside the model. A fusiform shaped model is hollowed out in a rectangular silicone model. A mixture of water and glycerin is used as the working liquid. Two-camera imaging system placed at right angles is used for three-component velocity measurement of a spherical particle inside the model. Images recorded as a time sequence are analyzed by a particle tracking algorithm. The particle trajectories in space and instantaneous velocities within the bulge have been obtained from experiments as well as numerical simulation. The frequency of oscillation considered is 1.2 Hz and the peak Reynolds numbers are in the range of 650–1200 (experiments) and 1000–3500 (simulation). The dimensionless frequency defined by the Womersely number is in the range of 10–12. Velocity signals obtained from the experiment have been analyzed to study chaotic behavior of fluid flow. Chaos is quantified in terms of the largest Lyapunov exponent, positive values being a signature of chaos. The Lyapunov exponent increases with Reynolds number and is significantly higher in the bulged geometry compared to that of the straight tube. The signature of chaotic flow is also seen in power spectra and Poincaré plots.

Oscillatory flow in an enlarged compliant vasculature

“…The LLE was obtained by the Rosenstein's algorithm [35] available in MATLAB. The overall measurement approach is similar to that reported in an earlier study [30].…”

“…Neutrality was checked by ensuring that the particle stayed fixed at a particular position in a stagnant medium, without rising up or descending under its own weight. Under flow conditions, the experimentally recorded particle motion was checked against one recorded in numerical simulation up to Re=3000 in a previous study [30]. The particle trajectory depends on the initial particle position but not the long-time statistics.…”

“…The reduction is due to an increase in the model crosssectional area. The transverse velocities are negligible (<5 mm s −1 ) in a straight tube and are not shown [30].…”

“…A realistic multi-phase blood model is required for clearly understanding pathologically triggered chaotic advection [29]. Flow in a tubular rigid bulge was shown experimentally and numerically to become chaotic under oscillatory flow conditions [30]. A quantitative description of chaotic advection within a vessel of irregular geometry can be specified in terms of positive Lyapunov exponents [31][32][33].…”

Lagrangian Postprocessing of Computational Hemodynamics

“…They argued that the creation of fractal structures by the chaotic flow can lead to an increase in exposure time of platelets along these structures, and the high stretching induced by these regions can enhance platelet activation. Parshar et al [108] quantified chaos with Lyapunov exponents in an idealized aneurysm for different Reynolds number. Maiti et al [87] looked at the effect of blood rheology corresponding to different hematocrit concentrations on the chaotic flow in a stenosis.…”