In this paper, the flow dynamics in the wake of a turbulent annular jet is studied using Time-Resolved Stereoscopic Particle Image Velocimetry and Proper Orthogonal Decomposition (POD). In this wake, a central recirculation zone is present which, under certain conditions, shows a low-frequency precessing motion. POD analysis of the measured velocity data shows that at zero swirl, an asymmetry is present in the wake, which motion is random in time. This asymmetry originates from a bifurcation of the flow once a threshold Reynolds number is exceeded. For low-swirl numbers, ranging from 0 < S < 0.12, the asymmetry is still present and its motion becomes structured into a well defined precession. For S > 0.12, the precession is gone and the motion of the asymmetric wake is again random in time, similar like the non-swirling jet. In this paper, a model is developed to describe the influence of swirl on the wake dynamics. The model assumes that perturbations in the inner shear layer near the bluff body wall are convected towards the stagnation point. These perturbations cause a shift in the stagnation points position. This shift is convected back to the inner shear layer through convection in the recirculating flow. The dynamics of this feedback mechanism can be modeled by the nonlinear delayed saturation model. In this paper, the model is adapted for swirling flow and simulations show that good agreement is found with the experiments.

A 5-year-old castrated male Labrador Retriever was presented to a referring veterinarian for a swelling in the neck region. Based on the results of histopathology, a carotid body tumor, was diagnosed. The dog was referred to a medical imaging unit for further staging and follow up. This report describes the magnetic resonance (MR) and computed tomographic (CT) appearance of a carotid body tumor.

Large scale periodic structures can exist in selected flow fields. Examples are the Precessing Vortex Core in swirling flows, vortex shedding behind a cylinder or the wake of an annular jet. A number of techniques are available to extract these large scales from the turbulent fluctuations in the flow field. In this paper, an analysis is made of three such methods: Eulerian Time Filtering (ETF), Proper Orthogonal Decomposition (POD) and non-linear least-squares regression POD (NLSR-POD). The accuracy of the three different extraction methods is compared quantitatively with phase averaged data of an annular wake flow. This flow was chosen as a test case, since it is widely used in industrial applications, such as for example bluff-body burners. It was shown that all three methods were able to reconstruct the flow field with reasonable accuracy. These techniques are therefore applicable to a number of periodic flows. The big advantage of these extraction methods is that they require 20 times less experimental data compared to phase averaging. All three methods require more or less the same computational time and since the computational time is a few orders of magnitude lower than the measurement time, application of these techniques results in a very large reduction in the total time to obtain the flow field characteristics. This results in a significant reduction of time in the design process of such flows.