<p>Cavitation is ubiquitous in nature and scientific application where it might hinder through noise, vibration or erosion which eventually leads to reduced performance. Similarly, rising bubbles are employed in several industrial applications to homogenize the fluid. This thesis sheds light on special applications of these two phenomena. </p> <p>Once a bubble has been captured by a vortex core, the low (sometimes negative) pressure in the core causes the cavitation bubble to elongate axially while the radius of the bubble oscillates with time. Three dimensional compressible Navier-Stokes equations with surface tension are numerically solved using an all-mach solver on Basilisk software. The bubble dynamics can be categorised into separate stages: spherical growth, pinching, elongation and fragmentation. As the cylindrical bubble grows, it increases the vortex core radius. The flow and the bubble dynamics are strongly coupled. The effect of changing cavitation number and bubble to vortex size ratio has been explored. The bubble sizes and dynamics at different time steps have also been recorded. When the pressure in the core is negative, the bubble continues to grow axially forming a long tube, which is also observed in experiments. In oceans, density varies with depth due to varying salinity and temperature gradient, which prevents the vertical exchange of heat, carbon, dissolved oxygen, and nutrients as well as blooms the population of harmful bacteria such as cyanobacteria. The rising motion of a single or cluster of bubbles creates an upflow that can cause homogenization or destratification. Confined bubble columns are used for microelectronic cooling as well as in chemical reactors for mixing stratified fluids without any mechanical agitation or power. To begin realizing this complex multi-phase flow system to better understand mixing, we start with a simplified problem of a single air bubble rising in a confined Hele-Shaw channel. We performed a time-resolved stereoscopic Particle Image Velocimetry (PIV) measurement to characterize the bubble wake. Pure water and varying salt concentration were used to achieve a linear density stratification corresponding to Froude numbers (Fr) ranging from 22.1 to 40.7. Due to the large velocity dynamic range for PIV, we enhanced the signal to noise ratio of our correlation planes with pyramid correlation. We found a significant out of plane velocity component in both homogenous and stratified fluid in the vicinity of the bubble, which was assumed to be negligible in previous studies with confined fluid. The wake of the bubble carries the higher density fluid to the top, which later releases from the wake to form the reverse jet. This buoyant jet has been characterized for different Fr. Eulerian coherent structures are also considered to describe the flow. The rising bubble generates vortices that shed downstream and decay with varying timescales for different Fr. The difference in the coherent structures and decay coefficient leads to a different level of mixing with Fr. The scope of this research is in applications homogenizing the stratified flow using rising bubbles. </p>

An examination of parameters affecting the control of a jet vectoring technique used in the Coanda-assisted Spray Manipulation (CSM) is presented. The CSM makes use of an enhanced Coanda effect on axisymmetric geometries through the interaction of a high volume primary jet flowing through the center of a collar and a secondary high-momentum jet parallel to the first and adjacent to the convex collar. The control jet attaches to the convex wall and vectors according to known Coanda effect principles, entraining and vectoring the primary jet, resulting in controllable r-θ directional spraying. Several control slots (both annular and unique sizes) and expansion radii were tested over a range of momentum flux ratios to determine the effects of these variables on the vectored jet angle and profile. Two- and three-component Particle Image Velocimetry (PIV) was used to determine the vectoring angle and the profile of the primary jet in each experiment. The experiments show that the control slot and expansion radius, along with the momentum ratios of the two jets, predominantly affected the vectoring angle and profile of the primary jet. The Reynolds number range for the primary jet at the exit plane was between 20,000 and 80,000. The flow was in the incompressible Mach number range (Mach< 0.3).

The uncertainty of any measurement is the interval in which one believes the actual error lies. Particle Image Velocimetry (PIV) measurement error depends on the PIV algorithm used, a wide range of user inputs, flow characteristics, and the experimental setup. Since these factors vary in time and space, they lead to nonuniform error throughout the flow field. As such, a universal PIV uncertainty estimate is not adequate and can be misleading. This is of particular interest when PIV data are used for comparison with computational or experimental data. A method to estimate the uncertainty due to the PIV calculation of each individual velocity measurement is presented. The relationship between four error sources and their contribution to PIV error is first determined. The sources, or parameters, considered are particle image diameter, particle density, particle displacement, and velocity gradient, although this choice in parameters is arbitrary and may not be complete. This information provides a four-dimensional "uncertainty surface" for the PIV algorithm used. After PIV processing, our code "measures" the value of each of these parameters and estimates the velocity uncertainty for each vector in the flow field. The reliability of the methodology is validated using known flow fields so the actual error can be determined. Analysis shows that, for most flows, the uncertainty distribution obtained using this method fits the confidence interval. The method is general and can be adapted to any PIV analysis.

A particle image velocimetry (PIV) computer software is analyzed in this work by applying automatic differentiation on it. We create two artificial images that contained particles that where moved with a known velocity field over time. These artificial images were created with parameters that we would have on real PIV experiments. Then we applied a PIV software to find the velocity output vectors. As we mentioned before, we applied automatic differentiation through all the algorithm to track the derivatives of the output vectors regarding interesting parameters declared as inputs. By analyzing these derivatives we analyze the sensitivity of the output vectors to changes on each one of the parameters analyzed. One of the most important derivatives calculated in this project was the derivative of the output regarding the image intensity. In future work we plan to use this derivative combined with the intensity probability distribution of each image pixel, to find PIV uncertainties. If we achieve this goal we will find an uncertainty method that will save computational power and will give uncertainty values with computer accuracy.

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A left ventricular assist device is a mechanical pump implanted in patients with heart failure that continuously takes blood from the left ventricle and delivers it to the aorta, thus decreasing ventricular load. The device is typically considered as a ‘bridge to transplant’, i.e. as a temporary therapy, and involves several risks. Modified ventricular hemodynamics due to a heart pump implantation is studied in-vitro using an elastic ventricle. The ventricle is incorporated into a pulse duplicator setup, which prescribes realistic pulsatile inflow/outflow to mimic a weak ejection fraction. A continuous axial pump mimics a ventricular assist device and its effect on the ventricular hemodynamics is investigated as a function of the pump flow suction. Using particle image velocimetry, pump flow effectiveness at providing unloading on the ventricle and increasing ejection is observed and understanding if proper recirculation of the myocardium down to the apex is restored under varying flow rate.

Experiments have been performed using the Air Force Research Laboratory (AFRL) Blade-Row Interaction (BRI) rig to investigate interactions between a loaded stator and transonic rotor. The BRI rig is a high-speed, highly loaded compressor consisting of a swirler/deswirler, a transonic rotor and a stator. The swirler/deswirler of the BRI rig is used to simulate an embedded transonic fan stage with realistic geometry which produces a wake through diffusion. Details of the unsteady flow field between the stator and rotor were obtained using Particle Image Velocimetry (PIV). Flow visualization images and PIV data that facilitate analysis of vortex shedding, wake motion, and wake-shock-interactions in the blade row are analyzed for three stator/rotor axial spacings and two stator loadings. The data analysis focuses on measuring and comparing, for the different spacings and loading, the vortex size, strength, and location as it forms on the stator trailing edge and propagates downstream into the rotor passage. It was observed that more than one vortex was shed with the passing of a rotor bow shock. These vortices were categorized as small and large vortices with a ~20% decrease in strength. The large vortices were compared at similar location and results show that vortex strength increased as spacing between stator and rotor decreased due to the increased strength of the rotor bow shock impacting the stator trailing edge. Changes in stator loading also affected shed vortex strength. A decrease in stator loading resulted in a decrease in the strength of the vortex shed. The smaller vortices were not affected by a change in spacing but strength was directly related to the loading.

The need exists for finding a quantitative method for validating crowd simulations. One approach is to use optical flow of videos of real crowds to obtain velocities that can be used for comparison to simulations. Optical flow, in turn, needs to be calibrated to be useful. It is essential to show that optical flow velocities obtained from crowd videos can be mapped into the spatially averaged velocities of the observed trajectories of crowd members, and to quantify the extent of the correlation of the results. This research investigates methods to uncover the best conditions for a good correlation between optical flow and the average motion of individuals in crowd videos, with the aim that this will help in the quantitative validation of simulations. The first approach was to use a simple linear proportionality relation, with a single coefficient, alpha, between velocity vector of the optical flow and observed velocity of crowd members in a video or simulation. Since there are many variables that affect alpha, an attempt was made to find the best possible conditions for determining alpha, by varying experimental and optical flow settings. The measure of a good alpha was chosen to be that alpha does not vary excessively over a number of video frames. Best conditions of low coefficient of variation of alpha using the Lucas-Kanade optical flow algorithm were found to be when a larger aperture of 15x15 pixels was used, combined with a smaller threshold. Adequate results were found at cell size 40x40 pixels; the improvement in detecting details when smaller cells are used did not reduce the variability of alpha, and required much more computing power. Reduction iii in variability of alpha can be obtained by spreading the tracked location of a crowd member from a pixel into a rectangle. The Particle Image Velocimetry optical flow algorithm had better correspondence with the velocity vectors of manually tracked crowd members than results obtained using the Lukas-Kanade method. Here, also, it was found that 40x40 pixel cells were better than 15x15. A second attempt at quantifying the correlation between optical flow and actual crowd member velocities was studied using simulations. Two processes were researched, which utilized geometrical correction of the perspective distortion of the crowd videos. One process geometrically corrects the video, and then obtains optical flow data. The other obtains optical flow data from video, and then geometrically corrects the data. The results indicate that the first process worked better. Correlation was calculated between sets of data obtained from the average of twenty frames. This was found to be higher than calculating correlations between the velocities of cells in each pair of frames. An experiment was carried out to predict crowd tracks using optical flow and a calculated parameter, beta, seems to give promising results.

Micro particle image velocimetry (microPIV) is a non-intrusive tool for visualizing flow in micron-scale conduits. Using this investigative instrument, two experimental studies were performed to understand flow behaviors in microfluidic channels - a sudden expansion step flow and laminar velocity profile variation in diffusion driven mixing. First, flow in a backward facing step feature (1:5 expansion ratio) in a microchannel was taken as the subject of microPIV flow visualization. The onset and development of a recirculation flow was studied as a function of flow rate. This flow pattern was further used to investigate two major parameters affecting microPIV measurements; the depth-of-focus and recording time-intervals between images in a microPIV image pair. The onset of recirculation was initiated at flow rates that correspond to Reynolds numbers, Re > 95, which is well beyond the typical working range of microfluidic devices (Re=0.01-10). The recirculation flow has a 3D structure due to the dimensions of the microchannel and the effect of no slip condition on the walls. Ensemble cross-correlation was found not to be sensitive to variations of depth-of-focus and the output flow fields were similar as long as the overall optical focus remained within the upper and lower bounds of the microchannel. However, variations of time intervals between images in a microPIV pair, resulted in quantitatively and qualitatively different flow patterns for a given constant flow rate and depth-of-focus. In the second experiment, the effect of the laminar velocity profile and its variation on mixing phenomena at the reduced scale is studied. It is shown that the diffusive mass flux between two miscible streams, flowing in a laminar regime in a microchannel, is enhanced if the velocity at their diffusion interface is increased. Based on this idea, an in-plane passive micromixing concept is proposed and implemented in a working device (sigma micromixer). This mixer shows considerable mixing performance by periodically varying the flow velocity profile, such that the maximum of the profile coincides with the transversely progressing diffusion fronts repeatedly throughout the mixing channel. microPIV has been used to visualize the behavior of laminar flow inside the micromixer device and to confirm the periodic variation of the velocity profile through the mixing channel.