Effervescent atomization has been a topic of considerable investigation in the literature due to its important advantages over other atomization mechanisms. This work contributes to the development of both effervescent atomizers and also laser-based techniques for spray investigation In order to develop non-intrusive measurement techniques for spray applications, a procedure is suggested to characterize the shape of droplets using image-based droplet analyzers. Image discretization which is a major source of error in droplet shape measurement is evaluated using a simulation. The accuracy of StereoPIV system in conducting droplet velocity measurement in a spray field is also investigated. To assist in the design of effervescent atomizers, bubble formation during gas injection from a micro-tube into liquid cross-flow is investigated using a Shadow-PIV/PTV system. The generated spray fields of two effervescent atomizers which operate using a porous and a typical multi-hole air injector are compared using qualitative images and Shadow-PTV measurement.

Concern for the nonphysiologic energy required to actuate medical devices utilizing “smart material” properties of shape memory polymer (SMP) compels a rigorous investigation into the flow and temperature fields surrounding a thermally activated catheter device. Multiple analyses include the theoretical approaches of exact analytical solutions and finite difference modeling combined with the experimental techniques of particle image velocimetry (PIV) and laser-induced fluorescence (LIF). The attained velocities and temperatures related to the convective heat transfer impact the potential for blood or tissue damage caused by intravascular heating. The clinical scenario involving a catheter device receiving heat within an artery is modeled in its simplest form as a cylindrical metal cap on the tip of a hollow glass rod placed inside of a long straight tube of constant cross-sectional area. Using a working fluid with properties comparable to blood, flow rates and energy input is then varied to determine their effects on velocity fields and temperature gradients. Analytical solutions for both the straight tube and concentric annulus demonstrate the two velocity distributions involved, as flow moves past the gap between the catheter and artery wall and then converges downstream to the Poiseuille solution for steady pipe flow of an incompressible fluid. To solve for the transition between the velocity profiles, computational fluid dynamics software simulates a finite volume model identical to the experimental setup used for intravascular heating experiments. PIV and LIF, both experimental techniques making use of similar hardware, determine velocity fields and temperature distributions, respectively, by imaging fluid seeding agents and their particular interaction with the light sheet. The velocity and temperature fields obtained experimentally are matched with the analytical and finite volume analysis through fluid properties, flow rates, and heating rates. Velocities determined during device heating show a small increase in local velocity, due to temperature dependent viscosity effects. When the device is centered in the model, flow patterns constrain the heat flow near the center axis and away from the channel walls. Increasing flow rate consequently decreases temperature rise, as the heat is carried more quickly downstream and away from the heat source. Using multiple analyses, fluid velocity and temperature distributions are first theorized with analytical and finite element methods and then validated through experimental imaging in a physical model.

Zugl.: Aachen, Techn. Hochsch., Diss., 2007.

Thesis (Ph.D.) - Carleton University, 2007. / Includes bibliographical references (p. 251-264). Also available in electronic format on the Internet.

Thesis (M.Oc.E.)--Oregon State University, 2011. / Printout. Includes bibliographical references (leaf 70). Also available on the World Wide Web.

Techn. Universiẗat, Diss., 2002--Berlin.

Thesis (Ph. D.)--University of Rhode Island, 2006. / Typescript. Includes bibliographical references (leaves 97-99).

We introduce new methods based on the L2 Optimal Transport (OT) problem and the Navier-Stokes equations to approximate a fluid velocity field from images obtained with Particle Image Velocimetry (PIV) measurements. The main idea is to consider two successive images as the initial and final densities in the OT problem, and to use the associated OT flow as an estimate of the underlying physical flow. We build a simple but realistic model for PIV data, and use it to analyze the behavior of the transport map in this situation. We then design and implement a series of post-processing filters created to improve the quality of the numerical results, and we establish comparisons with traditional cross-correlation algorithms. These results indicate that the OT-PIV procedure performs well on low to medium seeding densities, and that it gives better results than typical cross-correlation algorithms in some cases. Finally, we use a variational method to project the OT velocity field on the space of solutions of the Navier-Stokes equations, and extend it to the rest of the fluid domain, outside the particle locations. This extension provides an effective filtering of the OT solution beyond the local post-processing filters, as demonstrated by several numerical experiments. / Graduate

Blending processes in a silo minimise the fluctuations in the property of bulk solids with the blending performance being strongly influenced by the flow pattern and operating mode among other process parameters such as batch size and type of input fluctuations. An accurate prediction of flow characteristics such as flow channel boundary and velocity profiles is important for understanding and quantifying the blending performance, thereby increasing the scope for new design by minimising the number of expensive pilot scale experiments required. In this thesis, the Discrete Element Method (DEM) is deployed to predict and understand the flow characteristics and blending of cylindrical plastic pellets in a planar flat bottom silo and a multi-flow blender (a silo with an insert and a blending tube). The predictions are validated against high-resolution velocity measurements analysed using Particle Image Velocimetry (PIV) technique. A planar model silo was built to measure the flow of pellets using PIV technique. The existing GeoPIV Matlab module was customised to extract the velocity fields in the Eulerian frame of reference and its accuracy has been verified. The developed tool was then applied to quantitatively investigate the mechanism of evolution of flow in a flat bottom silo and the dependency of the state of developed flow on the depth of the planar silo. It was shown that the development of flow during discharge can be divided into two stages: a rapid upward propagation of plug flow followed by a widening of the flow channel with increasing shearing boundaries. The size of the flow channel was found to be increasing with the depth of the silo. For the 100 mm deep silo, the flow is three dimensional with significant retardation in velocity at the frontal walls, whilst a negligible retardation was found for the 20 and 40 mm deep model silos. The thickness and frontal wall friction in planar silos thus play an important role in the development of flow patterns in model silos. In this thesis, DEM model calibration relating the macro-scale bulk friction and micro- scale particle friction at different rolling friction values was developed from DEM simulations of Jenike direct shear box. During the direct shear simulation, a constant normal force was achieved with the use of a shear lid geometry made with glued spheres thereby eliminating the use of a traditional servo control function. The influence of particle rotations and rolling friction on the limiting bulk friction for different particle sliding friction coefficients was explored. The accuracy of the calibration data was assessed by simulating the flow in a flat bottom silo and comparing the model predictions of flow rate, velocity profiles and flow channel boundary with the experiments. A good quantitative agreement was found between the experiment and simulations. The DEM model predictions were also compared with the kinematic model. Following the validation of the model, it was shown that the frontal friction and rolling friction are the influential parameters in simulating the flow patterns such as semi-mass and internal flow. It was further shown that flow transits from semi-mass flow to internal flow with the increase of frontal wall friction. The drastic influence of frontal wall friction on stress, flow patterns and force chains were analysed highlighting its implications on interpretations in 2D test silos. Finally, the developed DEM and PIV tools are employed to investigate blending in a flat bottom and multi-flow blender silo for different flow patterns. The analysis showed that the blending is more effective with the internal flow when compared to semi-mass flow in a flat bottom silo, in both continuous and discontinuous modes for a variety of process conditions such as batch size, the number of recirculation and frequency of input fluctuations. An algorithm was developed to evaluate the blending performance from the spatially averaged Eulerian velocity fields. The flow in a relatively large-scale multi-flow blender comprising nearly 606,000 particles, thereby fully replicating the test silo, was simulated and the challenges in reproducing the test conditions of continuous and discontinuous modes of operation were discussed. The flow patterns and blending were first analysed from the experiments in different configurations of the insert. Using the same input parameters for the model, it was shown that the model predictions of the velocity profiles along the height of the silo are in good agreement with the experiments. Internal flow, mixed flow and mass flow were predicted for the diverging, straight and converging insert configurations respectively and the blending performance for each of these configurations suggests an optimal configuration of the blender thereby demonstrating the potential of PIV and DEM in design optimisation. The possibility of conducting the DEM simulations under increased gravity in order to reduce the computational time has also been explored.

New technologies are constantly developing towards the goal of increasing the performance of gas turbine engines while reducing pollutant emissions. The design of the combustion system is vital in the drive to reduce pollutants in order to meet legislative targets. As part of this, the fuel injector is crucial in preparing the fuel for combustion through atomization and correct mixing with the air flow. Thus, it is desirable to develop techniques to allow the analysis of performance in these key criteria and improve the understanding of both fuel injector aerodynamics and fuel atomisation. Particle Image Velocimetry (PIV) allows for spatially resolved velocity data of flow fields to be recorded and therefore enables the inspection of flow behaviour.