The biological effects of charged particles is of interest in particle therapy, radiation protection and space radiation science and known to be dependent on both absorbed dose and radiation quality or LET. Microdosimetry is a technique which uses a tissue equivalent gas to simulate microscopic tissue sites of the order of cellular dimensions and the principles of gas ionization devices to measure deposited energy. The Gas Electron Multiplier (GEM) has been used since 1997 for tracking particles and for the determination of particle energy. In general, the GEM detector works in either tracking or energy deposition mode. The instrument proposed here is a combination of both, for the purpose of determining the energy deposition in simulated microscopic sites over the charged particle range and in particular at the end of the range where local energy deposition increases in the so‐called Bragg‐peak region. The detector is designed to track particles of various energies for 5 cm in one dimension, while providing the particle energy deposition every 0.5 cm of its track. The reconfiguration of the detector for different particle energies is very simple and achieved by adjusting the pressure of the gas inside the detector and resistor chain. In this manner, the detector can be used to study various ion beams and their dose distributions to tissues. Initial work is being carried out using an isotopic source of alpha particles and this thesis will describe the construction of the GEM‐based detector, computer modelling of the expected gas‐gain and performance of the device as well as comparisons with experimentally measured data of segmented energy deposition. / UOIT

Theoretical and numerical studies of chaotic mixing are performed to circumvent the difficulties of efficient mixing, which come from the lack of turbulence in microfluidic devices. In order to carry out efficient and accurate parametric studies and to identify a fully chaotic state, a spectral element algorithm for solution of the incompressible Navier-Stokes and species transport equations is developed. Using Taylor series expansions in time marching, the new algorithm employs an algebraic factorization scheme on multi-dimensional staggered spectral element grids, and extends classical conforming Galerkin formulations to nonconforming spectral elements. Lagrangian particle tracking methods are utilized to study particle dispersion in the mixing device using spectral element and fourth order Runge-Kutta discretizations in space and time, respectively. Comparative studies of five different techniques commonly employed to identify the chaotic strength and mixing efficiency in microfluidic systems are presented to demonstrate the competitive advantages and shortcomings of each method. These are the stirring index based on the box counting method, Poincare sections, finite time Lyapunov exponents, the probability density function of the stretching field, and mixing index inverse, based on the standard deviation of scalar species distribution. Series of numerical simulations are performed by varying the Peclet number (Pe) at fixed kinematic conditions. The mixing length (lm) is characterized as function of the Pe number, and lm ∝ ln(Pe) scaling is demonstrated for fully chaotic cases. Employing the aforementioned techniques, optimum kinematic conditions and the actuation frequency of the stirrer that result in the highest mixing/stirring efficiency are identified in a zeta potential patterned straight micro channel, where a continuous flow is generated by superposition of a steady pressure driven flow and time periodic electroosmotic flow induced by a stream-wise AC electric field. Finally, it is shown that the invariant manifold of hyperbolic periodic point determines the geometry of fast mixing zones in oscillatory flows in two-dimensional cavity.

<p>The work is focused on experimental study and modelling of spacer grid influence on single- and two-phase flow. In the experimental study a mock-up of a realistic fuel bundle with five spacer grids of thin plate spring construction was investigated. A special pressure measuring technique was used to measure pressure distribution inside the spacer. Five pressure taps were drilled in one of the rods, which could exchange position with other rods, in this way providing a large degree of freedom. Laser Doppler Velocimetry was used to measure mean local axial velocity and its fluctuating component upstream and downstream of the spacer in several subchannels with differing spacer part. The experimental study revealed an interesting behaviour. Subchannels from the interior part of the bundle display a different effect on the flow downstream of the spacer compared to subchannels close to the box wall, even if the spacer part is the same. This behaviour is not reflected in modern correlations. The modelling part, first, consisted in comparing the present experimental data to Computational Fluid Dynamics calculations. It was shown that stand-alone subchannel models could predict the local velocity, but are unreliable in prediction of turbulence enhancement due to spacer. The second part of the modelling consisted in developing a deposition model for increase due to spacer. In this study Lagrangian Particle Tracking (LPT) coupled to Discrete Random Walk (DRW) technique was used to model droplet movements through turbulent flow. The LPT technique has an advantage to model the influence of turbulence structure effect on droplet deposition, in this way presenting a generalized model in view of spacer geometry change. The verification of the applicability of LPT DRW method to model deposition in annular flow at Boiling Water Reactor conditions proved that the method is unreliable in its present state. The model calculations compare reasonably well to air-water deposition data, but display a wrong trend if the fluids have a different density ratio than air-water.</p>

Geologic sequestration of CO₂ in deep saline aquifers has been studied extensively over the past two decades as a viable method of reducing anthropological carbon emissions. The monitoring and prediction of the movement of injected CO₂ is important for assessing containment of the gas within the storage volume, and taking corrective measures if required. Given the uncertainty in geologic architecture of the storage aquifers, it is reasonable to depict our prior knowledge of the project area using a vast suite of aquifer models. Simulating such a large number of models using traditional numerical flow simulators to evaluate uncertainty is computationally expensive. A novel stochastic workflow for characterizing the plume migration, based on a model selection algorithm developed by Mantilla in 2011, has been implemented. The approach includes four main steps: (1) assessing the connectivity/dynamic characteristics of a large prior ensemble of models using proxies; (2) model clustering using the principle component analysis or multidimensional scaling coupled with the k-mean clustering approach; (3) model selection using the Bayes' rule on the reduced model space, and (4) model expansion using an ensemble pattern-based matching scheme. In this dissertation, two proxies have been developed based on particle tracking in order to assess the flow connectivity of models in the initial set. The proxies serve as fast approximations of finite-difference flow simulation models, and are meant to provide rapid estimations of connectivity of the aquifer models. Modifications have also been implemented within the model selection workflow to accommodate the particular problem of application to a carbon sequestration project. The applicability of the proxies is tested both on synthetic models and real field case studies. It is demonstrated that the first proxy captures areal migration to a reasonable extent, while failing to adequately capture vertical buoyancy-driven flow of CO₂. This limitation of the proxy is addressed in the second proxy, and its applicability is demonstrated not only in capturing horizontal migration but also in buoyancy-driven flow. Both proxies are tested both as standalone approximations of numerical simulation and within the larger model selection framework. / text

No description available.

Microplastics are tiny particles that due to their small size, durability, and widespread usage have become a huge threat to the world and the environment. Aquatic environments like rivers and oceans have faced some irreparable problems such as the extinction of various marine species. Field sampling and numerical modeling are two methods that can help researchers have a better understanding of the situations to come up with the best solutions. Machine learning methods have drawn considerable attention in most engineering fields recently, which can be used in conjunction with field sampling and numerical simulation. In this study, by generating a fine mesh and using bathymetry, water level, and discharge data, a three-dimensional hydrodynamic modeling of the domain of study was conducted using TELEMAC 3D, which is a model that was used to simulate the behavior of the Fraser River in x, y, and z directions. The results were implemented to track the movements of microplastic particles in the lower part of the Fraser River. CaMPSim-3D, which is a three-dimensional Lagrangian particle tracking model was employed to track microplastic particles. This model, in addition to calculating the horizontal location of particles, computes their vertical movements too. The release locations of microplastic particles were chosen based on the locations of the wastewater treatment plants and combined sewer overflows and in the end, nine scenarios were conducted for this study. An unsupervised branch of machine learning is clustering which helps to cluster points by relying on their different properties. The OPTICS algorithm, which is a density-based clustering algorithm, was used to find the accumulation zones of microplastic particles in the lower part of the Fraser River. It should be mentioned that in all parts available measured data and information were used for validation. The results of the clustering algorithm indicated that there are eight accumulation zones in the study area and the breakwater in the upper branch of the Fraser River is an ideal place for microplastic particles to accumulate. A reasonable agreement was obtained between the model results and measured data.

Yes / Positron emission particle tracking (PEPT) was used to visualise the flow patterns established by mixing in two laboratory-scale anaerobic digesters fitted with mechanical mixing or gas mixing apparatus. PEPT allows the visualisation of flow patterns within a digester without necessitating the use of a transparent synthetic sludge. In the case of the mechanically-mixed digester, the mixing characteristics of opaque sewage sludge was compared to a transparent synthetic sludge at different mixing speeds. In the gas-mixed apparatus, two synthetic sludges were compared. In all scenarios, quasi-toroidal flow paths were established. However, mixing was less successful in more viscous liquids unless mixing power was increased to compensate for the increase in viscosity. The robustness of the PEPT derived velocities was found to be significantly affected by the frequency with which the particle enters a given volume of the vessel, with the accuracy of the calculated velocity decreasing in regions with low data capture. Nevertheless, PEPT was found to offer a means of accurate validation of computational fluid dynamics models which in turn can help to optimise flow patterns for biogas production. / The first author was funded via an EPSRC CASE award in conjunction with Severn Trent Water. The second author was funded via a University of Birmingham Postgraduate Teaching Assistantship award.

Single particle tracking has become a ubiquitous class of tools in the study of biology at the molecular level. While the broad adoption of these techniques has yielded significant advances, it has also revealed the limitations of the methods. Most notable among these is that traditional single particle tracking is limited to imaging the particle at low temporal resolutions and small axial ranges. This restricts applications to slow processes confined to a plane. Biological processes in the cell, however, happen at multiple time scales and length scales. Real-time feedback-driven single particle tracking microscopes have emerged as one group of methods that can overcome these limitations. However, the development of these techniques has been ad-hoc and their performance has not been consistently analyzed in a way that enables comparisons across techniques, leading to incremental improvements on existing sets of tools, with no sense of fit or optimality with respect to SPT experimental requirements. This thesis addresses these challenges through three key questions : 1) What performance metrics are necessary to compare different techniques, allowing for easy selection of the method that best fits a particular application? 2) What is a procedure to design single particle tracking microscopes for the best performance?, and 3) How does one controllably and repeatably experimentally test single particle tracking performance on specific microscopes?. These questions are tackled in four thrusts: 1) a comprehensive review of real-time feedback-driven single particle tracking spectroscopy, 2) the creation of an optimization framework using Fisher information, 3) the design of a real-time feedback-driven single particle tracking microscope utilizing extremum seeking control, and 4) the development of synthetic motion, a protocol that provides biologically relevant known ground-truth particle motion to test single particle tracking microscopes and data analysis algorithms. The comprehensive review yields a unified view of single particle tracking microscopes and highlights two clear challenges, the photon budget and the control temporal budget, that work to limit the two key performance metrics, tracking duration and Fisher information. Fisher information provides a common framework to understand the elements of real-time feedback-driven single particle tracking microscopes, and the corresponding information optimization framework is a method to optimally design these microscopes towards an experimental aim. The thesis then expands an existing tracking algorithm to handle multiple particles through a multi-layer control architecture, and introduces REACTMIN, a new approach that reactively scans a minimum of light to overcome both the photon budget and the control temporal budget. This enables tracking durations up to hours, position localization down to a few nanometers, with temporal resolutions greater than 1 kHz. Finally, synthetic motion provides a repeatable and programmable method to test single particle tracking microscopes and algorithms with a known ground truth experiment. The performance of this method is analyzed in the presence of common actuator limitations. / 2024-01-16T00:00:00Z

Particle-laden supersonic jets impinging on a flat surface are of interest to cold gas-dynamic spray technology. Solid particles are propelled to a high velocity through a convergent-divergent nozzle, and upon impact on a substrate surface, they undergo plastic deformation and adhere to the surface. For given particle and substrate materials, particle velocity and temperature at impact are the primary parameters that determine the success of particle deposition. Depending on the particle diameter and density, interactions of particles with the turbulent supersonic jet and the compressed gas region near the substrate surface can have significant effects on particle velocity and temperature. Unlike previous numerical simulations of cold spray, in this dissertation we track solid particles in the instantaneous turbulent fluctuating flow field from the nozzle exit to the substrate surface. Thus, we capture the effects of particle-turbulence interactions on particle velocity and temperature at impact. The flow field is obtained by direct numerical simulations of a supersonic rectangular particle-laden air jet impinging on a flat substrate. An Eulerian-Lagrangian approach with two-way coupling between solid particles and gas phase is used. Unsteady three-dimensional Navier-Stokes equations are solved using a six-order compact scheme with a tenth-order compact filter combined with WENO dissipation, almost everywhere except in a region around the bow shock where a fifth-order WENO scheme is used. A fourth-order low-storage Runge-Kutta scheme is used for time integration of gas dynamics equations simultaneously with solid particles equations of motion and energy equation for particle temperature. Particles are tracked in instantaneous turbulent jet flow rather than in a mean flow that is commonly used in the previous studies. Supersonic jets for air and helium at Mach number 2.5 and 2.8, respectively, are simulated for two cases for the standoff distance between the nozzle exit and the substrate. Flow structures, mean flow properties, particles impact velocity and particles deposition efficiency on a flat substrate surface are presented. Different grid resolutions are tested using 2, 4 and 8 million points. Good agreement between DNS results and experimental data is obtained for the pressure distribution on the wall and the maximum Mach number profile in wall jet. Probability density functions for particle velocity and temperature at impact are presented. Deposition efficiency for aluminum and copper particles of diameter in the range 1 micron to 40 microns is calculated. Instantaneous flow fields for the two standoff distances considered exhibit different flow characteristics. For large standoff distance, the jet is unsteady and flaps both for air (Mach number 2.5) and for helium (Mach number 2.8), in the direction normal to the large cross-section of the jet. Linear stability analysis of the mean jet profile validates the oscillation frequency observed in the present numerical study. Available experimental data also validate oscillation frequency. After impingement, the flow re-expands from the compressed gas region into a supersonic wall jet. The pressure on the wall in the expansion region is locally lower than ambient pressure. Strong bow shock only occurs for small standoff distance. For large standoff distance multiple/oblique shocks are observed due to the flapping of the jet. The one-dimensional model based on isentropic flow calculations produces reliable results for particle velocity and temperature. It is found that the low efficiency in the low-pressure cold spray (LPCS) compared to high-pressure cold spray (HPCS) is mainly due to low temperature of the particles at the exit of the nozzle. Three-dimensional simulations show that small particles are readily influenced by the large-scale turbulent structures developing on jet shear layers, and they drift sideways. However, large particles are less influenced by the turbulent flow. Particles velocity and temperature are affected by the compressed gas layer and remain fairly constant in the jet region. With a small increase in the particles initial temperature, the deposition efficiency in LPCS can be maximized. There is an optimum particle diameter range for maximum deposition efficiency. / Ph. D.

The analysis of turbulent flows provides a unique scientific challenge whose solution remains central to unraveling the fundamental nature of all fluid dynamics. Measuring and predicting turbulent flows becomes even more difficult when considering a two-phase flow, which is a commonly encountered engineering problem across many disciplines. One such example, the ingestion of foreign debris into a gas turbine engine, provided the impetus for this study. Despite more than 40 years of research, operation with a particle-laden inlet flow remains a significant problem for modern turbomachines. The purpose, therefore, is to develop experimental methods for investigating multi-phase flows relevant to the cooling of gas turbine components. Initially, several generic components representing turbine cooling designs were evaluated with a particle-laden flow using a special high temperature test facility. The results of this investigation revealed that blockage was highly sensitive to the carrier flowfield as defined by the cooling geometry. A second group of experiments were conducted in one commonly used cooling design using a Time Resolved Digital Particle Image Velocimetry (TRDPIV) system that directly investigated both the carrier flowfield and particle trajectories. Traditional PIV processing algorithms, however, were unable to resolve the particle motions of the two-phase flow with sufficient fidelity. To address this issue, a new Particle Tracking Velocimetry (PTV) algorithm was developed and validated for both single-phase and two-phase flows. The newly developed PTV algorithm was shown to outperform other published algorithms as well as possessing a unique ability to handle particle laden two-phase flows. Overall, this work demonstrates several experimental methods that are well suited for the investigation of wall-bounded turbulent two-phase flows, with a special emphasis on a turbine cooling method. The studies contained herein provide valuable information regarding the previously unknown fluid and particle dynamics within the turbine cooling system. / Ph. D.