Thesis (Ph. D.)--University of Washington, 2000. / Vita. Includes bibliographical references (leaves 111-116).

Thesis (Ph. D.)--University of Washington, 1995. / Vita. Includes bibliographical references (leaves [187]-197).

Active colloids are small particles that can convert external energy supply into self-propulsion. Because of the existence of the energy current inside and across the system, active colloids exhibit behaviors that are far away from thermodynamic equilibrium. During the past decades, active colloids have been used to provide models for many different non-equilibrium system studies and have been designed to complete tasks on small scale. By tuning the particle size, shape, etc, or changing the actuation methods of the active colloid systems, people have developed a large number of different active colloid systems. Among all active colloid systems, the Quincke rotation system can effectively propel particles with rapid speed. This phenomenon refers to the spontaneous rolling of a dielectric sphere in a weakly conducting liquid under a DC electric field. Although the basic mechanism of a single Quincke roller has been well explained, some behaviors that occur in complex environments or with multiple Quincke particles are still mysteries. For example, one particle will move back and forth on the bottom electrode under a high electric DC field. This so-called Quincke Oscillation motion cannot be explained by the previous models well. So a new model is required. In this dissertation, we will focus on explaining this newly-discovered dynamic in the Quincke system. Then we will study the collective dynamics of multiple Quincke oscillators with designed experiments and models. In Chapter 1, the background and different actuation methods of active colloid systems are first introduced. Then the Quincke rotation system and its field-dependent dynamics are explained with a classic leaky dielectric model. The recent research results with Quincke systems are shortly reviewed afterward. In Chapter 2, we introduce the experimentally discovered Quincke Oscillation phenomenon. Then we reveal its dependency on liquid conductivity and particle size. This dynamic is finally explained by the asymmetric charging of the particle surface in the field-induced boundary layer near the electrode. This work opens the door to the study of the collective dynamics of Quincke oscillators. In Chapter 3, we first introduce a dynamical model considering the charge, dipole, and quadrupole moments of the sphere and predict its oscillatory motion under a non-uniform liquid conductivity environment. Then we study the behavior of two coupled Quincke oscillators with far-field hydrodynamic and electrostatic interactions. The numerical simulations predict the synchronization and alignment of two oscillators with fixed positions. We further develop a model based on weakly coupled oscillator assumptions by considering the relative phase and oscillating orientations of two oscillators. The model successfully explains the numerical simulation results and can be applied to other active colloid systems with multiple mobile oscillators. In Chapter 4, we show that the Quincke oscillators can assemble into a cluster and oscillate with high synchronization and alignment. This formation of the cluster can also increase the oscillation frequency of the oscillators. By considering the perfect contact rolling of the oscillators on the electrode, we develop a weakly coupled oscillator theory model. This model explains the tendency of particles to synchronize and align in a cluster and predicts the increase of the oscillation frequency when particles are in synchronized phases. The cluster is stabilized due to the existing phase waves observed in experiments and simulations. In Chapter 5, we introduce two other studies on Quincke rollers with different experimental designs. Particles of helical shape exhibit self-propulsion in the liquid bulk and highlight the role of shape in controlling particle dynamics. For multiple spheres in a height-confined system, the particles display a transition from a fluctuating state to an absorbing stable state depending on their density and the applied field strength. This work provides an experimental model for studying absorbing state. In Chapter 6, the development of the Quincke system study is reviewed and some future directions are suggested.

Call number: LD2668 .T4 1985 F69 / Master of Science

Thesis (MIng) --Stellenbosch University, 1999. / ENGLISH ABSTRACT: A method was developed at the Atomic Energy Corporation of South Africa (AEC) for the plasma based production of tetrafluoroethylene (TFE). The process involves the feeding of carbon particles into a direct-current CF4 plasma. The resultant plasma gas is quenched rapidly to obtain TFE and other fluorocarbons. The mixing of the particles with the plasma gas is very important in order to achieve a high C:F-ratio in the gas phase, which promotes the desired reactions. The gas enthalpy in the reactor is a governing factor in the TFE yields that are obtained. In this study research was done on particle mixing and the enthalpy distribution in the laboratory scale reactor. An enthalpy probe was used as the main diagnostic tool. Results indicated that particle mixing is quite uniform throughout the reactor. A basic one-dimensional mechanistic model of the reactor was also expanded to assist in· the scale-up of the process. In its present form the model is adequate for predicting trends in the reactor. The model could still be expanded further to include reaction kinetics and internal heat transfer in the particles. Considering the restrictions of the model, satisfactory agreement was obtained between the model and experimental results. / AFRIKAANSE OPSOMMING: 'n Proses vir die plasmagebaseerde produksie van tetrafluoroetileen (TFE) is deur die Atoomenergiekorporasie van Suid-Afrika (AEK) ontwikkel. Koolstofpartikels word in 'n gelykstroomCF4- plasma gevoer en die resulterende plasmagas word vinnig geblus ten einde TFE en ander fluoor-koolstofverbindings as produkte te verkry. Goeie vermenging van die koolstofpartikels met die plasmagas is van uiterste belang ten einde 'n hoe C:F-verhouding, wat die gewenste reaksies bevorder, in die gasfase te verkry. Die entalpie van die plasmagas in die reaktor is 'n bepalende faktor in die opbrengs TFE wat verkry word. Vir die doel van hierdie werkstuk is navorsing op laboratoriumskaal gedoen oor partikelvermenging en die entalpie-verspreiding in die reaktor. Die hoof diagnostiese apparaat wat vir die doel aangewend is, is die entalpiesonde. Resultate toon dat partikelvermenging naastenby uniform deur die reaktor voorkom. Verder is 'n basiese een-dimensionele meganistiese model van die reaktor uitgebrei ten einde van nut te wees in die opskaling van die proses. In sy huidige vorm is die model voldoende om algemene neigings in die reaktor te voorspel. Die model kan nog verder uitgebrei word om reaksie-kinetika en interne hitte-oordrag in die partikels in te sluit. Die beperkings van die model in ag genome, is ooreenstemming tussen die model en eksperimentele resultate egter bevredigend.

Thesis (PhD (Mechanical and Mechatronic Engineering))--University of Stellenbosch, 2004. / Granular flow occurs in a broad spectrum of industrial applications that range from separation and mixing in the pharmaceutical industry, to grinding and crushing, blasting, stockpile construction, flow in and from hoppers, silos, bins, and conveyer belts, agriculture, mining and earthmoving. Two totally different approaches of modelling granular flow are the Discrete Element Method (DEM) and continuum methods such as Finite Element Methods (FEM). Continuum methods can be divided into nonpolar or classic continuum methods and polar continuum methods. Large displacements are usually present during granular flow which, without remeshing, cannot be solved with standard finite element methods due to severe mesh distortion. The Particle-in-Cell (PIC) method, which is a so-called meshless method, eliminates this problem since all the state variables are traced by material points moving through a fixed mesh. The main goal of this research was to model the flow of noncohesive granular material in front of flat bulldozer blades and into excavator buckets using a continuum method. A PIC code was developed to model these processes under plane strain conditions. A contact model was used to model Coulomb friction between the material and the bucket/blade. Analytical solutions, published numerical and experimental results were used to validate the contact model and to demonstrate the code’s ability to model large displacements and deformations. The ability of both DEM and PIC to predict the forces acting on the blade and bucket and the material flow patterns were demonstrated. Shear bands that develop during the flow of material were investigated. As part of the PIC analyses, a comparison between classic continuum and polar continuum (Cosserat) results were made. This includes mesh size and orientation dependency, flow patterns and the forces acting on the blade and the bucket. It is concluded that the interaction of buckets and blades with granular materials can successfully be modelled with PIC. In the cases conducted here, the nonpolar continuum was more accurate than the polar continuum, but the polar continuum results were less dependent on the mesh size. The next step would be to apply this technology to solve industrial problems.

Thesis (Ph.D)--Mathematics, Georgia Institute of Technology, 2008. / Committee Chair: Goldsztein, Guillermo; Committee Member: Dieci, Luca; Committee Member: McCuan, John; Committee Member: Santamarina, Juan; Committee Member: Zhou, Haomin.

This thesis addresses the sampling problem in a high-dimensional space, i.e., the computation of averages with respect to a defined probability density that is a function of many variables. Such sampling problems arise in many application areas, including molecular dynamics, multiscale models, and Bayesian sampling techniques used in emerging machine learning applications. Of particular interest are thermostat techniques, in the setting of a stochastic-dynamical system, that preserve the canonical Gibbs ensemble defined by an exponentiated energy function. In this thesis we explore theory, algorithms, and numerous applications in this setting. We begin by comparing numerical methods for particle-based models. The class of methods considered includes dissipative particle dynamics (DPD) as well as a newly proposed stochastic pairwise Nosé-Hoover-Langevin (PNHL) method. Splitting methods are developed and studied in terms of their thermodynamic accuracy, two-point correlation functions, and convergence. When computational efficiency is measured by the ratio of thermodynamic accuracy to CPU time, we report significant advantages in simulation for the PNHL method compared to popular alternative schemes in the low-friction regime, without degradation of convergence rate. We propose a pairwise adaptive Langevin (PAdL) thermostat that fully captures the dynamics of DPD and thus can be directly applied in the setting of momentum-conserving simulation. These methods are potentially valuable for nonequilibrium simulation of physical systems. We again report substantial improvements in both equilibrium and nonequilibrium simulations compared to popular schemes in the literature. We also discuss the proper treatment of the Lees-Edwards boundary conditions, an essential part of modelling shear flow. We also study numerical methods for sampling probability measures in high dimension where the underlying model is only approximately identified with a gradient system. These methods are important in multiscale modelling and in the design of new machine learning algorithms for inference and parameterization for large datasets, challenges which are increasingly important in "big data" applications. In addition to providing a more comprehensive discussion of the foundations of these methods, we propose a new numerical method for the adaptive Langevin/stochastic gradient Nosé-Hoover thermostat that achieves a dramatic improvement in numerical efficiency over the most popular stochastic gradient methods reported in the literature. We demonstrate that the newly established method inherits a superconvergence property (fourth order convergence to the invariant measure for configurational quantities) recently demonstrated in the setting of Langevin dynamics. Furthermore, we propose a covariance-controlled adaptive Langevin (CCAdL) thermostat that can effectively dissipate parameter-dependent noise while maintaining a desired target distribution. The proposed method achieves a substantial speedup over popular alternative schemes for large-scale machine learning applications.

The turbulent boundary layer is an aspect of fluid flow which dominates the performance of many engineering systems - yet the analytic solution of such flows is intractable for most applications. Our understanding of boundary layers is therefore limited by our ability to simulate and measure them. Tomographic Particle Image Velocimetry (TPIV) is a recently developed technique for direct measurement of fluid velocity within a 3D region. This allows new insight into the topological structure of turbulent boundary layers. Increasing Reynolds Number increases the range of scales at which turbulence exists; a measurement technique must have a larger 'dynamic range' to fully resolve the flow. Tomographic PIV is currently limited in spatial dynamic range (which is also linked to the spatial and temporal resolution) due to a high degree of noise. Results also contain significant bias error. This work proposes a modification of the technique to use more than two exposures in the PIV process, which (for four exposures) is shown to improve random error by a factor of 2 to 7 depending on experimental setup parameters. The dynamic range increases correspondingly and can be doubled again in highly turbulent flows. Bias error is reduced by up to 40%. An alternative reconstruction approach is also presented, based on application of a reduction strategy (elimination of coefficients based on a first guess) to the tomographic weightings matrix Wij. This facilitates a potentially significant increase in computational efficiency. Despite the achieved reduction in error, measurements contain non-zero divergence due to noise and sampling errors. The same problem affects visualisation of topology and coherent fluid structures. Using Projection Onto Convex Sets, a framework for post-processing operators is implemented which includes a divergence minimisation procedure and a scale-limited denoising strategy which is resilient to 'false' vectors contained in the data. Finally, developed techniques are showcased by visualisation of topological information in the inner region of a high Reynolds Number boundary layer (δ+ = 1890, Reθ = 3650). Comments are made on the visible flow structures and tentative conclusions are drawn.

Volcanogenic lightning has a long documented history in the scientific field, though its origins are still poorly understood. The interactions leading to electrification of ash plumes is essentially a function of the microphysics controlling and affecting ash particle collisions. This thesis presents measurements made on charged particle interactions in a fluidized bed, with large-scale applications to the phenomenon of volcanogenic lightning and charged particle dynamics in volcanic plumes. Using a fluidized bed of ash samples taken from Ecuador's Volcán Tungurahua, particles are introduced to a collisional environment, where they acquire an associated polarity. A charged copper plate is used to collect particles of a given polarity, and particle size distributions are obtained for different weight fractions of the ash. It is observed that relatively smaller particles acquire a net negative charge, while larger particles in the sample charge positively. This is a well-documented occurrence with perfectly spherical, chemically identical samples, but this work represents one of the first applications of the principle to volcanic ash. Image analysis is preformed to determine the size distribution associated with specific polarities, and the associated minimum charge on each particle is calculated based on the plate collection height and particle size. We also present results that demonstrate the relationship between particle collisions and the amount of charge exchanged. Using techniques developed to examine the collision rate within a flow, combined with the charging rates determined from this experiment, we determine a maximum charge exchange rate of 1.28±0.23 electrons transferred per collision.