New survey technologies are able to provide detailed data on the form and topography of riverbeds. With this increased data resolution, the required computational time rather than data availability has become the limiting factor for river models. Detailed bathymetric data can be used to provide better empirical representation of drag and roughness at fine scales, allowing a priori selection of roughness using known physics rather than a posteriori calibration. However, we do not have sufficient guidance or understanding from the literature to represent known heterogeneities smaller than our practical grid scale. The problem is what to do with known subgrid-scale bathymetric features and roughness when our models must use a coarser computational grid. In this project, we simplify this complex problem to analyzing flow in a simple open channel with a single patch of relatively high roughness against an otherwise uniform background of low roughness. We model this open channel with a two-dimensional, depth-averaged river model. By running multiple simulations using different grid sizes we gain insight into how the relationship between the grid cell size and the patch size affects the appropriate physical selection of roughness parameter. As the primary focus, the present work proposes and investigates several methods for upscaling known fine-scale drag coefficient data to a coarser grid resolution for a model. For the tested conditions, it appears that a simple area-weighted linear average is simple to apply and creates a flow field very similar to the best results achieved by calibration. As a secondary issue, the present work examines grid-dependent behaviors when using model calibration. Although recalibration of models for different grid scales is a common practice among modelers, we could find relatively little documentation or analysis. In our work, we examine both single-cell calibration (i.e. changing roughness in only the cell containing the rough patch) and multiple-grid cell calibration involving neighbor cells. With either method, improving calibration required multiple model simulations and comparative analysis for each tested grid size and was inefficient compared to the upscaling approach. As expected, the calibration at a given grid size was always inappropriate for a different grid size. / text

The non-interacting, nonuniform electron gas exhibits simplifications in two dimensions, that are of particular interest in the application of density functional theory. The results of linear response theory for an attractive impurity in a two-dimensional gas have been shown to be surprisingly accurate even though there are bound states, and were shown to be exact in the high density limit (Zaremba et al. Phys. Rev. B, 71:125323, 2005 and Zaremba et al. Phys. Rev. Lett., 90(4):046801, 2003). The density resulting from linear response theory and the Thomas-Fermi approximation coincide in the high density limit. As an alternative to linear response theory, the Kirzhnits gradient expansion gives corrections to Thomas-Fermi in gradients of the potential. In two dimensions, all of the gradient corrections vanish at zero temperature, which is a new result presented in this work. We have performed numerical calculations which show that while Thomas-Fermi appears to be a surprisingly accurate approximation in two dimensions, it is not exact. The differences between two and three dimensions that lead to the vanishing of the gradient corrections, however, are of great interest since these may lead to better understanding and simplifications of the corresponding three-dimensional problem. / Thesis (Master, Physics, Engineering Physics and Astronomy) -- Queen's University, 2007-11-07 09:47:00.316

In this thesis we look for potential chronic inflammation biomarkers because studies have shown that farmers with musculoskeletal disorders might be affected by the environment to develop musculoskeletal disorders. Animal farmers are highly exposed to dust, aerosols, molds and other toxins in the air and environment leading to musculoskeletal disorders, respiratory disorders, airway symptoms and febrile reactions. There is reason to believe that the farmers have a constant or chronic inflammation that develops into musculoskeletal disorders. By using a proteomic approach with Two-dimensional Gel Electrophoresis and silver staining our goal was to find biomarkers by quantifying protein spots that differ significantly from farmers with musculoskeletal disorders compared to rural controls. In our study we found 8 significant proteins, two from Alpha-2-HS-glycoprotein, one from Apolipoprotein A1, three from Haptoglobin, one from Hemopexin and 1 from Antithrombin. All 5 proteins are involved in inflammation response in some way and some proteins are linked to chronic inflammation. Out of the 5 proteins Alpha-2-HS-glycoprotein, Apolipoprotein A1 and Hemopexin seem like the most likely proteins to investigate further as potential inflammation biomarkers.

Fault detection and isolation (FDI) are essential in ensuring safe and reliable operations in industrial systems. Extensive research has been carried out on FDI for one dimensional (1-D) systems, where variables vary only with time. The existing FDI strategies are mainly focussed on 1-D systems and can generally be classified as model based and process history data based methods. In many industrial systems, the state variables change with space and time (e.g., sheet forming, fixed bed reactors, and furnaces). These systems are termed as distributed parameter systems (DPS) or two dimensional (2-D) systems. 2-D systems have been commonly represented by the Roesser Model and the F-M model. Fault detection and isolation for 2-D systems represent a great challenge in both theoretical development and applications and only limited research results are available. In this thesis, model based fault detection strategies for 2-D systems have been investigated based on the F-M and the Roesser models. A dead-beat observer based fault detection has been available for the F-M model. In this work, an observer based fault detection strategy is investigated for systems modelled by the Roesser model. Using the 2-D polynomial matrix technique, a dead-beat observer is developed and the state estimate from the observer is then input to a residual generator to monitor occurrence of faults. An enhanced realization technique is combined to achieve efficient fault detection with reduced computations. Simulation results indicate that the proposed method is effective in detecting faults for systems without disturbances as well as those affected by unknown disturbances.The dead-beat observer based fault detection has been shown to be effective for 2-D systems but strict conditions are required in order for an observer and a residual generator to exist. These strict conditions may not be satisfied for some systems. The effect of process noises are also not considered in the observer based fault detection approaches for 2-D systems. To overcome the disadvantages, 2-D Kalman filter based fault detection algorithms are proposed in the thesis. A recursive 2-D Kalman filter is applied to obtain state estimate minimizing the estimation error variances. Based on the state estimate from the Kalman filter, a residual is generated reflecting fault information. A model is formulated for the relation of the residual with faults over a moving evaluation window. Simulations are performed on two F-M models and results indicate that faults can be detected effectively and efficiently using the Kalman filter based fault detection. In the observer based and Kalman filter based fault detection approaches, the residual signals are used to determine whether a fault occurs. For systems with complicated fault information and/or noises, it is necessary to evaluate the residual signals using statistical techniques. Fault detection of 2-D systems is proposed with the residuals evaluated using dynamic principal component analysis (DPCA). Based on historical data, the reference residuals are first generated using either the observer or the Kalman filter based approach. Based on the residual time-lagged data matrices for the reference data, the principal components are calculated and the threshold value obtained. In online applications, the T2 value of the residual signals are compared with the threshold value to determine fault occurrence. Simulation results show that applying DPCA to evaluation of 2-D residuals is effective.

A system for recording the trajectories of non-planar shocks and particle tracers within a shock tube flow has been developed. The optics consists of a double-pass schlieren system with a multiply pulsed ruby laser as light source. The laser is synchronized with a high speed framing camera. A grid of ammonium chloride tracers is injected into the flow field, and the motion of the tracers behind the Mach reflection of intermediate strength shocks has been recorded. Analysis of the trajectories has yielded the space and time variation of the physical properties within the flow field. / Graduate / 0605

Doctor of Philosophy (PhD) / The glass-transition traverses continuously from liquid to solid behaviour, yet the role of structure in this large and gradual dynamic transition is poorly understood. This thesis presents a theoretical study of the relationship between structure and dynamics in two-dimensional glass-forming alloys, and provides new tools and real-space insight into the relationship at a microscopic level. The work is divided into two parts. Part I is concerned with the role of structure in the appearance of spatially heterogeneous dynamics in a supercooled glass-forming liquid. The isoconfigurational ensemble method is introduced as a general tool for analysing the effect that a configuration has on the subsequent particle motion, and the dynamic propensity is presented as the aspect of structural relaxation that can be directly related to microscopic variations in the structure. As the temperature is reduced, the spatial distribution of dynamic propensity becomes increasingly heterogeneous. This provides the first direct evidence that the development of spatially heterogeneous dynamics in a fragile glass-former is related to spatial variations in the structure. The individual particle motion also changes from Gaussian to non- Gaussian as the temperature is reduced, i.e. the configuration expresses its character more and more intermittently. The ability of several common measures of structure and a measure of structural ‘looseness’ to predict the spatial distribution of dynamic propensity are then tested. While the local coordination environment, local potential energy, and local free volume show some correlation with propensity, they are unable to predict its spatial variation. Simple coarse-graining does not help either. These results cast doubt on the microscopic basis of theories of the glass transition that are based purely on concepts of free volume or local potential energy. In sharp contrast, a dynamic measure of structural ‘looseness’ - an isoconfigurational single-particle Debye-Waller (DW) factor - is able to predict the spatial distribution of propensity in the supercooled liquid. This provides the first microscopic evidence for previous correlations found between short- and long-time dynamics in supercooled liquids. The spatial distribution of the DW factor changes rapidly in the supercooled liquid and suggests a picture of structural relaxation that is inconsistent with simple defect diffusion. Overall, the work presented in Part I provides a real-space description of the transition from structure-independent to structure-dependent dynamics, that is complementary to the configuration-space description provided by the energy landscape picture of the glass transition. In Part II, an investigation is presented into the effect of varying the interparticle potential on the phase behaviour of the binary soft-disc model. This represents a different approach to studying the role of structure in glass-formation, and suggests many interesting directions for future work. The structural and dynamic properties of six different systems are characterised, and some comparisons are made between them. A wide range of alloy-like structures are formed, including substitutionally ordered crystals, amorphous solids, and multiphase materials. Approximate phase diagrams show that glass-formation generally occurs between competing higher symmetry structures. This work identifies two new glass-forming systems with effective chemical ordering and substantially different short- and medium-range structure compared to the glassformer studied in Part I. These represent ideal candidates for extending the study presented in Part I. There also appears to be a close connection between quasicrystal and glass-formation in 2D via random-tiling like structures. This may help explain the experimental observation that quasicrystals sometimes vitrify on heating. The alignment of asymmetric unit cells is found to be the rate-limiting step in the crystal nucleation and growth of a substitutionally ordered crystal, and another system shows amorphous-crystal coexistence and appears highly stable to complete phase separation. The generality of these results and their implications for theoretical descriptions of the glass transition are also discussed.

Thesis (M.S.)--Youngstown State University, 2008. / Includes bibliographical references (leaves 50-53). Also available via the World Wide Web in PDF format.

Thesis (M.S.)--Rochester Institute of Technology, 2007. / Typescript. Includes bibliographical references (leaves 91-98).

Semiconducting nanocrystals in open-access microcavities are promising systems in which enhanced light-matter interactions lead to quantum effects such as the modulation of the spontaneous emission process and exciton-polariton formation. In this thesis I present improvements of the open cavity platform which serves to confine the electromagnetic field with mode volumes down to the λ³ regime and demonstrate results in both the weak and strong coupling regimes of cavity quantum electrodynamics with a range of different low-dimensional materials. I report cavity fabrication details allowing a peak finesse of 5 × 10⁴ and advanced photonic structures such as coupled cavities in the open cavity geometry. By incorporating two-dimensional materials and nanoplatelets in the cavity I demonstrate the strong coupling regime of light-matter interaction with the formation of exciton-polaritons, quasi-particles composed of both photon and exciton, at room temperature. In the perturbative weak coupling regime I show pronounced modulation of the single-photon emission from CdSe/ZnS quantum dots and the two-dimensional material WSe₂ and demonstrate Purcell enhancement of the spontaneous emission rate by factors of 2 at room temperature and 8 at low temperature. The findings presented in this thesis pave the way to establish open microcavities as a platform for a wide range of applications in nanophotonics and quantum information technologies.

A chevron is a U-shaped rock structure constructed for improving navigation conditions by diverting majority of flow towards main channel. The objective of this study is to improve understanding of how chevrons affect channel flow. For this study, a two-dimensional numerical hydrodynamic model of a two-km-long reach of the Mississippi River was developed; three chevrons have been constructed in the modeled reach. The model was calibrated by adjusting Manning's n to match predicted and observed water surface elevations (WSELs). The model was validated using measured WSEL and velocity data from two events: a low-flow discharge (4,500 m3/s) and high-flow discharge (14,000 m3/s). At reach scale the model performed well in predicting WSELs. Average difference between model prediction and observed WSEL was 0.23 m in low-flow condition and 0.05 in high flow condition. Root mean square of errors (RMSEs) and mean absolute errors (MAEs) were used to measure the degree of agreement between predicted and measured velocities. At the reach scale there was reasonable agreement between predicted and observed velocities (RMSE = 0.416 m/s and 0.425 m/s, respectively, for low-flow and high-flow conditions). Local differences between predicted and observed velocities were up to 1.5 m/s; this is attributed to uncertainties in the velocity measurements. The model's sensitivity of to changes in Manning's n, eddy viscosity and bathymetry were also analyzed. The sensitivity analysis showed that there are specific areas (e.g., near the banks of the river) which are sensitive to changes in Manning's n. This indicates that spatial distribution of Manning's n is required to increase the accuracy in the model's predictions of velocity. Model was found to be stable in a specific range of eddy viscosity values. Eddy viscosity had little effect on velocity predictions but was important for model stability (i.e., the model was stable only for a range of eddy viscosity values). Reach scale changes in bathymetry had minor impacts on RMSE and MAE. However, local changes in channel bathymetry resulted in differences in velocity predictions as much as ±0.4 m/s.