A dynamic model was developed for the distillation mechanism of the Darlington Tritium Removal Facility. The model was created using the commercial software package MATLAB/Simulink. The goal was to use such a model to predict the system behaviour for use in control analysis. The distillation system was first divided into individual components including columns, condensers, controllers, heaters and the hydraulic network. Flow streams were then developed to transfer enthalpy, pressure and mass flow rate between the components. The model was able to perform various plant transients for validation and analysis purposes. A comparison of the different controllers was made with the introduction of various disturbances to the system. Also, the effect of the system disturbances when isolated from the transients was studied using the same controllers. Studying different plant transients and disturbances under each controller enabled a comparative analysis.

A dynamic model was developed for the distillation mechanism of the Darlington Tritium Removal Facility. The model was created using the commercial software package MATLAB/Simulink. The goal was to use such a model to predict the system behaviour for use in control analysis. The distillation system was first divided into individual components including columns, condensers, controllers, heaters and the hydraulic network. Flow streams were then developed to transfer enthalpy, pressure and mass flow rate between the components. The model was able to perform various plant transients for validation and analysis purposes. A comparison of the different controllers was made with the introduction of various disturbances to the system. Also, the effect of the system disturbances when isolated from the transients was studied using the same controllers. Studying different plant transients and disturbances under each controller enabled a comparative analysis.

We consider the distributed access enforcement problem for Role-Based Access Control (RBAC) systems. Such enforcement has become important with RBAC’s increasing adoption, and the proliferation of data that needs to be protected. Our particular interest is in the evaluation of a new data structure that has recently been proposed for enforcement: the Cascade Bloom Filter. The Cascade Bloom Filter is an extension of the Bloom filter, and provides for time- and space-efficient encodings of sets. We compare the Cascade Bloom Filter to the Bloom Filter, and another approach called Authorization Recycling that has been proposed for distributed access enforcement in RBAC. One of the challenges we address is the lack of a benchmark: we propose and justify a benchmark for the assessment. Also, we adopt a statistically rigorous approach for empirical assessment from recent work. We present our results for time- and space-efficiency based on our benchmark. We demonstrate that, of the three data structures that we consider, the Cascade Bloom Filter scales the best with the number of RBAC sessions from the standpoints of time- and space-efficiency.

In the refining industry, the cost of a power system interruption is dominated by an associated loss of production. Power distribution within a refinery includes a set of production units within a highly inter-dependent process, where the outage of a single unit affects the production of additional units. This thesis proposes a method to quantify the impact of this cascading effect, called the criticality enhancement function, in which a process reliability model is introduced to link electrical outage cut-sets with lost production. Power system criticality is analyzed using four different approaches to the calculation of annual expected impact from load point interruptions on a case study of the 125,000 barrel-per-day Petro-Canada Edmonton Refinery. This thesis demonstrates how employment of the proposed technique, with its marriage of electrical and process reliability models, enables the most accurate estimation of the impact of power system interruptions.

The structure and composition of mixed-conifer forest (MCF) in central Oregon has been altered by fire exclusion and logging. The resulting increased density, spatial contagion, and loss of fire resistant trees decrease the resiliency of this ecosystem to fire, drought, and insects. The historical and current composition and structure of MCF are characterized by steep environmental gradients and a complex mixed-severity fire regime. This inherent variation makes it difficult to determine the magnitude of anthropogenic effects and set objectives for restoration and management. As a result, there is a lack of consensus regarding how MCF should be managed and restored across the landscape. My primary research objectives were to: (1) Characterize the current structure and composition of MCF and how these vary with environmental setting; and (2) Characterize establishment and tree growth patterns in MCF in different environmental settings. To address these objectives, I collected field data on structure and composition and increment cores across a range of environmental conditions in MCF of the eastern Cascades and Ochoco Mountains. I used cluster analysis to identify four stand types based on structure and composition in the eastern Cascades study area and four analogous types in the Ochoco Mountains study area. Variation in understory composition and the presence of large diameter shade tolerant species distinguish each type. Stand types occupied distinct environmental settings along a climatic gradient of increasing precipitation and elevation. At relatively dry PIPO sites understories were dominated by ponderosa pine. At wetter PIPO/PSME and PIPO ABGC sites understories were dominated by shade tolerant species, but ponderosa pine was dominant in the overstory. At the coolest and wettest PIPO/PSME/ABGC sites understories were dominated by grand fir and shade tolerant species were common in the overstory. In the eastern Cascades current density of all live trees and snags was 432, 461, 570, 372 trees per hectare (TPH) for the four stand types identified. Stand types in the drier Ochoco Mountains were currently less dense at 279, 304, 212, and 307 TPH. Current MCF densities in both areas are 2-3 times higher than densities estimated for the late 19th and early 20th centuries from other studies in those two areas. Reconstruction of cuts in each stand type indicates that the density of large diameter ponderosa pine has been reduced by approximately 50% in all stand types in both study regions. Age histograms demonstrate that current density and composition of MCF stand types is a product of abrupt increases in tree establishment following fire exclusion in the late 19th century. The number of trees established increased after 1900 in all stand types, but the timing and composition of changes in establishment varied with climate. At dry PIPO sites increases in establishment were delayed until the 1920s and 1930s and were composed of ponderosa pine. At PIPO/PSME and PIPO/ABGC sites with intermediate precipitation, establishment was dominated by ponderosa pine prior to 1900, but after 1900 establishment was dominated by a large pulse of Douglas-fir and grand fir. At the wettest PIPO/PSME/ABGC there was less evidence of changes in structure and composition over time. My results indicate that compared to dry pine and dry-mixed conifer sites, relatively productive moist mixed-conifer sites were characterized by large changes in structure and composition. Such sites could be considered more ecologically altered by lack of fire than drier forest types that had high fire frequencies but slower rates of stand development and less plant community change. Radial growth patterns of cored ponderosa pines differed between the eastern Cascades and Ochoco Mountains. In the eastern Cascades mean growth rates and variance decreased during favorable climatic periods after 1900. This is likely related to increased competition, and provides evidence that current stand density lacks a temporal analog in the 18th and 19th centuries. Sensitivity of growth to climate and harvest suggest competition for water in the denser forest of the eastern Cascades, and indicates thinning will increase the diameter growth rate of large old pines. In the Ochoco Mountains, ponderosa pine tree growth was less responsive to climate prior to fire exclusion in the late 1800s, and growth did not respond to fire events. This suggests competition among trees was historically low in this region. After fire exclusion growth became more responsive to wet and dry climatic cycles, which may indicate that increased density and competition made trees more responsive to climate variability. Patterns of slow and fast growth appeared to differ between study regions and likely differ at the sub-regional scale. Further analysis of the relationship between growth and climate in different environmental settings is needed to distinguish where stand development has been modified by disruption of fire regimes. / Graduation date: 2013

Over the last ten years, terahertz (THz or T-ray) biomedical imaging has become a modality of interest due to its ability to simultaneously acquire both image and spectral information. Terahertz imaging systems are being commercialized, with increasing trials performed in a biomedical setting. Advanced digital image processing algorithms are greatly need to assist screening, diagnosis, and treatment. Pattern recognition algorithms play a critical role in the accurate and automatic process of detecting abnormalities when applied to biomedical imaging. This goal requires classification of meaningful physical contrast and identification of information in images, for example, distinguishing between different biological tissues or materials. T-ray tomographic imaging and detection technology contributes especially to our ability to discriminate opaque objects with clear boundaries and makes possible significant potential applications in both in vivo and ex vivo environments. The Thesis consists of a number of Chapters, which can be grouped in to three parts. The first part provides a review of the state-of-the-art regarding THz sources and detectors, THz imaging modes, and THz imaging analysis. Pattern recognition forms the second part of this Thesis, which is represented via combining several basic operations: wavelet transforms and wavelet based signal filtering, feature extraction and selection, along with classification schemes for THz applications. Signal filtering in this Thesis is achieved via wavelet based de-noising. The ultrafast pulses generated terahertz time-domain spectroscopy (THz-TDS), which is demonstrated to justify their decomposition in the wavelet domain as it can provide better de-noising performance. Feature extraction and selection of the terahertz measurements rely on observed changes in pulse amplitude and phase, as well as scattering characteristics of several different types of powder samples under study. Additionally, three signal processing algorithms are adopted for the evaluation of the complex insertion loss function of such samples as lactose, mandelic acid, and dl-mandelic acid: (i) standard evaluation by ratioing the sample with the background spectra, (ii) a subspace identification algorithm, and (iii) a novel wavelet packet identification procedure. These system identification algorithms enable THz measurements to be transformed to features for THz pattern recognition. Meanwhile, a novel feature extraction method involving the use of Auto Regressive (AR) and Auto Regressive Moving Average (ARMA)models on the wavelet transforms of measured T-ray pulse responses of ex vivo osteosarcoma cells as well as other biomedical materials is presented. Classification schemes are carried out via simple and robust schemes, such as the linear Mahalanobis distance classifier, and the non-linear Support Vector Machine (SVM) classifier. In particular, SVMs are used as a learning scheme to achieve the identification of two classes of RNA samples and multiple classes of powered materials. Coherent terahertz detection hardware—THz time-domain spectroscopy (THz-TDS)—is used to obtain all the data for validation of these classification schemes. The past decade has witnessed the tremendous development of terahertz instruments for detecting, storing, analysing, and displaying images. Terahertz time-domain spectroscopy (THz-TDS) is a broadband technique that generates and detects THz radiation in a synchronous and coherent manner. By contrast, the newly developed THz quantum cascade laser is a narrow-band radiation source that provides potential for realising compact systems; they produce image data with higher average power levels. The third part of this Thesis discusses methods to improve the capability of both broad and narrow-band terahertz imaging, driven by computer-aided analytical techniques. A wavelet based reconstruction algorithm for terahertz computed tomography is represented to show how this algorithm can be used to rapidly reconstruct the region of interest (ROI) with a reduction in the measurements of terahertz responses, compared with a standard filtered back-projection technique. These reconstruction algorithms are applied to the analysis of acquired experimental data and to locally recover the two dimensional (2D) and three-dimensional (3D) structures of several optically opaque objects. Moreover, a segmentation technique based on two dimensional wavelet transforms is investigated for the identification of different materials from the reconstructed CT image. / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1352839 / Thesis (Ph.D.) - University of Adelaide, School of Electrical and Electronic Engineering, 2009

Thesis (Ph. D.)--Oregon State University, 2008. / Printout. Includes bibliographical references (leaves 138-151). Also available on the World Wide Web.

Thesis (Ph. D.)--University of Washington, 2002. / Vita. Includes bibliographical references (p. 71-76).

Typescript. Includes vita and abstract. Includes bibliographical references (leaves 155-177). Also available online in Scholars' Bank; and in ProQuest, free to University of Oregon users.

abstract: Nuclear proliferation concerns have resulted in a desire for radiation detectors with superior energy resolution. In this dissertation a Monte Carlo code is developed for calculating energy resolution in gamma-ray detector materials. The effects of basic material properties such as the bandgap and plasmon resonance energy are studied using a model for inelastic electron scattering based on electron energy-loss spectra. From a simplified "toy model" for a generic material, energy resolution is found to oscillate as the plasmon resonance energy is increased, and energy resolution can also depend on the valence band width. By incorporating the model developed here as an extension of the radiation transport code Penelope, photon processes are also included. The enhanced version of Penelope is used to calculate the Fano factor and average electron-hole pair energy in semiconductors silicon, gallium arsenide, zinc telluride, and scintillators cerium fluoride and lutetium oxyorthosilicate (LSO). If the effects of the valence band density-of-states and phonon scattering are removed, the calculated energy-resolution for these materials is fairly close to that for a toy model with a uniform electron energy-loss probability density function. This implies that the details of the electron cascade may in some cases have only a marginal effect on energy resolution. / Dissertation/Thesis / Ph.D. Physics 2011