Thesis (Ph.D.)--University of Rhode Island, 2005. / Includes bibliographical references (leaves 90-95).

Thesis (M. Phil.)--University of Hong Kong, 1994. / Includes bibliographical references (leaves 115-117).

Thesis (Ph. D.)--University of Florida, 1984. / Description based on print version record. Typescript. Vita. Includes bibliographical references (leaves 101-104).

Current environmental and economic trends have forced grid operators to maximize the utilization of the existing assets, which is causing systems to be operated closer to their stability limits than ever before. This requires, among other things, better knowledge and modelling of the existing power system equipment to increase the accuracy of the assessment of current stability margins.This research investigates the possibility of improving the quality of load modeling. The thesis presents a review of the traditional methods for estimation of load model parameters and proposes to use Improved Particle Swarm Optimization. Different algorithms are tested and compared in terms of accuracy, reliability and CPU requirements using computer simulations and real-data captured in a power system.Estimation of frequency and power components has also been studied in this thesis. A review of the existing methods has been provided and the use of an Unscented Kalman Filter proposed. This nonlinear recursive algorithm has been thoroughly tested and compared against selected traditional techniques in a number of experiments involving computer-generated signals as well as measurements obtained in laboratory conditions.

Biological systems, processes, and applications present modeling challenges in the form of system complexity, limited steady-state availability, and limited measurements. One primary issue is the lack of well-estimated parameters. This thesis presents two contributions in the area of modeling and parameter estimation for these kinds of biological processes. The primary contribution is the development of an adaptive parameter estimation process that includes parameter selection, evaluation, and estimation, applied along with modeling of cell growth in culture. The second contribution shows the importance of parameter estimation for evaluation of experiment and process design. / Thesis / Master of Applied Science (MASc)

Inlet distortion research has become increasingly important over the past several years as demands for aircraft flight efficiency and performance has increased. To accommodate these demands, research progression has shifted the emphasis onto airframe-engine integration and improved understanding of engine operability in less than ideal conditions. Swirl distortion, which is considered a type of non-uniform inflow inlet distortion, is characterized by the presence of swirling flow in an inlet. The presence of swirling flow entering an engine can affect the compression systems performance and operability, therefore it is an area of current research. A swirl distortion generation device created by Virginia Tech, identified as the StreamVane, has the ability to produce various swirl distortion flow profiles. In its current state, the StreamVane methodology generates a design swirl distortion at the trailing edge of the device. However, in many applications the plane at which the researcher wants a desired distortion is downstream of the StreamVane trailing edge. After the distortion is discharged from the StreamVane it develops as it moves downstream. Therefore, to more accurately replicate a desired swirl distortion at a given downstream plane, distortion development downstream of the StreamVane must be considered. Currently Virginia Tech utilizes a numerical modeling design tool, designated StreamFlow, that generates predictions of how a StreamVane-generated distortion propagates downstream. However, due to the non-linear physics of the flow problem, StreamFlow cannot directly calculate an accurate inverse solution that can predict upstream conditions from a downstream boundary, as needed to design a StreamVane. To solve this problem, in this research, an efficient estimation process has been created, combining the use of the StreamFlow model with a Markov Chain Monte Carlo (MCMC) parameter estimation tool to estimate upstream flow profiles that will produce the desired downstream profiles. The process is designated the StreamFlow-MC2 Estimation Process. The process was tested on four fundamental types of swirl distortions. The desired downstream distortion was input into the estimation process to predict an upstream profile that would create the desired downstream distortion. Using the estimated design profiles, 6-inch diameter StreamVanes were designed then wind tunnel tested to verify the distortion downstream. Analysis and experimental results show that using this method, the upstream distortion needed to create the desired distortion was estimated with excellent accuracy. Based on those results, the StreamFlow-MC2 Estimation Process was validated. / Master of Science

The collection of biological data has been limited by instrumentation, the complexity of the systems themselves, and even the ability of graduate students to stay awake and record the data. However, increasing measurement capabilities and decreasing costs may soon enable the collection of reasonably sampled time course data characterizing biological systems, though in general only a subset of the system's species would be measured. This increase in data volume requires a corresponding increase in the use and interpretation of such data, specifically in the development of system identification techniques to identify parameter sets in proposed models. In this paper, we present the results of identifiability analysis on a small test system, including the identifiability of parameters with respect to different measurements (proteins and mRNA), and propose a working definition for "biologically meaningful estimation". We also analyze the correlations between parameters, and use this analysis to consider effective approaches to determining parameters with biological meaning. In addition, we look at other methods for determining relationships between parameters and their possible significance. Finally, we present potential biologically meaningful parameter groupings from the test system and present the results of our attempt to estimate the value of select groupings. / Master of Science

In previous studies, evidence of thermal wave behavior was found in heterogeneous materials. Thus, the overall goal of this study was to experimentally verify those results, and develop a parameter estimation scheme to estimate the thermal properties of various heterogeneous materials. Two types of experiments (Experiments 1 and 2) were conducted to verify the existence or non-existence of thermal wave behavior in heterogeneous materials. In Experiment 1 sand, ion exchanger, and sodium bicarbonate were used as test materials, while processed meat (bologna) was used in Experiment 2. The measured temperature profiles of the samples were compared with the parabolic and hyperbolic heat conduction model results. The values of thermal diffusivity and thermal conductivity were obtained using the Box-Kanemasu parameter estimation method which is based on the comparison between temperature measurements and the solutions of the theoretical model. Overall, no clear experimental evidence was found to justify the use of hyperbolic heat conduction models rather than parabolic for the materials tested. Further comprehensive experimentation using different heating rates is warranted to definitely identify the accurate type of heat conduction process associated with such materials, and to describe the physical mechanisms which produce wave-like heat conduction in heterogeneous materials. / Master of Science

published_or_final_version / abstract / Electrical and Electronic Engineering / Master / Master of Philosophy

published_or_final_version / Statistics and Actuarial Science / Doctoral / Doctor of Philosophy