Physical Sciences and Mathematics Commons^™

A Viscous Flow Analog To Prandtl’S Optimized Lifting Line Theory Utilizing Rotating Biquadratic Bodies Of Revolution, Mark Nathaniel Callender

Doctoral Dissertations

Prandtl’s lifting line theory expanded the Kutta-Joukowski theorem to calculate the lift and induced drag of finite wings. The circulation distribution about a real wing was represented by a superposition of infinitesimal vortex filaments. From this theory, the optimum distribution of circulation was determined to be elliptical. A consequence of this theory led to the prediction that the elliptical chord distribution on a real fixed wing would provide the elliptical circulation distribution. The author applied the same line of reasoning to lift-producing rotating cylinders in order to determine the cylindrical geometry that would theoretically produce an elliptical circulation distribution. The …

Bayesian Dictionary Learning For Single And Coupled Feature Spaces, Li He

Doctoral Dissertations

Over-complete bases offer the flexibility to represent much wider range of signals with more elementary basis atoms than signal dimension. The use of over-complete dictionaries for sparse representation has been a new trend recently and has increasingly become recognized as providing high performance for applications such as denoise, image super-resolution, inpaiting, compression, blind source separation and linear unmixing. This dissertation studies the dictionary learning for single or coupled feature spaces and its application in image restoration tasks. A Bayesian strategy using a beta process prior is applied to solve both problems.

Firstly, we illustrate how to generalize the existing beta …

Characterization Techniques And Electrolyte Separator Performance Investigation For All Vanadium Redox Flow Battery, Zhijiang Tang

Doctoral Dissertations

The all-vanadium redox flow battery (VRFB) is an excellent prospect for large scale energy storage in an electricity grid level application. High battery performance has lately been achieved by using a novel cell configuration with advanced materials. However, more work is still required to better understand the reaction kinetics and transport behaviors in the battery to guide battery system optimization and new battery material development. The first part of my work is the characterization of the battery systems with flow-through or flow-by cell configurations. The configuration difference between two cell structures exhibit significantly different polarization behavior. The battery output can …

Modeling And Control Of Nanoparticle Bloodstream Concentration For Cancer Therapies, Scarlett S. Bracey

Doctoral Dissertations

Currently, the most commonly used treatments for cancerous tumors (chemotherapy, radiation, etc.) have almost no method of monitoring the administration of the treatment for adverse effects in real time. Without any real time feedback or control, treatment becomes a "guess and check" method with no way of predicting the effects of the drugs based on the actual bioavailability to the patient's body. One particular drug may be effective for one patient, yet provide no benefit to another. Doctors and scientists do not routinely attempt to quantifiably explain this discrepancy. In this work, mathematical modeling and analysis techniques are joined together …

Online Multi-Stage Deep Architectures For Feature Extraction And Object Recognition, Derek Christopher Rose

Doctoral Dissertations

Multi-stage visual architectures have recently found success in achieving high classification accuracies over image datasets with large variations in pose, lighting, and scale. Inspired by techniques currently at the forefront of deep learning, such architectures are typically composed of one or more layers of preprocessing, feature encoding, and pooling to extract features from raw images. Training these components traditionally relies on large sets of patches that are extracted from a potentially large image dataset. In this context, high-dimensional feature space representations are often helpful for obtaining the best classification performances and providing a higher degree of invariance to object transformations. …

Fully Coupled Fluid And Electrodynamic Modeling Of Plasmas: A Two-Fluid Isomorphism And A Strong Conservative Flux-Coupled Finite Volume Framework, Richard Joel Thompson

Doctoral Dissertations

Ideal and resistive magnetohydrodynamics (MHD) have long served as the incumbent framework for modeling plasmas of engineering interest. However, new applications, such as hypersonic flight and propulsion, plasma propulsion, plasma instability in engineering devices, charge separation effects and electromagnetic wave interaction effects may demand a higher-fidelity physical model. For these cases, the two-fluid plasma model or its limiting case of a single bulk fluid, which results in a single-fluid coupled system of the Navier-Stokes and Maxwell equations, is necessary and permits a deeper physical study than the MHD framework. At present, major challenges are imposed on solving these physical models …

Evaluating Predictability In The Community Earth System Model In Response To The Eruption Of Mount Pinatubo, Abigail Laurel Gaddis

Doctoral Dissertations

A central goal of climate research is to determine the perceptible effects of climate change on humans; in other words, the regional and decadal scale effects of carbon dioxide forcing. Identifying the most pronounced and long-lasting responses of climate variables to forcing is important for decadal prediction since forcing terms are a source of predictability on those time scales. Powerful volcanic eruptions provide a transient forcing on the climate system, creating a test bed for climate models. In this study, the Mount Pinatubo eruption is simulated in the Community Earth System Model, CESM1.0, for three model configurations: fully coupled T85 …

Investigation Of Time And Position Resolved Alpha Transducers For Multi-Modal Imaging With A D-T Neutron Generator, Joshua William Cates

Doctoral Dissertations

Deuterium-Tritium (D-T) neutron generators have been used as an active interrogation source for associated particle imaging (API) techniques. The D-T reaction yields a 14.1 MeV neutron and a 3.5 MeV alpha (or assoicated) particle, projected nearly back-to-back. The kinetics of the reaction allow the direction and initial time of the neutron to be determined utilizing position sensitive detectors for both the alpha and neutron. This information facilitates multi-modal fast neutron imaging of inspection objects and closed containers to infer the geometry within them and the presence of special nuclear material (SNM). Since position and time of interaction of the alpha …

Novel Bimetallic Plasmonic Nanomaterials, Ritesh Sachan

Doctoral Dissertations

Plasmonic nanomaterials have attracted a lot of attention recently due to their application in various fields such as chemical and biological sensing, catalysis, energy harvesting and optical devices. However, there is a need to address several outstanding issues with these materials, including cost-effective synthesis, tunability in plasmonic characteristics, and long term stability. In this thesis, we have focused on bimetallic nanoparticles (NPs) of Ag and Co due to their immiscibility as well as their individual properties. First, a pulsed laser induced dewetting route was used to synthesize Ag-Co bimetallic plasmonic NPs. An synthesis parameter space was derived to show the …

Femtosecond Laser Patterned Templates And Imprinted Polymer Structures, Deepak Rajput

Doctoral Dissertations

Femtosecond laser machining is a direct-write lithography technique by which user-defined patterns are efficiently and rapidly generated at the surface or within the bulk of transparent materials. When femtosecond laser machining is performed with tightly focused amplified pulses in single-pulse mode, transparent substrates like fused silica can be surface patterned with high aspect ratio (>10:1) and deep (>10 μm) nanoholes. The main objective behind this dissertation is to develop single-pulse amplified femtosecond laser machining into a novel technique for the production of fused silica templates with user-defined patterns made of high aspect ratio nanoholes. The size of the …

Multiscale Modeling Of Enzyme-Catalyzed Methanol Production By Particulate Methane Monooxygenase, Katherine K. Bearden

Doctoral Dissertations

In this work, the conversion of methane to methanol by the particulate Methane Monooxygenase (pMMO) enzyme is investigated using a multi-scale modeling approach. This enzyme participates in carbon cycling and aids in the removal of harmful atmospheric methane, converting it to methanol. The interaction between pMMO and a neighboring enzyme that is present in the same organism is studied, and the unknown pMMO active site is elucidated and tested for methane oxidation towards the production of methanol.

Fundamental knowledge of pMMO's mechanism is not fully understood. Understanding how this enzyme works in nature will provide information towards designing efficient synthetic …

New Microarray Image Segmentation Using Segmentation Based Contours Method, Yuan Cheng

Doctoral Dissertations

The goal of the research developed in this dissertation is to develop a more accurate segmentation method for Affymetrix microarray images. The Affymetrix microarray biotechnologies have become increasingly important in the biomedical research field. Affymetrix microarray images are widely used in disease diagnostics and disease control. They are capable of monitoring the expression levels of thousands of genes simultaneously. Hence, scientists can get a deep understanding on genomic regulation, interaction and expression by using such tools.

We also introduce a novel Affymetrix microarray image simulation model and how the Affymetrix microarray image is simulated by using this model. This simulation …

Nonlinear Granger Causality And Its Application In Decoding Of Human Reaching Intentions, Mengting Liu

Doctoral Dissertations

Multi-electrode recording is a key technology that allows the brain mechanisms of decision making, cognition, and their breakdown in diseases to be studied from a network perspective. As the hypotheses concerning the role of neural interactions in cognitive paradigms become increasingly more elaborate, the ability to evaluate the direction of neural interactions in neural networks holds the key to distinguishing their functional significance.

Granger Causality (GC) is used to detect the directional influence of signals between multiple locations. To extract the nonlinear directional flow, GC was completed through a nonlinear predictive approach using radial basis functions (RBF). Furthermore, to obtain …

Using Power-Law Properties Of Social Groups For Cloud Defense And Community Detection, Justin L. Rice

Doctoral Dissertations

The power-law distribution can be used to describe various aspects of social group behavior. For mussels, sociobiological research has shown that the Lévy walk best describes their self-organizing movement strategy. A mussel's step length is drawn from a power-law distribution, and its direction is drawn from a uniform distribution. In the area of social networks, theories such as preferential attachment seek to explain why the degree distribution tends to be scale-free. The aim of this dissertation is to glean insight from these works to help solve problems in two domains: cloud computing systems and community detection.

Privacy and security are …