Physical Sciences and Mathematics Commons^™

Static And Dynamic State Estimation Applications In Power Systems Protection And Control Engineering, Ibukunoluwa Olayemi Korede

Doctoral Dissertations

The developed methodologies are proposed to serve as support for control centers and fault analysis engineers. These approaches provide a dependable and effective means of pinpointing and resolving faults, which ultimately enhances power grid reliability. The algorithm uses the Least Absolute Value (LAV) method to estimate the augmented states of the PCB, enabling supervisory monitoring of the system. In addition, the application of statistical analysis based on projection statistics of the system Jacobian as a virtual sensor to detect faults on transmission lines. This approach is particularly valuable for detecting anomalies in transmission line data, such as bad data or …

Atomic-Level Mechanisms Of Fast Relaxation In Metallic Glasses, Leo W. Zella

Doctoral Dissertations

Glasses are ubiquitous in daily life and have unique properties which are a consequence of the underlying disordered structure. By understanding the fundamental processes that govern these properties, we can modify glasses for desired applications. Key to understanding the structure-dynamics relationship in glasses is the variety of relaxation processes that exist below the glass transition temperature. Though these relaxations are well characterized with macroscopic experimental techniques, the microscopic nature of these relaxations is difficult to elucidate with experimental tools due to the requirements of timescale and spatial resolution. There remain many questions regarding the microscopic nature of relaxation in glass …

Exploring Soil Microbial Dynamics In Southern Appalachian Forests: A Systems Biology Approach To Prescribed Fire Impacts, Saad Abd Ar Rafie

Doctoral Dissertations

Prescribed fires in Southern Appalachian forests are vital in ecosystem management and wildfire risk mitigation. However, understanding the intricate dynamics between these fires, soil microbial communities, and overall ecosystem health remains challenging. This dissertation addresses this knowledge gap by exploring selected aspects of this complex relationship across three interconnected chapters.

The first chapter investigates the immediate effects of prescribed fires on soil microbial communities. It reveals subtle shifts in porewater chemistry and significant increases in microbial species richness. These findings offer valuable insights into the interplay between soil properties and microbial responses during the early stages following a prescribed fire. …

A Measurement Of Neutron Polarization And Transmission For The Nedm@Sns Experiment, Kavish Imam

Doctoral Dissertations

The D.O.E Nuclear Science Advisory Committee Long Range Plan has called for experimental programs to explore fundamental symmetry violations and their implications in nuclear, particle and cosmological physics. The neutron electric dipole moment experiment at the Spallation Neutron Source (nEDM@SNS) aims to search for new physics in the Time-reversal (T) and Charge-Parity (CP) symmetry violating sector by setting a new limit on the nEDM down to a few x 10^-28 e·cm using a novel cryogenic technique, which combines the unique properties of polarized Ultracold Neutrons (UCN), polarized ³He, and superfluid ⁴He. The experiment will employ a cryogenic …

Towards Safer Code Reuse: Investigating And Mitigating Security Vulnerabilities And License Violations In Copy-Based Reuse Scenarios, David Reid

Doctoral Dissertations

Background: A key benefit of open source software is the ability to copy code to reuse in other projects. Code reuse provides benefits such as faster development time, lower cost, and improved quality. There are several ways to reuse open source software in new projects including copy-based reuse, library reuse, and the use of package managers. This work specifically looks at copy-based code reuse.

Motivation: Code reuse has many benefits, but also has inherent risks, including security and legal risks. The reused code may contain security vulnerabilities, license violations, or other issues. Security vulnerabilities may persist in projects that copy …

Integration Of Raman Spectroscopy And Python-Based Data Analysis For Advancing Neurobiological Research, Natalie E. Dunn

Doctoral Dissertations

The field of Raman spectroscopy continues to expand into biological applications due to its usefulness as a non-invasive technique that can be utilized qualitatively and quantitatively. However, the inherent weakness of Raman scattering leads to the need for each collected spectra to undergo a preprocessing step to remove noise, background drift, and cosmic rays. Biological research in particular needs large datasets due to the increased variability in samples. As datasets grow, the need to perform preprocessing on each individual spectra becomes daunting. Often, these steps are done by hand with the help of specialized software programs. Preprocessing can be accelerated …

Short Range Correlation Measurements In The Quasielastic Region With An 11 Gev Beam, Casey Morean

Doctoral Dissertations

Electron scattering is a significant means of studying internal high momentum
nucleon and quark distributions in nuclei. Thomas Jefferson National Accelerator
Facility (JLab) with its 11GeV beam is capable of studying high momentum nucleons
with unmatched precision. The role of short range nucleon configurations and
quark distributions is significant for understanding the dynamics of nuclei and their
underlying components. Scattering cross section measurements in the kinematic
regime x > 1, where the free nucleon is forbidden, are sensitive to high momentum
nucleons, which are believed to come from short range correlations (SRCs). SRCs are
strongly interacting, high momentum nucleons with a …

Exact Models, Heuristics, And Supervised Learning Approaches For Vehicle Routing Problems, Zefeng Lyu

Doctoral Dissertations

This dissertation presents contributions to the field of vehicle routing problems by utilizing exact methods, heuristic approaches, and the integration of machine learning with traditional algorithms. The research is organized into three main chapters, each dedicated to a specific routing problem and a unique methodology. The first chapter addresses the Pickup and Delivery Problem with Transshipments and Time Windows, a variant that permits product transfers between vehicles to enhance logistics flexibility and reduce costs. To solve this problem, we propose an efficient mixed-integer linear programming model that has been shown to outperform existing ones. The second chapter discusses a practical …

Towards Expressive And Versatile Visualization-As-A-Service (Vaas), Tanner C. Hobson

Doctoral Dissertations

The rapid growth of data in scientific visualization has posed significant challenges to the scalability and availability of interactive visualization tools. These challenges can be largely attributed to the limitations of traditional monolithic applications in handling large datasets and accommodating multiple users or devices. To address these issues, the Visualization-as-a-Service (VaaS) architecture has emerged as a promising solution. VaaS leverages cloud-based visualization capabilities to provide on-demand and cost-effective interactive visualization. Existing VaaS has been simplistic by design with focuses on task-parallelism with single-user-per-device tasks for predetermined visualizations. This dissertation aims to extend the capabilities of VaaS by exploring data-parallel visualization …

Characterizing Silicate Materials Via Raman Spectroscopy And Machine Learning: Implications For Novel Approaches To Studying Melt Dynamics, Blake O. Ladouceur

Doctoral Dissertations

Silicate melt characteristics impose dramatic influence over igneous processes that operate, or have operated on, differentiated bodies: such as the Earth and Mars. Current understanding of these melt properties, such as composition, primarily comes from investigations on their volcanic byproducts. Therefore, it is imperative to innovate on modalities capable of constraining melt information in environments where a reliance on laboratory methods is severed. Recent investigations have turned to Raman Spectroscopy and amorphous volcanics as a suitable pairing for exploring these ideas. Silicate glasses are a proxy for igneous melts; and Raman spectroscopy is a robust analytical technique capable of operating …

Generative Adversarial Game With Tailored Quantum Feature Maps For Enhanced Classification, Anais Sandra Nguemto Guiawa

Doctoral Dissertations

In the burgeoning field of quantum machine learning, the fusion of quantum computing and machine learning methodologies has sparked immense interest, particularly with the emergence of noisy intermediate-scale quantum (NISQ) devices. These devices hold the promise of achieving quantum advantage, but they grapple with limitations like constrained qubit counts, limited connectivity, operational noise, and a restricted set of operations. These challenges necessitate a strategic and deliberate approach to crafting effective quantum machine learning algorithms.

This dissertation revolves around an exploration of these challenges, presenting innovative strategies that tailor quantum algorithms and processes to seamlessly integrate with commercial quantum platforms. A …

Threads, Buckets, And Impact: A Framework For Tool Accelerated Machine Learning Courses, Jonathan Adam Niemirowski

Doctoral Dissertations

Artificial intelligence and machine learning (ML) have exploded in use, accessibility, and awareness in the past few years, particularly with the release of ChatGPT in late 2022. Advances in end-user ML tools are accelerating the development of ML applications, lowering the technical barrier of entry for users outside of the computer science (CS) community. Access to ML education within STEM is mostly limited to upper-level computer science courses that have deep pre-requisite requirements or to introductory workshops that yield limited ML skills. Despite the critical need for ML education, there is a lack of guidance in instructional design for applied …

Utilizing Phylogenetic And Geochemical Techniques To Examine Echinoderms Through Time, Maggie Ryan Limbeck

Doctoral Dissertations

Understanding biotic changes through Earth’s history has been the goal of paleobiology since the inception of the field. Advances in science and technology have progressed allowing us to reassess old questions and new questions that could have not been addressed without these new methods. Echinoderms (sea stars, sea urchins, etc.) appear in the fossil record during the early Cambrian and are still abundant in marine ecosystems today. This persistence through time has made echinoderms model organisms to answer questions about Earth’s past and present. Despite this role as a model organism there are many questions that remain with respect to …

Metagenomic Investigation Of Microbial Dark Carbon Fixation, Viral Interactions, And Horizonal Gene Transfer Within A Convergent Margin Subsurface Ecosystem, Timothy Joseph Rogers

Doctoral Dissertations

Convergent margins are geological regions where two or more tectonic plates collide, and the denser “subducting slab” is pushed beneath the less dense overriding plate. As the slab descends, it devolatilizes under higher temperatures and pressures, allowing dissolved inorganic carbon (DIC) and redox active volatile rich fluids to cycle between the upper crust and Earth’s mantle. These fluids migrate through cracks and fissures in the upper mantle and crust, fueling chemolithoautotrophy-based microbial ecosystems in the subsurface before they are expelled on the surface in the form of hydrothermal seeps and springs. Chemolithoautotrophic ecosystems, such as those in the Costa Rican …

Optimizing Collective Communication For Scalable Scientific Computing And Deep Learning, Jiali Li

Doctoral Dissertations

In the realm of distributed computing, collective operations involve coordinated communication and synchronization among multiple processing units, enabling efficient data exchange and collaboration. Scientific applications, such as simulations, computational fluid dynamics, and scalable deep learning, require complex computations that can be parallelized across multiple nodes in a distributed system. These applications often involve data-dependent communication patterns, where collective operations are critical for achieving high performance in data exchange. Optimizing collective operations for scientific applications and deep learning involves improving the algorithms, communication patterns, and data distribution strategies to minimize communication overhead and maximize computational efficiency.

Within the context of this …

Theoretical Studies Of Adsorption And Reactivity At The Gas-Solid Interface, Carson J. Mize

Doctoral Dissertations

Catalytic transformations of small molecules is of great interest for both laboratory and industrial practices. Two specific transformations are ethylene to ethylene oxide and combinations of azides and alkenes into aziridine molecules. Ethylene oxide is an epoxide used as a feed-stock for many bulk reactions and commercial products such as antifreeze and various sterilization techniques, while molecules with the aziridine functional group are used for many ring opening and closing techniques as well as in pharmaceuticals and other drug treatments. For production of ethylene oxide, the combination of oxygen adsorbed onto a silver crystal is the known catalysts for thus …

Chirality, Symmetry-Breaking, And Chemical Substitution In Multiferroics, Kiman Park

Doctoral Dissertations

Multiferroic materials attract significant attention due to their potential utility in a broad range of device applications. The inclusion of heavy metal centers in these materials enhances their magnetoelectric properties, yielding fascinating physical phenomena such as the Dzyaloshinskii–Moriya interaction, nonreciprocal directional dichroism, enhancement of spin-phonon coupling, and spin-orbit-entangled ground states. This dissertation provides a comprehensive survey of magnetoelectric multiferroics containing heavy metal centers and explores spectroscopic techniques under extreme conditions. A microscopic examination of phase transitions, symmetry-breaking, and structure-property relationships enhances the fundamental understanding of coupling mechanisms.

In A2Mo3O8 (A = Fe, Zn, Ni, and Mn), we use optical spectroscopy …

Comprehensive Studies Of Magnetic Properties Of Metal-Organic Frameworks And Molecular Compounds, Pagnareach Tin

Doctoral Dissertations

Single-ion magnets (SIMs) are at the forefront of molecular electronic spin magnets with potential applications in magnetic memory storage devices. However, the magnetic properties of the SIMs are yet to be completely understood, especially the magnetic properties of large anisotropy systems. A part of this dissertation is to utilize optical and neutron spectroscopies such as far-IR magneto-spectroscopy (FIRMS) and inelastic neutron scattering (INS) to quantify the anisotropy and study the phonon properties of the SIMs as two-dimensional (2-D) metal-organic frameworks (MOFs) or coordination polymer (CP), and a molecular magnet. In addition, ab initio calculations are used to understand the origin …

The Synthesis And Optimization Of Sulfide And Halide Solid Electrolytes For All Solid-State Batteries, Teerth Brahmbhatt

Doctoral Dissertations

Countries and organizations around the world have established ambitious targets to transition away from fossil fuel-based energy sources and devices. The transition is focused on cleaning up power generation by converting coal, natural gas, and oil-based power generation to renewables and nuclear energy. Decarbonizing other sectors of energy use, transportation for example, will require broader electrification. To drive this move away from fossil fuel powered transportation will require portable energy storage devices. Conventional lithium-ion batteries are a popular candidate to lead this shift. However, these batteries often rely on flammable liquid electrolytes and carbon anodes that suffer from low energy …

Heat Pump Integrated Thermal Storage For Building Demand Response And Decarbonization, Sara Sultan

Doctoral Dissertations

This work presents a novel thermal energy storage (TES) integrated with existing residential heat pump (HP). The research focuses on controls and configuration for energy, demand, cost and carbon emissions savings for residential buildings’ energy consumption. This work will be significant in developing a framework especially for reduced energy demand and carbon emissions associated with space heating and cooling in residential buildings. Since buildings account for about 40% primary energy consumption in U.S. and half of that is associated with HP.

An existing air source HP in integrated with a phase change material (PCM) based TES via active configuration where …

Hashed Coordinate Sparse Tensor Storage With Matlab, Jama Meili Charles

Doctoral Dissertations

Tensors, or n-way arrays, are incredibly useful for storing indexable data in an arbitrary number of dimensions. Interest in tensor analysis using tensor decomposition has expanded to a variety of fields, including data mining, signal processing, computer vision, and machine learning. Tensors modelling interesting data may also be sparse, where the majority of its values are zero. These tensors can be extremely large and contain millions of entries that cannot be stored explicitly. To address this problem, various formats have arisen in the past decade to compress and compact such massive data. However, most of these existing structures are …

Precipitation Variability And Predictability Over The Arabian Peninsula, Central Southwest Asia, And Southern Africa, Matthew Francis Horan

Doctoral Dissertations

The Northern Hemisphere winter is the main rainy season for the Arabian Peninsula (AP), Central Southwest Asia (CSWA), and Southern Africa (SF), where precipitation predictability is limited or understudied. This dissertation research focuses on improving our understanding of these regions' wet-season precipitation characteristics and predictability.

First, I have identified the AP's key moisture sources through a Lagrangian back-trajectory algorithm. Mid-latitude land and water bodies, such as the Mediterranean and Caspian Seas, are the primary moisture sources in the northern region. Areas further south rely on moisture transport from the Western Indian Ocean and the African continent. A significant drying trend …

The G_2-Hitchin Component Of Triangle Groups: Dimension And Integer Points, Hannah E. Downs

Doctoral Dissertations

The image of $\PSL(2,\reals)$ under the irreducible representation into $\PSL(7,\reals)$ is contained in the split real form $G_{2}^{4,3}$ of the exceptional Lie group $G_{2}$. This irreducible representation therefore gives a representation $\rho$ of a hyperbolic triangle group $\Gamma(p,q,r)$ into $G_{2}^{4,3}$, and the \textit{Hitchin component} of the representation variety $\Hom(\Gamma(p,q,r),G_{2}^{4,3})$ is the component of $\Hom(\Gamma(p,q,r),G_{2}^{4,3})$ containing $\rho$.

This thesis is in two parts: (i) we give a simple, elementary proof of a formula for the dimension of this Hitchin component, this formula having been obtained earlier in [Alessandrini et al.], \citep{Alessandrini2023}, as part of a wider investigation using Higgs bundle techniques, …

Morphologic Analyses Of Paleozoic Rhombiferan Echinoderm Stems, Aidan R. Sweeney

Doctoral Dissertations

During the Paleozoic, echinoderms exhibited a diverse array of morphologies. This work specifically deals with an extinct stemmed group called glyptocystitoid rhombiferans. The goal of this work is to investigate functional morphology of the stem in this enigmatic group. Abnormalities in form are addressed herein by a brief literature review of teratologic features and in the description of a new species of pleurocystitid Pleurocystites? scylla. Morphologic specialization is discussed in the investigation of the internal structure and morphometrics of the mesotem of Brockocystis. Linear morphometrics, multiple imputation, and multivariate statistics were used to describe the variability exhibited in …

Reducing Communication In The Solution Of Linear Systems, Neil S. Lindquist

Doctoral Dissertations

There is a growing performance gap between computation and communication on modern computers, making it crucial to develop algorithms with lower latency and bandwidth requirements. Because systems of linear equations are important for numerous scientific and engineering applications, I have studied several approaches for reducing communication in those problems. First, I developed optimizations to dense LU with partial pivoting, which downstream applications can adopt with little to no effort. Second, I consider two techniques to completely replace pivoting in dense LU, which can provide significantly higher speedups, albeit without the same numerical guarantees as partial pivoting. One technique uses randomized …

Exploring Skyrmions Dynamics And Structure Using Neutron Scattering, W-L-Namila Chandula Liyanage

Doctoral Dissertations

Magnetic skyrmions are topologically protected chiral spin textures with great potential for next-generation consumer technologies. These magnetic structures can be described as spins continuously wrapping into a closed coplanar loop, featuring a core and fencing perimeter with opposite out-of-plane orientations. While conventional depictions of magnetic skyrmions use a two-dimensional projection, recent research underscores the importance of their three-dimensional structure in determining their topology and stability. Magnetic skyrmions typically emerge just below the curie temperature of a magnetic material, creating what is known as a skyrmion pocket. In most materials the stability pocket is at low temperatures and finite fields, however …

Dinitrogen Functionalization Using A Molybdenum Atom: Bridging The Gap Between Small And Coordination Complexes Via Quantum Mechanical Methods, Maria Virginia White

Doctoral Dissertations

Chemistry devotes a significant amount of its research to understanding small molecule activation from an electronic structure perspective to help with the investigation of the reaction pathways of catalytically active substances that can promote biomimetic catalysis. A large portion of the energy used annually in our planet is used for the artificial nitrogen fixation (Haber-Bosch process), which renders dinitrogen activation a subject of study. Molybdenum, a fourth row transitional metal, has demonstrated its effectiveness as an essential component of the dinitrogen reduction catalytic process. To better understand the multiple dinitrogen molybdenum binding modes, the work described herein combines wave function …

Insights Into The Application Of Deep Reinforcement Learning In Healthcare And Materials Science, Benjamin R. Smith

Doctoral Dissertations

Reinforcement learning (RL) is a type of machine learning designed to optimize sequential decision-making. While controlled environments have served as a foundation for RL research, due to the growth in data volumes and deep learning methods, it is now increasingly being applied to real-world problems. In our work, we explore and attempt to overcome challenges that occur when applying RL to solve problems in healthcare and materials science.

First, we explore how issues in bias and data completeness affect healthcare applications of RL. To understand how bias has already been considered in this area, we survey the literature for existing …

Clickable Lipid Precursors As Chemical Tools For Imaging And Tracking Lipids, Christelle Anne Fernandez Ancajas

Doctoral Dissertations

The regulation of lipid metabolism is crucial for maintaining the human body, as disruptions in lipid homeostasis have drastic implications. While lipids are known for their roles as energy stores as well as for cellular compartmentalization, certain lipid classes can serve as signaling agents that govern cellular behavior and physiology or as biomarkers whose concentration and spatial organization impacts cell fate. Thus, dysregulation in these processes coincide with a variety of diseases and cancers. However, the ability to track lipids has been a long-standing challenge in the area of chemical biology since lipids are chemically diverse and undergo continuous interconversion …

Reduced Order Modeling And Analysis Of Cardiac Chaos, Tuhin Subhra Das

Doctoral Dissertations

Numerous physiological processes are functioning at the level of cells, tissues and organs in the human body, out of which some are oscillatory and some are non-oscillatory. Networks of coupled oscillators are widely studied in the modeling of oscillatory or rhythmical physiological processes. Phase-isostable reduction is an emerging model reduction strategy that can be used to accurately replicate nonlinear behaviors in dynamical systems for which standard phase reduction techniques fail. We apply strategies of phase reduction, or isostable reductions in biologically motivated problems like eliminating cardiac alternans to alleviate arrhythmia by applying energy-optimal, non-feedback type control solutions.

Cardiac fibrillation caused …