Digital Commons Network^™

Development, Characterization And Testing Of Traditonal And Advanced Nuclear Fuel Cladding Materials, Joshua Eddy Rittenhouse

Doctoral Dissertations

Kanthal D and FeCrAl alloys in general, are prospective candidates as accident tolerant nuclear fuel cladding materials. The work presented herein focuses on applying two techniques of severe plastic deformation, equal channel angular pressing (ECAP) and high-pressure torsion (HPT), as means of grain refinement to improve irradiation resistance. Samples of as-received, ECAP, and HPT processed Kanthal D were exposed to neutron irradiation to a dose of 2 DPA at two different temperatures, 300 °C and 500 °C. Detailed characterization was performed including mechanical and microstructural, and several positive improvements with regards to irradiation resistance were identified in the ECAP and …

Assessing And Comparing Geophysical Methods For Resolving Shallow Subsurface Geology, Abdullah Basaloom

Doctoral Dissertations

Geophysical methods are essential tools for investigating shallow subsurface structures, offering non-invasive means to characterize geological features and detect anomalies. Techniques such as electrical resistivity tomography (ERT), towed Transient Electromagnetic (tTEM), seismic refraction, magnetic, gravity, and magnetotelluric (MT) are commonly employed to image subsurface conditions with high resolution.

This study started with an in-depth analysis of comparing results co-located in space to assess uncertainties and resolution in the obtained resistivity models in the Kansas River Alluvial Aquifer (KRAA). Our results provided a quantitative interpretation of resistivity estimates between different geo-electrical methods (ERT, tTEM and DPEC). Following this, we provided a …

Design And Synthesis Of Organocatalyts For Efficient Decontamination Of Organophosphate-Based Nerve Agents And Pesticides, Emmanuel Kingsley Darkwah

Doctoral Dissertations

Exposure to organophosphate-based nerve agents and pesticides poses significant health and security threats to civilians, soldiers, and first responders. Despite extensive efforts to develop chemical detoxification agents for use in topical applications on exposed skin surfaces and for intravenous injections, there remains an unmet need for effective, non-hazardous decontaminating agents. The current state-of-the-art decontaminating agent, Dekon-139 (2,3-butanedione oxime, potassium salt), exhibits adverse effects when applied to the skin.

In this study, we designed and synthesized pharmaceutically relevant aminoguanidine-derived aldimines that are relatively non-toxic and substantially more effective at decontaminating nerve agents and pesticides compared to existing agents, and they act …

Design Of Real-Time And Energy-Efficient Driver Assist Systems Using Electroencephalogram And Neuromorphic Computing, Nathan Alan Lutes

Doctoral Dissertations

Despite the technological breakthroughs in advanced driver assist systems, distracted driving persists as a major challenge to roadway safety. This investigation advances the body of knowledge towards a solution by developing an individualized driver-state detection method using electroencephalogram (EEG) and neuromorphic computing to provide a less invasive and more energy efficient ADAS solution. It furthermore explores the changes in brain functional connectivity under distracted conditions to better understand brain state information that could be used for neuro-feedback intervention systems. The first contribution introduces the concept of using Convolutional Spiking Neural Networks (CSNNs) for recognition of patterns with movement-intention predictive power …

Novel Nano-Formulations Based On Flash Nanoprecipitation For Ocular Drug Delivery, Lin Qi

Doctoral Dissertations

Effective ocular drug delivery has always been a challenge for clinical and research. Although many nanotechnology-based formulations have been developed and showed great potential in ocular drug delivery, this is far from enough to meet clinical requirements. These studies aimed at the design and synthesis of novel nanoparticles using multi-inlet vortex mixer (MIVM) to improve ocular drug delivery efficiency. The first project involves packaging two different anti-glaucoma drugs, brimonidine (BM) and betaxolol (BX), into solid drug nanoparticles (SDNs) by MIVM, which can achieve both functions, reducing aqueous humor production and promoting aqueous humor efflux. The studies demonstrate that the SDNs …

Synthesis And Analysis Of Materials For Quantum Devices, Mathew Pollard

Doctoral Dissertations

Quantum materials play a pivotal role in the advancement of next-generation technology. Superconducting quantum computing, dissipationless spintronics, or valleytronics offer promising ways forward beyond traditional chip miniaturization. Josephson Junctions (JJs) have already revolutionized quantum information and high precision detectors. Quantum systems, however, are either hard to control, produce, and/or maintain. This calls for a better understanding of microscopic properties and tuning of these quantum states.

In this work, we experimentally investigated growth methods to control the electric and magnetic properties of Topological Insulator (TI) Sb2Te3 through Cr-doping. Our results demonstrate the onset of a Magnetic Topological Insulator (MTI) and have …

Higher-Order Statistics And Normalized Decay Analysis For Detector Deadtime Characterization, Abdallah Wazzan

Doctoral Dissertations

Detector deadtime limits radiation measurement accuracy at high count rates, yet current methods rely on idealized paralyzable or non-paralyzable models. Real detectors exhibit hybrid behavior requiring advanced characterization approaches. This study explores deadtime characterization using two Monte Carlo simulation approaches: higher-order statistical analysis of inter-arrival times and simplified deadtime correction with hybrid models.

Using MATLAB (PULSE-WIZ), we analyzed full decay curves spanning ~4.5 half-lives of Cobalt-60 and Vanadium-52, examining coefficient of variation (CV), skewness, and kurtosis of inter-arrival times, plus normalized decay curves with Full Width at Half Maximum (FWHM) analysis. Hybrid models incorporated paralyzable and non-paralyzable components with dead …

Supporting Human-Ai Interaction From User Expectations To Mental Models, Harishankar Vasudevanallur Subramanian

Doctoral Dissertations

Explainable AI (XAI) aims to unravel the "black box" nature of AI systems and provide insights into the inner workings that lead to a prediction. However, the best XAI communication varies depending on the individual, task, and broader context. It is challenging to anticipate the best XAI for a particular use case. One strategy is for users to build an appropriate mental model of AI with both prediction and system level XAI. To date, little research has focused on quantitatively measuring users interacting with system-level XAI. This dissertation has three primary contributions. The first contribution is a scoping review paper …

Enhanced Optimization Of Mass Transfer For Carbon Capture And Wastewater Remediation In Algal Systems Through Algorithmic And Bioprocessing Techniques, Peter Ofuje Obidi

Doctoral Dissertations

The scalability and industrial deployment of algal cultivation systems are limited by suboptimal mass transfer, constraining their effectiveness in carbon capture and wastewater remediation. This research investigated these challenges through integrated optimization methodologies that combine algorithmic frameworks with enhanced bioprocessing techniques to enhance efficiency, economy, and scalability. A System-of-Systems (SoS) meta-architecture was developed using genetic algorithms and fuzzy assessor functions to demonstrate a pathway toward cost reduction. Rigorous mechanical and chemical characterizations were quantitatively analyzed to reveal existing optimization strategies and further evaluated the best strategies to use in enhancing mass transfer for improved biomass yield. The work also integrates …

Introducing Triangular Groups And Further Results On Magic Groups, Nicholas Charles Fleece

Doctoral Dissertations

In this research, we discuss two new topics in group theory. First, we define an n-magic square in a group to be a nxn array of group elements whose rows, columns, and diagonals have the same product. This definition is akin to the idea of magic squares in the integers. Groups that have an n-magic square are said to be n-magic. We begin with some preliminary results and focus much of our attention on 3-magic groups, though we also give some results for higher n. Through a series of propositions, we ultimately prove a characterization theorem for 3-magic finitely generated …

Dynamic Response, Assessment, And Retrofitting Of Prestressed Concrete Bridge Girders Subjected To Lateral Impact Loads, Haitham A. Abdelmalek

Doctoral Dissertations

Over height vehicle collisions pose a growing threat to the resilience of bridge infrastructure across the United States. According to the American Road & Transportation Builders Association (ARTBA, 2024), approximately 36% of all U.S. bridges require major repair or replacement, with an estimated cost of $400 billion. This dissertation investigates the structural dynamic response, damage assessment, and retrofitting strategies for prestressed concrete (PC) bridge girders subjected to lateral impact loading.

The research comprised two main phases: (1) numerical modeling and (2) experimental testing. A validated 3D nonlinear finite element (FE) model was developed to conduct parametric studies on impact behavior, …

Nutrient Fate, Mass Balance, Species Selection, And Plant Management Strategies With Floating Treatment Wetlands, Carla Campbell

Doctoral Dissertations

Excess nutrients in shallow urban ponds can lead to harmful algal blooms, low dissolved oxygen, and internal phosphorus cycling. These effects can compromise municipal water supplies and cause negative impacts on fisheries and recreation. Floating treatment wetlands (FTWs) show promise to mitigate surface water nutrient pollution. However, despite recent research, many aspects of FTWs remain poorly characterized. The contribution of FTW components to nutrient removal, local species selection, and plant management strategies were the focus of this dissertation. Mesocosm experiments revealed that the combination of plants and coir fiber growth media in FTWs appeared to positively affect plant biomass gain …

Tailoring Selected Aerogels To Targeted Applications, Stephen Yaw Owusu

Doctoral Dissertations

Aerogels are ultra-lightweight, porous solid materials characterized by a three-dimensional nanostructured network. Owing to their exceptional physical and chemical properties, aerogels have garnered considerable attention within the materials science community and were recognized by IUPAC in 2022 as one of the top ten emerging technologies in chemistry. Although numerous aerogels have been synthesized, only a few have been effectively tailored for specific applications. Optimizing the properties of known aerogels for targeted uses remains challenging. This dissertation investigates strategies for tailoring aerogels derived from isocyanate-benzoxazine, benzodiazine, and phenolic resins to meet the requirements of various advanced applications. The approaches employed include …

Deep Learning Architecture Design For Nano-Satellite Image Super-Resolution, William Everette Symolon

Doctoral Dissertations

Increasing threats to U.S. national security satellite constellations have resulted in an increased interest in constellation resilience and satellite redundancy. NanoSats have contributed to commercial, scientific and government applications in remote sensing, communications, navigation, and research. They also have the potential to enhance satellite constellation resilience. However, the inherent size, weight, and power limitations of NanoSats enforce constraints on imaging hardware; the small lenses and short focal lengths result in imagery with low spatial resolution, which limits the utility of CubeSat images for military planning purposes and national intelligence applications. This research proposed a deep learning architecture capable of enhancing …

Advancements In Signal Processing And Image Reconstruction For Active Microwave Thermographic Measurements, Logan Martin Wilcox

Doctoral Dissertations

Active microwave thermography, or AMT, is a coupled electromagnetic-thermographic nondestructive testing and evaluation technique. AMT has found success in a variety of inspection needs in the aerospace, space, and infrastructure fields due to its unique type of thermal excitation. During an AMT inspection, a specimen is exposed to microwave energy from a radiating source (i.e., an antenna). This exposure to microwave energy results in dielectric/magnetic heating, which causes an increase in temperature and potential defect indications to manifest on an inspection surface (which is measured via an infrared camera). Due to the use of an antenna, there is a spatially …

Characterization And Deportment Of Anode Impurities In Copper Electrorefining, Charles Michael Campbell

Doctoral Dissertations

The objective of this research was to study the deportment of the group 15 elements, arsenic, antimony and bismuth during copper electrorefining. Samples were collected from six industrial copper anodes with different compositions. Specimens were physically characterized and electro refined to understand the differences in the behavior of selected impurities. Inclusions in the cast metal structures were characterized using automated scanning electron microscopy and energy dispersive spectroscopy to measure and correlate their size, shape and composition. Arsenic and lead were found to have a positive correlation between concentration and size of inclusions. Using wavelength dispersive spectroscopy, multiphase inclusions were examined, …

Data-Driven Mulitiscale Modeling Of Electrochemical Transport, Non-Linear Electrical Contact, And Additive Manufacturing Processes, Emmanuel Olugbade

Doctoral Dissertations

The growing demand for high-efficiency energy systems and advanced manufacturing technologies requires predictive frameworks that link atomic-scale physics with engineering-scale performance. This dissertation develops a unified multiscale modeling approach that integrates molecular dynamics, density functional theory, finite-element analysis, and machine learning to connect structure, transport, and performance across materials and processes. Depending on the interactions involved, the framework employs loose coupling for parameter transfer, tight coupling for two-way feedback, and hybrid coupling where machine-learning surrogates accelerate high-fidelity simulations while retaining physical interpretability. In electrochemical systems, an XGBoost-enhanced single-particle model reproduces P2D-level electrolyte potential dynamics at roughly one-hundredth the computational cost, …

Investigating The Effects Of Fly Ash On The Properties Of Silica-Deficient High Alumina Materials, Sai Akshay Ponduru

Doctoral Dissertations

This research is made up of five studies mainly focused on attaining sustainability in high alumina cements like calcium aluminate cement (CAC) and calcium sulfoaluminate belite cements (CSAB) by partially replacing them with additives and supplementary cementitious materials (SCMs) like fly ash (FA). The first study focused on understanding the reaction kinetics of CAC and FA binders at different replacement levels (i.e. between 10%-to-50% by mass) and their effect on mechanical properties. It was also shown that the reactive nature of FAs can be determined by calculating a single parameter called number of constraints (nc) derived from topological constraint theory. …

Machine Learning Models For Location Prediction, Message Routing And Path Planning For Rescue Of Underground Miners, Abhay Goyal

Doctoral Dissertations

Self-rescue during underground mine disasters is vital for miner safety. Evolving hazards and post-disaster conditions demand solutions that enable navigation under severe communication and computational constraints. Centralized systems often fail in such rugged settings, while decentralized methods—particularly Delay Tolerant Networks (DTNs), proven in battlefields and space missions—offer distinct advantages for underground applications. This research addresses five core challenges: (i) predicting miners’ next locations on low-power devices using points of interest and movement sequences; (ii) delivering timely updates on safe routes, evacuation zones, and hazardous areas; (iii) evaluating energy efficiency and comparing graph-based approaches to existing methods; (iv) enabling edge-ready frameworks, …

Optical Sensor Instrumentation For Enhanced Continuous Caster Development, Hanok Wondimagegnehu Tekle

Doctoral Dissertations

Fiber-optic sensors are an emerging technology that can enhance process monitoring and control in steelmaking. They are especially valuable in the continuous caster’s harsh environment. This dissertation presents the industrial application and demonstration of three sensor types: single-mode silica fiber with Rayleigh-based Optical Frequency Domain Reflectometry (OFDR), sapphire fiber (single-crystal alumina) with Fiber Bragg Gratings (sFBG), and an in-line Raman spectroscopy probe. Each sensor served a distinct role in the continuous caster. Rayleigh OFDR sensors were embedded in tundishes for distributed thermal mapping at 7-mm spatial resolution across ≈4 m. Measurements were taken during preheating, casting, and ladle exchanges, and …

Generalizations Of Finiteness Conditions And Extension Monads In Algebras With Infinitely Many Or Infinitary Operations, Danielle Christienne Bowerman

Doctoral Dissertations

In this work, we extend the results of finiteness conditions and extension monads found in Insall from finitely many finitary operations to infinitely many finitary operations, as well as touching on infinitary operations. We also examine varieties of algebras, including the notion of strong varieties introduced in Insall, and common constructions of extension monads in varieties of algebras. We see that for finite collections of algebras of the same signature, the extension monad operation on a variety of algebras commutes with the direct product operation, and all retractions from an enlargement or extension monad are trivial. We also see that …

Identification Of Corrosion Damage, Vibration, And Loose Conections In Aircraft Data Transmission Lines Using Reflected And Transmitted Signals; Formulation Of Vegetable Oil-Based Nanofluids As Cutting Fluids For Mql Machining, Saidanvardzhon Valiev

Doctoral Dissertations

This research presents a novel Frequency Domain Transmitometry (FDT) method that uses transmitted signals (S21) to detect and characterize aircraft data transmission lines (ADTL) corrosion damage without additional reflectometry circuitry. Corrosion experiments were conducted according to ASTM G85-A5 over 14 weeks. Combined FDT and reflected signals (S11) analyses revealed distinct three-peak signatures associated with damage and corrosion. The square root of the Area Under the Curve (AUC) of the FDT damage peak and the Full Width at Three-Quarter Maximum (FW3QM) of the S11 damage peak is correlated with corrosion propagation depth and width. S11 signals were further used for vibration …

Process-Structure-Property Relationships In Laser Powder Bed Fusion Produced 17-4 Ph Steel, Ben Brown

Doctoral Dissertations

Laser powder bed fusion (LPBF) is a metal additive manufacturing method that produces non-traditional microstructures as a result of the rapid solidification and thermal cycling inherent to the process. When using LPBF-produced material in application, these unique microstructures challenge the applicability of well-developed mechanical property databases achieved by conventional heat treatments. For wider adoption of this technology, a more holistic understanding is necessary on how process attributes develop material structure, which dictate mechanical properties. This dissertation explores the process structure-property relationships in LPBF 17-4 PH steel through systematic evaluation of atmospheric processing and heat treatment effects on microstructure and mechanical …

The Role Of Mineral Raw Material Imports In Driving The Energy Transition, Mahelet G. Fikru, Nurcan Kilinc-Ata

Economics Faculty Research & Creative Works

This study contributes to the mineral-energy nexus by examining the role of importing mineral raw materials (ores and concentrates) on subsequent progress in the energy transition among 33 countries from 1992 to 2015. We focus on net imports of ores and concentrates for five energy transition minerals (copper, cobalt aluminum, nickel, and manganese) and present an economic production framework to link the mineral raw materials with renewable electricity generation shares. The distinction between mineral raw materials and processed/refined inputs is important because processing capabilities vary among nations, influencing their import-export dynamics and energy transition strategies. Our empirical analysis based on …

Effect Of Thermomechanical Processing And Heat Treatment On The Microstructure And Mechanical Properties Of Ultra-High Strength Steels, Rogerio Antao Cardoso

Doctoral Dissertations

"A martensite-based and an austenite-based Fe-Mn-Al steels were investigated aiming the pilot-scale production of steels that meet military specifications for Rolled Homogeneous Armor (RHA) and High-hardness Armor (HHA) plates. Each material underwent specific thermomechanical processes and the following hardness, Charpy V-notch (CVN) impact toughness at -40 °C and room-temperature tensile properties were correlated with the resulting microstructures.

Specimens of the martensitic steel were austenitized at 1010 °C, quenched and tempered at 150, 175, 200, 225 and 250 °C for times up to four hours. As for the Fe-Mn-Al steel, its hot rolling schedule was design to promote strain accumulation in …

Selected Topics In Blockchain-Aided Iot Inference, Yiming Jiang

Doctoral Dissertations

"Blockchain has recently been considered in the Internet of Things (IoT) to secure data exchanges and storage across various engineering applications. This newly emerging blockchain-aided IoT (BIoT) network has been applied to a great deal of security-related applications. However, the BIoT still has the vulnerability that can be exploited by attackers, potentially impairing the performance of BIoT applications. Despite this, research addressing the vulnerability has been limited. This work presents four studies aimed at addressing critical gaps in current BIoT research.

The first study introduces a Time-Restricted Double-Spending Attack (TR-DSA) model for Proof-of-Work (PoW)-based blockchains, where the adversary only conducts …

Application Of Artificial Intelligence Techniques To Improve Leadership Decision Making With Uncertainty, Michael David Parrish

Doctoral Dissertations

"Every good leader is a good manager, but not every good manager is a good leader. The difference between the leader and the manager is critical decision-making. Today’s decision-making environment is characterized as Volatile, Uncertain, Complex, and Ambiguous (VUCA). With the exponential increase in the technical capabilities of systems, the human has become the weakest link in the use of such systems. To remain relevant, good leaders must continuously adapt to new advances in technology and processes.

The research contributions of this work provide several unique and novel solutions for leaders to utilize artificial intelligence tools to improve and optimize …

Drone-Based Multimodal Sensing On Vegetations And Data Analytics For Early Detection Of Gas Leakage From Underground Pipelines, Pengfei Ma

Doctoral Dissertations

"This study explored the feasibility of using multimodal remote sensors in the early detection of natural gas leaks from underground pipelines, as vegetation situated above pipelines can discern microbial changes in soil when affected by gas and exhibit physiological stress symptoms on leaves. Three sensors (RBG, thermal, and hyperspectral cameras) were utilized to monitor vegetation stress as an indicator of gas leaks. A laboratory experiment was conducted to evaluate the workability of vegetation for gas leak detection. Regular hyperspectral imagery was collected from test vegetations to identify gas stress and distinguish it from other environmental stressors such as salinity impact, …

Phase-Field Modeling Of Rapid Solidification Processes, Nima Najafizadeh

Doctoral Dissertations

"Many advanced manufacturing processes such as additive manufacturing utilize rapid solidification of alloys, as it enables the formation of exotic non-equilibrium microstructure and thus improved properties. However, the interrelationship between the processing parameters and the resulting microstructure in rapid solidification is yet to be fully understood. We aim to investigate the microstructure evolutions during the rapid solidifications using phase-field modeling. The phase-field method assumes a diffuse interface, which avoids tracking the moving interface and hence enables efficient numerical simulations for complex microstructure evolution. A phase-field model with coupled solute-thermal diffusion and solute trapping effect is developed to investigate the rapid …

Sensor Embedding And Thermal Monitoring Strategies For Laser-Foil-Printing Additive Manufacturing, Tunay Turk

Doctoral Dissertations

"This work investigates Laser Foil Printing (LFP), a novel metal additive manufacturing (AM) process that fabricates parts layer-by-layer using metal foils. To enhance LFP productivity, the process steps were optimized, and an 88.1% reduction in processing duration was achieved. A unique aspect of this study was the introduction of laser polishing as an edge polishing technique within the LFP process. This innovative approach, employing an overlapping spiral pattern, leverages selective laser remelting and erosion to effectively suppress elevated edges. To stabilize the molten melt pool, a discrete spot scanning strategy was implemented. The fabricated parts were subjected to detailed analysis, …