Engineering Commons^™

Investigations Of Carbon Dioxide Storage In Low-Temperature Reservoirs For Non-Leaking Storage, Md Nahin Mahmood

Doctoral Dissertations

Carbon dioxide (CO₂) injection into subsea or low-temperature water zones has emerged as a promising strategy for long-term, non-leaking CO₂ storage through the formation of solid hydrates. This research investigates CO₂ injection into Berea sandstone cores saturated with water under simulated subsea conditions, focusing on hydrate formation behavior across varying temperatures, pressures, and injection flow rates. Experimental results demonstrate that CO₂ hydrate formation under dynamic (flowing) conditions occurs at significantly higher pressure compared to static conditions reported previously. At temperatures ranging from 0 °C to 5 °C, dynamic hydrate formation pressures were observed to be approximately double. This can be …

Multidomain Modeling And Ramp-Aware Forecasting Of Floating Photovoltaic Systems For Water-Energy Nexus Applications, Md Atiqur Rahaman

Doctoral Dissertations

Floating photovoltaic (FPV) systems have become a transformative renewable energy technology because of their cooling effects on PV performance and ability to prevent water evaporation in land-constrained areas. Although FPV systems have the potential to become a commercially viable technology, their large-scale deployment remains constrained by uncertainties in thermal behavior, sustainability, and grid-operational variability. This dissertation identifies and characterizes these three key issues and presents an integrated, measurement-based evaluation of a 130 kW FPV installation located at the Passaúna reservoir in Brazil. In the first contribution, four temperature models, including physical and empirical models, were developed and comparatively evaluated to …

Geometric Effects Of Warfighters On Body Armor Fit And Protective Capabilities Against Shock Wave Energy, Melissa Lynn Sutter

Doctoral Dissertations

Body armor is a vital piece of protective equipment for warfighters to defend against threats, necessitating continued development to improve comfort, weight, and protection. However, female warfighters often wear unisex body armor, designed primarily for the male torso. Current research has evaluated the short- and long-term detriments of female warfighters wearing these armors, focusing on comfort and performance. However, these studies do not comprehensively consider how a non-form-fitting armor compromises warfighter safety from battlefield threats. This research examines the geometric effects of female warfighters on armor protection level when defending against shock threats by evaluating the energy distribution on a …

Adaptive Machine Learning Framework For Microstructural Optimization And Mechanical Performance Prediction In Steels, Henry Adekola Haffner

Doctoral Dissertations

Evolution of microstructures, such as polygonal ferrite, acicular ferrite, bainite, and martensite, plays a pivotal role in determining the final microstructural and mechanical properties of steel products. Given the established inter-relationship between processing parameters, microstructure, properties, and performance, precise control of phase transformation is essential to achieve pre-determined properties. To understand transformation routes in different steel grades, time-temperature-transformation (TTT) and continuous-cooling-transformation (CCT) diagrams are necessary and can be described using the Johnson-Mehl-Avrami-Kolmogorov equation and Scheil’s additivity rule. This study presents a comprehensive computational framework for predicting and optimizing microstructure and mechanical properties in advanced high-strength steels (AHSS) using adaptive machine …

Manufacturing And Performance Evaluation Of Carbon/Epoxy Laminated Composites Cured Using Single- And Six-Magnetron Microwave Applications, Nayan Pundhir

Doctoral Dissertations

Microwave curing is fast, energy-efficient, and a viable alternative to conventional thermal curing processes. It has been widely adopted for processing carbon fiber-reinforced polymer (CFRP) composites because the high electrical conductivity of carbon fibers enables strong microwave coupling, leading to rapid volumetric heating and reduced energy consumption. The aim of this study is to investigate the use of microwave curing for manufacturing CFRP composites. IM7/Cycom 5320-1 unidirectional prepreg was utilized to fabricate laminated composites in two thickness ranges: 16-layer laminates (2.5 mm thickness) and 64-layer laminates (9.2 mm thickness). Two lay-up configurations were examined: symmetric cross-ply and quasi-isotropic. Different curing …

Investigations In Hydrogen Ironmaking, Joseph William Govro

Doctoral Dissertations

The purpose of this research is to contribute to the Grid Interactive Steelmaking with Hydrogen (GISH) project. This research investigates the viability of both producing and melting Direct-Reduced Iron (DRI) utilizing hydrogen. Conventional CO reduced DRI will be referred to as “C-DRI” and DRI produced using hydrogen gas will be referred to as “H-DRI”.

An H-DRI pilot plant was constructed in Golden Colorado. The pilot plant was commissioned and successfully operated four campaigns. Process improvements were made throughout the campaigns and the process was optimized. In addition to running the pilot plant in a pure hydrogen condition, the pilot plant …

Zirconium Carbide Based Materials For Extreme Aerospace Environments, Nathaniel Hyman Blatt

Doctoral Dissertations

This research focuses on the processing and properties of zirconium carbide-based materials to promote their use in extreme environment aerospace applications, including nuclear thermal propulsion and hyper sonics. Several carbide systems including ZrC, ZrC-Mo cermets, (Zr, Nb)C, and a high entropy carbide were developed. The ZrC-Mo cermet was studied extensively to understand the effect of starting carbide grain size on the final microstructure, composition, elastic moduli, hardness, fracture toughness, room and elevated temperature flexural strength, thermal diffusivity, electrical resistivity, thermal expansion coefficient, and thermal conductivity. It was shown that heat transport in the cermets was dominated by the ZrC phase …

Machine Learning Based Automation Of Pcb Pdn Design And Optimization, Haran Manoharan

Doctoral Dissertations

The rapid increase in power density and stringent power-integrity requirements in modern System-on-Chip (SoC) platforms have made Power Delivery Network (PDN) design an increasingly complex, multi-stage challenge. Critical decisions must be made both during pre-layout planning, such as stackup configuration, power-plane geometry, and early decoupling capacitor (decap) budgeting, and during post-layout refinements. Traditional heuristic and evolutionary optimization techniques struggle with scalability, require extensive manual iteration, leading to long runtimes and limited adaptability across varying board configurations. To address these challenges, this work proposes a unified reinforcement-learning-driven framework for automated PDN synthesis and decap optimization that spans both pre-layout and post-layout …

Incremental Cluster Validity Indices And Their Role In Interpreting Lifelong Learning Systems, Niklas Max Melton

Doctoral Dissertations

Clustering and supervised learning are often treated as distinct paradigms, yet both rely on structure in feature space. This dissertation investigates the relationship between cluster validity indices (CVIs) and supervised learning in real-time and lifelong learning settings where data arrive incrementally and cannot be revisited. Across four studies, it develops methods for online cluster validation, uses supervised learning to improve their interpretability, and applies these ideas to evaluating performance degradation in continual learning.

The first study extends incremental cluster validity indices (iCVIs), enabling widely used validation metrics to operate in streaming environments. Experiments on synthetic and real-world datasets show systematic …

Advancing Coal Rib Support Design Through The Integration Of Field Studies And Numerical Simulations, Alper Kirmaci

Doctoral Dissertations

Coal rib stability remains a major safety concern in U.S. underground coal mines, with rib failure-related injuries and fatalities still occurring. A key challenge is the lack of a standardized methodology for designing rib support systems that can address varying geological conditions. As a result, many mines rely on trial-and-error or traditional practices, leading to inconsistent designs. This research aims to develop a systematic methodology for rib support design to improve coal rib stability in U.S. mining operations.

The study consists of: i) field monitoring in active room-and-pillar coal mines, ii) in-situ pull-out tests on coal ribs, iii) numerical model …

Critical Parameters Controlling Oxide Scale Formation And Hydro-Descaling Efficiency During Steelmaking, Tochukwu Princewill Ojiako

Doctoral Dissertations

In modern steelmaking, cast slabs are exposed to high-temperature oxidizing environments during secondary cooling, reheating, and hot rolling, resulting in the formation of multilayer oxide scales on the steel surface. These scales interact with mold-flux residues originating from the casting process (CC). The morphology, chemistry, and adhesion of oxide scale strongly influence its removability during high-pressure hydraulic descaling and ultimately determine the surface quality of hot-rolled products. However, the mechanistic relationship between oxide scale evolution, scale-steel interfacial structure, and hydraulic descaling performance remains poorly understood.

This dissertation investigates oxide scale formation, modification, and removal in low-carbon thin-slab steels produced by …

Strontium Titanate For Capacitor And Energy Storage Applications At Cryogenic Temperatures, Hung Trinh

Doctoral Dissertations

This study investigates the dielectric properties of single crystal and ceramic strontium titanate (SrTiO₃) for cryogenic capacitor applications from room temperature to 4 K. Permittivity (k) and loss tangent are dependent on temperature, frequency, mechanical stress, and applied DC electric field. Accordingly, the dielectric constant and loss tangent were measured at various frequencies and DC bias levels. Loss tangent data are also presented as equivalent series resistance (ESR). For single crystal SrTiO₃, an impurity level of ≈500 ppm barium resulted in an increase of the maximum permittivity to approximately 50,000 at 6 K. This relatively high …

Secret Key Generation Based On The Physical Layer Characteristics For Iot Networks, Abdullah Dakhlallah Alshamdayn

Doctoral Dissertations

The rapid expansion of low-resource devices, coupled with advances in telecommunications, has significantly increased the number of connected devices and enabled the development of affordable, energy-efficient, portable, and high-performance sensors for diverse applications. However, this convenience comes with security and privacy concerns related to the reliability of hardware, software, and communication infrastructure. The extensive interconnectivity of limited-resource devices and the transmission of large data volumes pose significant security challenges in wireless networks. The future wireless technologies, such as 5G, will enable the transfer of critical data, including personal, financial, military, and industrial information, necessitating secure communication in wireless networks. Generally, …

Advanced Plant Growth Using Halloysite Nanotubes (Hnts) And Waste Extraction For Medical Applications, Zeinab Jabbari Velisdeh

Doctoral Dissertations

This dissertation presents an integrated research framework that bridges nanotechnology, green chemistry, and sustainable agriculture, aiming to address two critical global challenges: enhancing plant growth under resource-limited conditions and valorizing agricultural waste for bioactive compound extraction. The study is divided into three major projects that together highlight the innovative application of magnesium oxide-coated halloysite nanotubes (MgO-HNTs) and the development of environmentally conscious extraction methods for high-value phytochemicals. The first component of this work investigates the design, fabrication, and functional evaluation of MgO-HNTs as advanced nanocarriers for promoting seed germination and early root development in tomato plants. MgO-HNTs were synthesized via …

Towards Robust Autonomous Systems: Handling Multi-Modal Uncertainties In Gps-Denied Environments, Vivya Kalidindi

Doctoral Dissertations

This dissertation focuses on designing a robust and uncertainty-aware framework for autonomous systems operating in GPS-denied environments, such as indoor infrastructures, underground tunnels, and lunar surfaces. The proposed framework addresses the challenges posed by multi-modal uncertainties, including sensor noise, distributional shifts under adverse conditions, and conflicting decision-making preferences. These challenges compromise the reliability and adaptability of autonomous platforms. To overcome these challenges, the proposed framework adopts a layered architecture that integrates advanced methodologies across the sensing, perception, and decision-making layers. At the sensing layer, an Edge-Kalman Filter combined with a density ratio-based update mechanism is employed to reduce aleatoric uncertainty …

Investigation Of Electrochemical Corrosion Fatigue Mitigation Strategies For Mild Carbon Steel, Joel Andrew Hudson

Doctoral Dissertations

Corrosion fatigue remains a critical durability challenge for steels used in boiler tubes and other safety-critical components, where the interaction of cyclic stresses and corrosive environments accelerates material degradation. This dissertation comprises three experimental studies aimed at advancing mitigation strategies and test methodologies: (1) enhancing corrosion resistance through electrodeposited Fe-Ni anodic coatings, (2) inducing synthetic crack closure to suppress fatigue crack growth, and (3) developing an accessible, low-cost, automated testing system to investigate environmentally assisted cracking (EAC) under controlled laboratory conditions. The first study examined the corrosion behavior of Fe and Fe-Ni electrodeposits synthesized from sulfate-based baths and applied to …

Posture - A Framework With Measures And Mediating Effects In Support Of A Structural Model For Attitude In Identity Formation, Christopher Kyle Prather

Doctoral Dissertations

This dissertation develops a framework and new, valid, abbreviated instruments for researching engineering identity formation as an evolving relational and attitudinal development process rather than a fixed outcome. The framework centers on “posture”, a mediating effect analogous to physical posture in human factors engineering. The investigation was unique, and developed evidence for a structural model using an interdisciplinary, systems-oriented approach. Methodologically, a clinical measure of internal emotional states from the Marriage and Family Therapy literature was administered alongside existing scales for perseverance, perceived workload, and psychological ownership. This study used the broad coverage of the clinical instrument to search for …

Advancing Rfid Systems: From Head Orientation To Robotic Localization Using Passive Tags, Guilherme Ricardo Mendes Da Silva Barreto De Figueiredo

Doctoral Dissertations

No abstract provided.

An Envisioned And Efficient Design Of Next Generation Decentralized Iot Bot Detection Model, Ahmed Abdullah Almalki

Doctoral Dissertations

The Industrial Internet of Things (IIoT) and Internet of Medical Things (IoMT) are revolutionizing critical infrastructures, but their expansion has also introduced severe cybersecurity vulnerabilities. Traditional IoT Bot Detection Systems (IBDS) struggle to scale in environments characterized by high-dimensional, large-scale, and redundant network traffic. These challenges hinder the development of reliable cloud-based intrusion detection systems. The limitations of static and rulebased methods in detecting evolving IoT botnet attacks—such as those launched by Mirai and Gafgyt—underscore the need for intelligent, adaptive approaches. To address this, the present study proposes a machine learning and deep learning-driven IoT Botnet Detection Model, validated through …

Detection And Mitigation Of Out-Of-Band Channel Wormhole Attack In Wireless Network Using Propagation Delay, Harry May

Doctoral Dissertations

Wireless networks, susceptible to a range of attacks due to their simplicity and ease of evasion, face a significant threat from control data attacks, notably the elusive wormhole attack. Detecting and mitigating such attacks poses challenges, particularly in the absence of a digital signature. This dissertation introduces an innovative approach that utilizes the propagation delay associated with malicious nodes’ timing characteristics for detection, employing the Ad-hoc On-Demand Distance Vector (AODV) algorithm as its foundation. The inherent propagation delay in the AODV protocol is calculated for each node link along the entire communication path, offering a distinctive timing method that provides …

Encryption With Synchronized Chaos Using Fabricated Cobalt Ferrite Memristors, Kiran Sai Seetala

Doctoral Dissertations

No abstract provided.

Multiscale Materials Characterization And In-Situ Process Monitoring In Additive Manufacturing Via Non-Contact Optical Thermometry Techniques, Rifat-E-Nur Hossain

Doctoral Dissertations

While additive manufacturing (AM) is experiencing rapid growth, its development is uneven across different branches. Some areas are still emerging, while even the more established branches are still facing ongoing challenges that require further development. Regardless of their development stage, both emerging and mature AM require process monitoring and part characterization. Process monitoring helps to achieve more control over the process and build a self-adaptive system, while characterization of printed parts speeds up process optimization and ensures required quality. Together, process monitoring and build characterization will transform AM into a more dependable and commercially viable technique. Build surface temperature is …

Solid-State Crystallization Of Zeolites And Their Use In Plastic Upcycling Applications, Yixin Liao

Doctoral Dissertations

Plastics have been an irreplaceable component of modern technology as well as everyday life. They have brought much convenience to us with their characteristics of great malleability, durability, and stability. The versatile and low-cost nature of plastics also enables their wide engagement in many modern industries including automobile, medical, communication as well as aerospace. Polyethylene (“PE”), made from polymerization of ethylene, is one of the most widely used plastics in the world. Being cheap, flexible, and long-lasting, they are extensively used in the packaging industry, especially for plastic bags and other sorts of containers. However, the durability of plastics, on …

Real-Time Prediction Of Dynamical Systems Using A Hybrid Analog Computer: Network Traffic Modeling, Majd Zuhair Tahat

Doctoral Dissertations

As the number of online users grows exponentially, the number and severity of cyber threats escalate, urgently requiring advancements in real-time network modeling and response. Swiftly predicting and analyzing network traffic is crucial for effective network monitoring and control, preventing cyber breaches, and maintaining healthy network functionality. This research presents a novel approach to real-time modeling based on analyzing evolving properties and patterns in a dynamical network system using a hybrid analog-digital computer. An analog computer was utilized as a co-processor to compute differential equations that model the Transmission Control Protocol (TCP) window size. A comparative analysis was conducted between …

A Human-In-The-Loop Framework For Scalable And Interpretable Event Triaging In Large-Scale Systems, Ibrahim Khaled Al-Agha

Doctoral Dissertations

This dissertation presents a comprehensive and scalable framework for real-time fault detection and event triage in industrial systems, addressing critical challenges such as class imbalance, ambiguous feature boundaries, and the prioritization of complex, high-dimensional event data. The proposed framework integrates advanced methodologies, including micro-batch processing, retrospective divergence-based event detection (DB-RED), association rule mining (ARM), clustering, and Dempster-Shafer Theory (DST) for conflict resolution. Together, these components enable the systematic stratification of events into actionable priority levels, ensuring robust and interpretable decision-making in real-time environments. DB-RED forms the cornerstone of the framework, leveraging KL-divergence and PE-divergence metrics to detect subtle and transient …

Creating A Framework To Develop Project-Based Platforms To Support Engineering And Technology Education, Casey Daniel Kidd

Doctoral Dissertations

Engineering education has evolved over the last few decades to increasingly include project-based learning (PBL) throughout the curriculum to give students more hands-on experience. However, there can be a hesitancy from faculty and instructors to move from traditional lectures to PBL-based curricula. Research has been conducted to identify barriers to research-based instructional strategies (RBIS), which include PBL. However, this research does not go into depth about the specific barriers for these individual RBIS. Furthermore, it has been found that the adoption of a new practice within a community has more success through a propagation paradigm, where the change agents are …

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 …

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 …

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 …

Lifelong Machine Learning With Adaptive Resonance Theory, Sasha Petrenko

Doctoral Dissertations

"This publication option dissertation is composed of three papers concerning the study of the problem lifelong machine learning with Adaptive Resonance Theory (ART) algorithms. Lifelong learning (L2) is a challenging machine learning paradigm that both encompasses and formalizes the fields of continual learning and incremental learning. The field is concerned with the mitigation of the phenomenon of catastrophic forgetting whereby learning agents that are faced with incrementally novel information deleteriously overwrite previous knowledge if that learning process is not regularized to counteract this consequence. ART algorithms solve this stability-plasticity dilemma by optimally assigning learning to categories or instantiating new knowledge …