Engineering Commons^™

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. …

Contextual Augmentation In Artificial Intelligence, Emmanuel Joshua Balogun

College of Graduate Studies: Theses & Dissertations

Contextual understanding is a significant challenge of Large Language Models (LLMs), which are typically trained on general-purpose datasets. Due to this, LLMs fail to capture nuanced or domain-specific information and may struggle to interpret user queries accurately. Consequently, prompt engineering can become complex in automating, and LLMs are prone to “hallucinating”—generating random or irrelevant texts—when they lack sufficient context. This undermines their ability to provide focused, accurate responses. Accordingly, this thesis seeks to enhance the contextual understanding capabilities of Artificial Intelligence systems to facilitate more precise and relevant answer generation. Study A looks into a new approach to combating misinformation …

Enhancing Ai-Driven Automation For Object Detection And Computer Vision, Nafeeul Alam Walee

College of Graduate Studies: Theses & Dissertations

In recent years, AI-driven automation has revolutionized the field of object detection and computer vision, enabling sophisticated and efficient solutions across various industries. This research explores the latest advances and techniques in improving AI-driven automation for object detection and computer vision applications. We examine state-of-the-art deep learning models and frameworks that have contributed to significant improvements in accuracy and speed and highlight the generative results. The focus is on exploring the real-time processing capabilities that have expanded the applicability of these technologies in real-world scenarios. Furthermore, we investigate image integration and video data to improve precision detection and contextual understanding. …

Bio-Inspired Airfoil Design Based On The Aerodynamic Analysis Of A Bird Feather Microstructure, Jack C. Ihm

College of Graduate Studies: Theses & Dissertations

This study investigates the aerodynamic effects of a bio-inspired airfoil design based on the microstructure of a secondary feather from a female wood duck. The research hypothesized that incorporating barbs and barbules into an airfoil design would modify boundary layer behavior by introducing localized flow disturbances. To test this, a bio-inspired airfoil was developed by integrating the microstructure into a NACA 0012 airfoil and analyzed using computational fluid dynamics (CFD) simulations at angles of attack of 0°, 5°, 10°, and 15°. The results showed that the bio-inspired airfoil influenced boundary layer behavior, producing localized flow disturbances near x/c = 0.7 …

Ease Of Product Disassembly Through A Systematic Structured Time-Based Design For Disassembly Methodology, Emeka S. Igwe

College of Graduate Studies: Theses & Dissertations

This research introduces a systematic time-based design for disassembly (DfD) framework aimed at optimizing product disassembly by addressing important features like liaisons between components in product, component accessibility and the overall modularity of the product. This study specifically covers electromechanical and mechatronic systems in both household and industrial setup, identifying their disassembly challenges and high value pointers for improvement. The methodology involves using a design for disassembly framework called LeanDfD in carrying out a holistic disassembly process and evaluating quantitative metrics like disassembly time and complexity and suggesting further redesign strategies to minimize disassembly time and cost. Adopting this systematic …

Insider Threat Agent: A Behavioral Based Zero Trust Access Control Using Machine Learning Agent, Michael Fojude

College of Graduate Studies: Theses & Dissertations

Hybrid work, cloud adoption, and freely available AI‑enabled attack tools have exposed critical weaknesses in perimeter‑centric security. Current breach reports attribute more than one‑third of incidents to insider misuse or credential compromise, yet many organizations still depend on static Role‑ or Attribute‑Based Access Control that neither verifies intent continuously nor adapts to subtle behavioral change. This research addresses that gap by designing and validating a behavioral based Zero Trust Access Control (ZTAC) Agent. A five‑year enterprise log Dataset was extracted and cleansed to establish a high‑fidelity baseline of normal user behavior. Feature engineering captured temporal regularity (login sequence, session duration), …

Temporal Analysis Of Construction Safety Incidents In Southeastern U.S. Using Machine Learning Techniques, Mayowa O. Oladele

College of Graduate Studies: Theses & Dissertations

Construction safety incidents remain a significant concern, particularly in the Southeastern U.S. due to the high-risk nature of the industry. Analyzing patterns in these incidents can help improve safety practices and reduce accidents. Machine learning (ML) techniques were employed in this study to identify temporal patterns in construction safety incidents, aiming to enhance proactive safety management. The machine learning methods used in this research included logistic regression, decision trees, random forest, support vector machine (SVM), and K nearest neighbors (KNN).

The objective of the study was to analyze temporal trends in safety incidents and identify the most effective machine learningtechnique …

Comparative Analysis Of Lidar And Close-Range Photogrammetry Techniques For Inspection Of Mse Walls In Two Georgia Bridges, Md. Mehrab Hossain

College of Graduate Studies: Theses & Dissertations

Mechanically Stabilized Earth (MSE) retaining walls are durable, settlement tolerant, easy to install, and present cost-effectiveness, in highway bridges. Nevertheless, the cost of repairing MSE walls is high, and it is crucial to have an accurate, quantitative, and scalable inspection method for early detection of potential problems. This study aims to analyze and evaluate undesired displacements that may affect these walls over time. For this, two remote-sensing technologies are considered: Light Detection and Ranging (LiDAR) and 3D Close Range Photogrammetry (CRP). Their performances are compared against an accurate Robotic Total Station (RTS) device, serving as the benchmarking instrument. This work …

Quantifying Inositol Phosphate Dephosphorylation To Understand The Role Of Recalcitrant Organic Phosphorus Forms On Harmful Algal Blooms In Freshwater Systems, Iffat Tasnim

College of Graduate Studies: Theses & Dissertations

Organophosphorus such as phytic acid, a surrogate species of inositol phosphate (IP), may serve as a source for orthophosphate (OP) in freshwater. In absence of OP, competent aquatic microorganisms upregulate the production of specialized enzymes to obtain growth-sustaining OP from organic phosphorus (org-P) forms. The contribution of recalcitrant org-P to the OP pool has been overlooked due to the lack of capable tools to measure OP production from org-P accurately. The objective of this study was to quantify OP production from phytic acid (a surrogate form of recalcitrant org-P) to assess the contribution of recalcitrant org-P forms to the total …

Synthesis And Processing Of Co-Axial/Tri-Axial Multi-Layered Nano-Particles, Jannatul Ferdaus

College of Graduate Studies: Theses & Dissertations

Electro-spraying has been used as an effective processing method of nanoparticle fabrication for the application of targeted drug delivery. The study demonstrates the feasibility of a non-conventional triaxial electro-spraying setup for multi-layered nano-drug fabrication and proposes optimized parameters. Two different drugs, XAV939 and Dextran 40000, were used to study the process parameters (voltage and solution concentration) of coaxial electro spraying. The particle size of Dextran-PCL was an average of 166.3 nm for PCL-Dextran at 32.5 kV and 18-hour sonication. The SEM analysis and UV-spectrum showed the encapsulation of Dextran with PCL, though the in vitro study in mice after 24 …

Multiphysics Modeling Of Solid Oxide Fuel Cells For Gradient Minimization And Inductive Loop Analysis In Impedance Spectroscopy Using Machine Learning-Based Microstructural Property Estimation, Muhammad Usman Khan

College of Graduate Studies: Theses & Dissertations

Solid oxide fuel cells have significant advantages in renewable energy utilization due to their high efficiency, fuel flexibility, and low emissions. However, despite the numerous efforts of technology, thermal and current density gradients and impedance behavior fluctuations are still causing performance degradation. A combined computational framework that integrates machine learning and three-dimensional Multiphysics modeling is needed to investigate and optimize the performance of solid oxide fuel cells. A machine learning model, trained on synthetic microstructure data by percolation analysis, is used to predict important microstructural parameters like triple phase boundary density and geometric tortuosity. These are then employed in a …

Experimental Study Of Deformation Behavior For A Novel Elastohydrodynamic Seal For Supercritical Carbon Dioxide Power Cycles, William A. Adams

College of Graduate Studies: Theses & Dissertations

Supercritical carbon dioxide (sCO₂) Brayton cycles are a strong contender for future power generation systems due to their high thermal efficiency and compact nature. Sealing is one of the key challenges presented by such systems that has a direct impact on the system's overall efficiency. This research is the first experimental study to investigate the deformation behavior of an elastohydrodynamic (EHD) seal made from bearing-grade polyether ether ketone (PEEK). A testing apparatus was developed to integrate four strain gauges positioned along the seal to quantify the deformation occurring up to pressures of 13 MPa. Mass flow rate measurements …

One-Dimensional Numerical Analysis Of A Novel Elastohydrodynamic Seal For Supercritical Co2 Power Cycles With Experimental Validation And Future Approach, Cole B. Hayne

College of Graduate Studies: Theses & Dissertations

This thesis presents a numerical analysis and experimental verification approach for a novel elastohydrodynamic (EHD) seal designed with the specific application of supercritical carbon dioxide (sCO₂) power cycles. Brayton power cycles with sCO₂ as the working fluid have gained significant traction as potential large-scale power generation methods. This increase in interest and research is primarily due to their many beneficial characteristics, such as high thermal efficiency, compact geographic footprint, reduced capital costs, and lower water and fuel usage than comparable power cycles. Despite these many positive qualities, proper sealing technology remains one of the primary barriers to …

Viscoelastic Property Analysis Of A Magnetorheological Elastomer Micropump For Insulin Delivery In Type 1 Diabetes, Victor Buitimea

College of Graduate Studies: Theses & Dissertations

Over two decades, there has been a significant rise in awareness regarding Type 1 Diabetes (T1D), leading to a deeper comprehension of numerous variables, including hereditary factors, patterns of occurrence, and health challenges. According to the Type 1 Diabetic Index, around 8.7 million people worldwide are affected by this chronic autoimmune illness marked by a lack of insulin and hyperglycemia. The introduction of artificial pancreas systems could save more than half a million patients by 2040. Despite the availability of various insulin delivery technologies that are offered to diabetic patients, many still are skeptical of this modern system. The issues …

An Investigative Study Of Thermal Fluid Properties When Introducing Metallic Nanoparticles Through A Heat Exchanging System, Levi P. Mckinney

College of Graduate Studies: Theses & Dissertations

Heat-exchanging systems are essential in applications ranging from automobiles to air-conditioning units, and ongoing improvements aim to enhance efficiency while reducing system size. Conventional coolant upgrades often rely on ethylene glycol, which increases thermal stability and lowers freezing point but reduces water’s inherent heat-transfer capability. Advances in nanotechnology provide an alternative approach: suspending nanoparticles in base fluids can significantly modify thermal properties, with some formulations exhibiting conductivity increases of up to 60%. This thesis examines the thermal and tribological performance of three working fluids—distilled water, a 50:50 water–ethylene glycol mixture, and the same mixture enhanced with Al₂O₃ nanoparticles. Distilled water …

Effect Of Alloying Additions On Austenite Refinement In Nickel-Alloyed Ductile Cast Irons, Adnan Adib Aahamed

College of Graduate Studies: Theses & Dissertations

The benefits associated with the application of ductile irons are significantly attributed to the control of microstructures, with refinement of austenitic matrix during solidification playing a significant role. Nickel alloyed ductile irons are attractive due to their potential for high ductility and suitability for potential high-temperature applications with stable austenitic microstructure. Refinement of austenite grain structure is thus important to enhance the mechanical properties of the alloyed ductile iron. This research investigates the impact of in-mold additions of different alloying elements on the austenite morphology and grain refinement of nickel-alloyed ductile iron along with the associated mechanical properties. A hypoeutectic …

Synthesis And Assessment Of Biobased Acrylated Epoxidized Soybean Oil Resins For Stereolithography 3d Printing Of Microfluidic Devices, Natalie S. Romero Figueroa

College of Graduate Studies: Theses & Dissertations

This research focuses on the development and characterization of a biobased photocurable resin synthesized from soybean oil for use in stereolithography (SLA) 3D printing of microfluidic devices. The study explores a sustainable alternative to petroleum-based resins by performing an acrylation reaction on epoxidized soybean oil (ESO) to produce acrylated epoxidized soybean oil (AESO), which was then formulated into a photocurable resin with the addition of a photo initiator. The fabrication process involved designing microfluidic molds in SolidWorks and printing them using an Elegoo Mars 4 SLA printer under various exposure and layer thickness parameters. The printed samples consisted of microchannels …

Accelerated Test Method (Atm) For The Evaluation Of External Sulfate And Chloride Attack On Concrete Using Artificial Climate Environment (Ace): An Assessment Of Methodology, Eli Walker

College of Graduate Studies: Theses & Dissertations

This study seeks to investigate a testing methodology that utilizes accelerated testing methods (ATM) in conjunction with nondestructive testing methods (NDT) to assess destructive ion attacks on concrete. Through the testing of concrete samples, the impacts of chloride and sulfate ions on concrete will be tested by subjecting concrete to cyclic testing in an artificial climate environment. Electrical resistivity (ER) and ultrasonic pulse velocity (UPV) testing will evaluate the impact of the accelerated testing on the migration of destructive ions within the pore structure of the tested concrete. Based on this investigation, comparisons between accelerated, non-accelerated, and control samples will …

Enhancing The Mechanical Properties Of Sla 3d-Printed Bio-Resin From Linseed Oil Using Cellulose And Lignin Biopolymers, Chukwunonso A. Ikedionu

College of Graduate Studies: Theses & Dissertations

Abstract

This research explores the development of bio resin from linseed oil by the process of epoxidation and acrylation to produce acrylated epoxidized linseed oil (AELO). Lignin and cellulose biopolymers were added as reinforcement at varying weight fractions of 1 wt.%, 2.5 wt.%, and 5 wt.%, and their mechanical performance was compared against pure AELO. The formulations were printed using an Elegoo SLA 3D printer to create standardized test specimens like tensile bars, compression cylinders, and hardness blocks, which were all prepared according to the ASTM testing standard.

The results indicate that reinforcement effects depend on both filler type and …

Hybrid Rans-Les Analysis Of Turbulent Flame Under Near Blow-Off Condition In A Multi-Stage Swirl Combustor, Brandon O'Brien

College of Graduate Studies: Theses & Dissertations

Advances in computational resources are making computational fluid dynamics (CFD) increasingly accessible for a variety of engineering applications. However, certain complex problems, such as simulating detailed flame kinetics, remain computationally prohibitive for many users. Developing cost-effective methods to simulate these challenges would greatly benefit applications involving flame dynamics, such as turbine engines or industrial burners. This study investigates the effect of main stage swirler intensity on near lean blow-off characteristics in a multi-staged swirl combustor using Ansys Fluent. The hybrid RANS-LES turbulence model, Stress Blended Eddy Simulation (SBES) coupled with Flamelet Generated Manifold (FGM) combustion model was selected to model …

Evaluation Of The Dnazyme Gr5 For The Determination Of Lead Speciation In Natural Waters, Gaganprit Gill

Theses and Dissertations (Comprehensive)

This thesis explores the development and application of a DNAzyme-based biosensor designed to detect labile metal species in environmental samples. Real time and on-site monitoring of labile metal fractions would make a valuable contribution to environmental management, as these fractions are the most bioavailable and pose significant toxicity risks to aquatic organisms. Conventional methods for detecting labile metals, while effective, are often burdened by high costs, complexity, and lengthy processing times, making them less ideal for rapid and widespread environmental assessments.

The first manuscript of this thesis (chapter 2) establishes the fundamental capabilities of the Pb²⁺-specific DNAzyme GR5 …

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 …

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 …

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 …

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 …

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, …

Processing And Densification Of Multi-Phase High-Entropy Ceramics, Steven Smith

Doctoral Dissertations

"This work focuses on the processing and densification of multiphase, high-entropy ceramics to promote their use in friction stir welding technologies. Several high-entropy systems including high-entropy borides, carbides, and their composites were produced. Boro/carbothermal and carbothermal synthesis were used to produce high-entropy powders from oxide powder mixtures. Composites of high-entropy borides and high-entropy carbides were produced using a sequential approach to produce both phases. The carbide was first produced using carbothermal reduction, then ZrH2 and B4C were added to the carbide powder to produce the high-entropy boride phase. The resulting powder was densified by spark plasma sintering and pressureless sintering, …

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, …

A Hybrid Data Processing, Computational Intelligence, And Complex Systems Modeling Approach For Describing And Predicting The Bitcoin Market, Oluwadamilare Akinpelu Omole

Doctoral Dissertations

"The Bitcoin market, like traditional financial markets, is a complex system with intricate interdependencies and nonlinear interactions among various market elements. This, coupled with the inherent uncertainty and high volatility present, makes predicting Bitcoin price movements difficult. The lack of understanding of the underlying market dynamics often results in significant losses for investors and traders. Existing studies have focused on the use of predictive models, which have not sufficiently captured the complexities of the market and cannot forecast extreme market events. This research endeavors to bridge this gap by combining data processing techniques, computational intelligence, and complex systems theory to …

Atmospheric Transport Of Radionuclides, Meteorological Data Mining & Synthesis For Site Data Supplementation, Ben Yao Sonpon

Doctoral Dissertations

"This research aligns with the NRC's vision of implementing risk-informed decision-making to support its regulatory charter. The suite of tools developed includes automated procedures for data mining and extracting meteorological (met) data from various national and regional repositories. A second data analytics tool automates the process of data fusion into a uniform format while preserving data fidelity. Autocorrelations were then established, and correlation coefficients were calculated between the Callaway Nuclear Power Plant (Callaway) and nearby off-site weather stations. The complexity of these correlations depends on factors such as physical proximity, geographic features, and topology, potentially necessitating multivariate analysis (MVA). Furthermore, …