Engineering Commons^™

Selective Extraction Of Nickel And Cobalt From Limonitic Laterite Via Optimized Sulfation Roasting–Water Leaching And Solvent Extraction, Maryam Osali, Farid Ahani, Mohammad Reza Aboutalebi, Mandana Adeli, Javad Moghaddam, Saeid Karimi, Janaka Jayamini Wijenayake, Lana Alagha

Mining Engineering Faculty Research & Creative Works

Limonitic laterites typically contain low Ni and Co contents and significant impurities, making the development of technical and economically feasible processes challenging. To address this challenge, this study investigates and evaluates an integrated hydrometallurgical process comprising sulfation roasting, water leaching, and solvent extraction (SX) for the selective recovery of Ni and Co from limonite-type laterite. Response Surface Methodology coupled with a Central Composite Design (RSM-CCD) was employed as a statistical experimental design tool to efficiently optimize the sulfation roasting conditions. Under the optimal sulfation roasting conditions (temperature 703 °C), selective leaching efficiencies of 87.2% for Ni and 96.6% for Co …

Effect Of Environmental Conditions On Fracture Of Composite Materials And Thin Films, Victor Birman

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Environmental conditions, i.e., temperature and moisture, affect mechanical properties of materials, including composites. In this paper, we concentrate on one of the aspects of the effect of environment on fracture in a composite lamina. The paper demonstrates an analytical approach to account for the effect of the changes in environment on the strain energy release rate of composite materials and thin films. These analytically determined strain energy release rates should be compared to fracture toughness to predict the susceptibility of the material to fracture. Numerical examples are presented for several polymeric and metal matrix composites using available experimental data for …

A Federated Learning Framework For Data-Sovereign Predictive Maintenance In Distributed Smart Manufacturing, Md Sazol Ahmmed, Sriram Praneeth Isanaka, Frank Liou

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Featured Application: The proposed federated learning framework can be applied in distributed smart manufacturing environments where multiple factories or production facilities collaboratively develop predictive maintenance models without sharing sensitive operational data. This approach is particularly useful for industrial networks involving geographically distributed plants, contract manufacturing partners, and multi-site production systems where data sovereignty and avoidance of raw data sharing are critical. Predictive maintenance enables early detection of machine failures and reduces unexpected production downtime. However, conventional approaches typically rely on centralized data collection and model training which introduce challenges related to data sovereignty, communication overhead and data ownership. To address …

Machine Vision For In Situ Measurement And Control Of Wire Stickout In Lwded Process, Braden Mclain, Remy Mathenia, Todd Sparks, Frank Liou

Mechanical and Aerospace Engineering Faculty Research & Creative Works

This work presents a machine-vision–based measurement and control framework for laser wire directed energy deposition (LWDED) processes. A visible-light camera system is used to capture meltpool images, from which a novel vision algorithm extracts the wire–meltpool interface location. By utilizing a camera that is rigidly mounted to the deposition head, the vision algorithm provides a relative measurement of the distance between the nozzle tip and the workpiece, also referred to as wire stickout. A proportional-derivative (PD) control strategy is implemented using the measured stickout as feedback to adjust deposition feedrate. Results show that the control system successfully compensates for improper …

Calibration Refinement Of Aashto Paveme For Kentucky Asphalt Overlays, Clayton S. Cook, Kean H. Ashurst Jr., Clark Graves

Kentucky Transportation Center Research Report

The Kentucky Transportation Cabinet (KYTC) uses AASHTOWare’s Pavement ME Design Version 3.0 (PaveME) to develop mechanistic-empirical designs for new and reconstructed pavements. Transfer functions used for estimating pavement distress in PaveME rely on national calibration values derived from the Long-Term Pavement Performance (LTPP) database. However, these often fail to reflect Kentucky’s local conditions, materials, and practices. To address this issue, Kentucky Transportation Center (KTC) researchers completed local calibrations for several key transfer functions (rutting, reflective fatigue cracking, and roughness (IRI)) to improve the predictive accuracy of and reduce bias in pavement performance models developed for rehabilitation projects that involve placing …

Effects Of A Passive Assistive Hamstring Device On Overground Running Kinematics And Hamstring Activation., Quinn Castner

All Theses

Hamstring strain injuries are among the most common and recurring injuries in sports, occurring most often during the terminal swing phase of gait. Despite progress in rehabilitation, the incidence of injury has only increased, suggesting a need for a novel intervention. We designed a passive, assistive, wearable device with two specific criteria in mind: to offload the hamstrings during running, and do so without hindering normal kinematic patterns. The device consists of an adjustable elastic band anchored proximally at the waist and distally just above the ankle joint center. It stretches and shortens with the hamstrings, providing passive hip extension …

Robustness Of Vision Language Models For Pedestrian Detection Tasks, Ostonya K. Thomas

All Theses

Autonomous vehicle (AV) systems typically employ modular systems in which discrete components handle separate tasks such as perception, computation, and path planning. While flexible, this approach allows errors to propagate and compound across the pipeline, and many AI systems offer little transparency into their internal decision-making. Such limitations are particularly concerning in safety-critical domains where failures can carry lethal consequences. Vision Language Models (VLMs) have emerged as a promising alternative because they support end-to-end implementations that bypass compounding error risks and provide natural language explanations of their outputs. Despite these advantages, prior research has demonstrated that both computer vision systems …

Utility-Scale Battery Energy Storage Systems - Field Pilot Unit Experience, Analysis, And Review Of Technological Advancements, Kwabena A. Kyeremeh, Shaun E. Lavin, Grant M. Fischer, Dan M. Ionel, Aron Patrick

Electrical and Computer Engineering Graduate Research

Utility-scale Battery Energy Storage Systems (BESS) are becoming increasingly important in modern power systems, providing services ranging from backup support to load balancing and peak shaving. The long-term operational performance and reliability of these systems with expanding deployment remain insufficiently documented. This paper provides an operational assessment of a 1MW/2MWh utility-scale BESS alongside a systematic review of technology developments across major subsystems. Operational metrics including round-trip efficiency (RTE), outage characteristics, and degradation patterns are examined to identify performance trends and the underlying causes of outages. In addition, testing and operational principles aligned with utility practice and standards are presented to …

Improving Fairness On Semantic Segmentation Using Large Language Models, Samuel E. Burggraf

Electrical & Computer Engineering Projects for D. Eng. Degree

As machine learning systems are increasingly integrated into critical decision-making processes, ensuring fairness in their design and implementation has become a significant concern. While fairness research has primarily focused on specific protected attributes, less attention has been given to spatial fairness, which can affect individuals at specific locations. If fairness is not addressed, models may systematically underperform in certain regions or across populations which can lead to unequal access to accurate predictions and potentially biased decision-making. Fairness considerations should extend across all machine learning applications to align with the National Institute of Standards and Technology (NIST) guidelines of fair and …

Enhanced Situational Awareness Of Solar Pv Plants For Near Real-Time Planning And Operation In Modern Power Systems, Michael A. Walters

All Theses

Solar photovoltaic (PV) plant development and utilization is increasing worldwide but remains intrinsically challenged by its large dependence on highly variable weather conditions and operating states. This paper presents a framework to leverage three new situational awareness indices (SAIs), namely: weather condition index (WCI) to gauge operational performance based on environmental states, operational complexity index (OCI) to indicate the severity of power generation reductions, and photovoltaic generation index (PVGI) to provide a final determination of the impact on power generation and to bolster situational awareness in planning and operational contexts for solar PV plants. This is accomplished by exploiting the …

Boron Nitride Nanotubes Assist The Self-Assembly Of Spherical Cholesteric Liquid Crystal Shells Of Cellulose Nanocrystals In Water, Tanner L. Larson, Brandon J. Heppe, Benjamin S. Flavel, Ralph Krupke, Geyou Ao

Chemical & Biomedical Engineering Faculty Publications

Spherical confinement of cholesteric liquid crystal (ChLC) droplets is emerging as an intriguing approach for achieving complex ordered structures for photonic applications and beyond. Previously, this has been achieved primarily through microfluidic assembly utilizing immiscible solvents or immiscible mesogen-solvent systems, such as oil-water or thermotropic liquid crystal-water systems, respectively. Here, we show the spontaneous assembly of spherical ChLC droplets with isotropic cores from lyotropic liquid crystals of mixed nanorods containing boron nitride nanotubes (BNNTs) and cellulose nanocrystals (CNCs) in all-aqueous environments. We show that the mixing of as low as 0.094 vol % of pectin-coated BNNTs with isotropic dispersions of …

Harness: Hybrid Architecture For Resilience In Networked Engineering System Simulations, Daniel Scott

Graduate Theses and Dissertations

This dissertation presents the development of HARNESS, a unified, domain-agnostic framework for the modeling, optimization, and evaluation of complex systems under conditions of degradation and uncertainty. The research addresses a persistent challenge in systems engineering: the lack of a generalizable, behaviorally grounded approach for quantifying resilience and robustness across diverse domains. HARNESS integrates graph-theoretic dependency modeling, GPU-accelerated evolutionary optimization, and agent-based simulation into a modular architecture that enables both system design and diagnostic analysis. The framework models system interdependencies through user-defined components, parameters, and constraints, allowing architectures to evolve dynamically while maintaining structural validity. A mutation-only genetic algorithm with a …

An Energy- And Area- Efficient Two-Stage Latch Comparator Using Common-Mode Reset, Larry Yu

Electrical Engineering Theses and Dissertations

This thesis presents an energy-and-area-efficient two-stage comparator implemented in TSMC 65 nm CMOS that incorporates a Floating Inverter Amplifier (FIA) followed by a latch using a common-mode reset scheme. The FIA improves input sensitivity and reduces kickback noise by isolating the input nodes from large latch voltage swings. The proposed latch resets its output nodes to a common-mode voltage rather than one of its supply rails, thereby reducing switching energy during the reset phase. The comparator can resolve differential input voltages as small as 2 mV with a clock period of 500 ps, achieving 74.33 μV input-referred noise while consuming …

Optimization Of The Baffle Geometry Of A Circular Culvert Outlet Structure To Maximize Energy Dissipation, Kiarash Shirmahi

Department of Civil and Environmental Engineering: Dissertations, Theses, and Student Research

High-velocity flow at culvert outlets can lead to significant soil erosion and damage to downstream infrastructure, particularly in agricultural regions where land protection is critical. Circular culverts, commonly used in transportation systems, are especially susceptible to this issue due to flow acceleration caused by geometric constraints and installation angles. Despite extensive research on energy dissipation in rectangular culverts, limited attention has been given to circular configurations. This study addresses this gap by evaluating the hydraulic performance of baffle systems designed to reduce outlet energy in circular culverts.

A series of laboratory experiments was conducted using a scaled physical model of …

Modeling Structural Support To Facilitate Novel Treatments Of Degenerative Disc Disease, Jose Luis Calderon

Poster Presentations

Over 600 million people worldwide suffered from low back pain in 2020, with projections for 2050 being over 800 million [1]. Annual costs associated with low back pain total over 450 billion dollars in the US alone [2]. This research serves as a proof-of-concept for the use of structural supports to facilitate intervertebral disc healing. This treatment would involve the implementation of these supports along with existing injection treatments to promote regeneration. In both models, along with the combined model, the ability for these supports to alleviate intervertebral disc height loss is shown. This indicates that these supports would serve …

Polymer Charge Effects On Scaling In Membrane Distillation, Lucia Milans Del Bosch

Chemical Engineering Undergraduate Honors Theses

This research evaluates the effectiveness of polymeric inhibitors at suppressing scaling during direct contact membrane distillation (DCMD). Anionic polyacrylic acid (PAA), neutral polyethylene glycol (PEG), and cationic polyethyleneimine (PEI), were investigated. Experiments were conducted using both hypersaline single-salt and multi-component mixed-salt feeds to determine how the presence of different ions influences performance. Results from single-salt experiments showed that PAA and PEG effectively maintained permeate flux through chelation and steric hindrance, respectively, while PEI caused rapid membrane failure due to interfacial aggregation and pore wetting. In complex mixed-salt solutions, PEG was the additive, maintaining a steady flux with only a 7.33% …

The Influence Of Social Media On The Product Life Cycle In Fast Fashion: A Shein Case Study On Environmental And Social Impacts, Clara R. Devine

Industrial Engineering Undergraduate Honors Theses

Fast fashion has transformed global consumer culture through its rapid product cycles, affordability, and accessibility. However, this model has also contributed significantly to environmental degradation, excessive textile waste, and unethical labor practices. Social media platforms have accelerated these patterns by amplifying short-lived trends and influencing consumer purchasing behavior. This study aims to analyze the relationship between social media activity and the fast-fashion life cycle, with a focus on how online engagement drives consumption, production speed, and environmental impact. The research utilized a quantitative and analytical approach, combining correlation analysis and time-series data to evaluate the connection between SHEIN’s growing user …

A Full System Co-Simulation Platform For Evaluating Edge Machine Learning Inference Using Compute-In-Memory, Belsen Lee

Electrical Engineering and Computer Science (MS) Theses

We present a full-system co-simulation platform for evaluating embedded machine learning (ML) inference using compute-in-memory (CIM). CIM architectures aim to reduce data movement overhead by performing matrix operations in memory, but end-to-end benefits depend on system-level integration costs that are difficult to assess with isolated hardware models alone. To address this gap, we develop an integrated RISC-V QEMU-SystemC co-simulation environment that allows standard embedded Linux to interact with a transaction-level CIM accelerator model via memory-mapped I/O, direct memory access (DMA), and interrupts. To evaluate performance, we benchmark an MNIST image inference workload and a synthetic fully connected neural network, comparing …

Transformation Efficiency And Gfp Expression In E. Coli, Jessica H. Hobbs

Honors Theses

Genetic transformation of bacteria is a foundational technique in molecular biology and biotechnology, enabling the introduction and expression of foreign genes for research, industrial, and educational applications. This thesis investigates the transformation efficiency and green fluorescent protein (GFP) expression in Escherichia coli using the pGLO plasmid system, with the primary objective of supporting the development of a graduate-level laboratory course focused on bioprocess engineering and molecular biotechnology. The pGLO plasmid contains a GFP reporter gene regulated by an arabinose-inducible promoter and an ampicillin resistance gene that allows for selective growth of transformed cells. Competent E. coli HB101 K-12 cells were …

Salt-Dependent Purification Of Green Fluorescent Protein Via Hydrophobic Interaction Chromatography, Katie L. Collins

Honors Theses

Green fluorescent protein, GFP, is a widely used fluorescent reporter, and its purification provides a clear model for studying downstream bioprocessing. This thesis investigates how binding-buffer salt strength affects GFP retention and elution during hydrophobic interaction chromatography, HIC, by comparing three conditions (1.0×, 0.8×, and 0.6×). GFP-expressing E. coli were lysed and clarified, and the lysate was purified on HIC columns; collected fractions were evaluated qualitatively under UV illumination to track fluorescence distribution. Results showed a salt-dependent trend in which higher salt improved retention and shifted fluorescence toward later elution fractions, while reduced salt weakened hydrophobic interactions and increased earlier …

Capacity Reduction Factors For Steel Beam Ends With Holes, Kevin Saleh Makubuli

Masters Theses

The presence of holes at steel beam ends can decrease the nominal resistance (capacity) of beam ends. Codes such as AASHTO LRFD and AISC include equations for evaluating the nominal resistance of steel beam ends. While these equations are appropriate for as-designed beam ends, they may not apply to deteriorated beam ends, such as those with holes. Thus, this study aims to develop procedures to calculate the capacity of steel beam ends with holes. First, the FEA of an as-designed beam is performed for capacity evaluation (numerical result). The latter is compared with the analytical result (as-designed beam capacity) to …

Transformer Vulnerability To Geomagnetically Induced Currents Using Layered Soil Conductivity Models, Junior A. Sterling

Masters Theses

Geomagnetically induced currents (GICs) pose a significant threat to modern power transformers connected to long high-voltage transmission systems, particularly in regions with low subsurface electrical conductivity. During geomagnetic disturbances (GMDs), time-varying magnetic fields induce surface electric fields that drive quasi-DC currents through grounded transformer neutrals. These currents can bias transformer cores, leading to saturation, waveform distortion, and potential system instability. Despite extensive research, the role of regional Earth conductivity in shaping electric fields and transformer response remains an area requiring deeper investigation.

This study analyzes how contrasting Earth conductivity profiles influence GIC magnitude and transformer saturation risk using two representative …

Transient Mitigation In Dual Active Bridge Converter Using An Auxiliary Converter With High-Frequency Selective Control For Load Step-Down Condition, Sachith Dilshan Wijesooriya

Masters Theses

Dual Active Bridge (DAB) converters are widely utilized in applications such as electric vehicles, renewable energy systems, and solid-state transformers due to their high efficiency, galvanic isolation, and bidirectional power transfer capability. However, during rapid load transitions, DAB converters frequently exhibit significant output voltage overshoot and prolonged settling times, which increase device stress and adversely affect system reliability. This thesis proposes an auxiliary-circuit-based transient mitigation method to address these limitations. The auxiliary circuit, implemented as a bidirectional Buck–Boost stage, operates in Boost mode during load step-down events to absorb excess energy and suppress the resulting voltage overshoot. The design of …

Design Of An Extensible And Scalable Data Acquisition System For Pulse Shape Discrimination, Prince John

McKelvey School of Engineering Graduate Student Theses & Dissertations

This thesis presents the design and development of a highly scalable, end-to-end data acquisition (DAQ) system for nuclear physics experiments that can be deployed in configurations ranging from a few to thousands of detector channels. The system is built as an extensible platform composed of modular 16-channel chipboards that support a wide range of scintillator and detector types and perform real-time, on-board data sparsification and pulse-shape processing. Three versions of the chipboard have been fabricated to date.

The DAQ architecture is based on a family of analog pulse-shape-processing application- specific integrated circuits (ASICs) developed by the IC Design Laboratory at …

Temporal Logic Planning In Semantic Maps Of Unknown Environments Using Tl-Rrt, Dongrui Yang

McKelvey School of Engineering Graduate Student Theses & Dissertations

Autonomous mobile robots are increasingly expected to perform complex missions in unstructured environments. Traditional path planning approaches handle simple point-to-point navigation, but struggle with complex tasks that involve temporal and logical orderings of objectives. Linear Temporal Logic (LTL) provides a method for complex missions (e.g., sequential visits to multiple targets or surveillance tasks) in a strict way. This thesis presents an integrated planning framework that enables a robot to satisfy LTL-based task specifications in an unknown environment by combining a Temporal Logic RRT* (TL-RRT*) planner with semantic mapping. The robot builds a semantic map of its environment online using simultaneous …

Estimation Of The Mechanical Properties Of South Carolina Timber Piles Using Non-Destructive Evaluation Methods And Experimentally-Informed Models, Aashish Sapkota

All Theses

South Carolina has about 2,600 bridges that are supported by nearly 75,000 timber piles. They are increasingly vulnerable to biological decay, cracking and impact damages after decades of service. Current inspection methods used by the South Carolina Department of Transportation (SCDOT), such as hammer sounding and awl probing, are labor-intensive and expensive. This study investigated non-destructive evaluation (NDE) methods, including micro-resistance drilling and stress wave timing, as alternatives for assessing timber pile condition.

Ten timber piles were collected from two South Carolina bridges, and their above-grade portions were cut into 40 specimens approximately 13 to 15 inches long. Specimens were …

Neural-Network-Based Modeling Of Grid-Forming Inverters, Jacob D. Levesque

All Theses

Renewable energy production has grown significantly in recent years and continues to expand, resulting in an increasing number of inverter-based resources (IBRs) in the grid. As the number of IBRs in the grid continues to grow, grid-forming (GFM) inverters are becoming increasingly popular due to their ability to regulate voltage and frequency, providing increased grid stability and enabling islanding. As GFM inverters become more widely used in power systems, accurate and efficient models of their behavior are needed for system design purposes.

Emerging advances in neural networks have led to research on computationally efficient neural-network-based (NN-based) modeling approaches for inverters. …

Development Of Low-Cost Triaxial Force Sensor For Measurement Of Human-Exoskeleton Interaction Forces, Hamdan Khan Sarvathullah

All Theses

Contemporary research suggests that shear force is a major contributor to discomfort and pressure injury. However, the variation of shear forces during human-exoskeleton interaction dynamics is a highly unexplored field. The high cost of commercial triaxial force sensors may be a major factor in the notable lack of research in this field. Therefore, in this paper, we present a low-cost, 3D-printed triaxial force sensor designed specifically to measure the triaxial interaction forces between an exoskeleton and its user. The triaxial force sensor uses Carbon-Black/Silicone Rubber (CB/SR) strings to measure shear forces, whereas the normal force is measured with a Force …

Exploration Of Real-Time Power Electronic Simulation On Amd Npu, Shouyu Du

All Theses

The rapid electrification of the automotive and data center sectors has created a critical demand for high-fidelity, real-time simulation of complex power electronic systems. While Hardware- in-the-Loop (HIL) simulation on Field-Programmable Gate Arrays (FPGAs) is the current industry standard, it presents significant challenges regarding development complexity and memory limita- tions. This dissertation investigates the feasibility of utilizing Neural Processing Units (NPUs)— specifically the AMD AI Engine (AIE) XDNA2 architecture—as a novel platform for real-time, deterministic circuit simulation. This study establishes a comprehensive automated modeling framework based on graph theory and Massarini’s method to derive linear state-space representations for arbitrary circuit …

Developing Aero-Floating Treatment Wetland (Aeroftw) Scaffolds: A Non-Plastic Alternative To Conventional Plastic-Based Ftws, Ada C. Montoya Gomez

All Theses

This research was conducted to explore the possibility of constructing floating treatment wetlands (FTWs) without using plastic materials. FTWs are floating platforms that hold plants on the water’s surface, letting roots dangle within the water column, to help remove contaminants from contaminated water, especially in stormwater ponds. Many conventional FTWs are made with plastic components, such as mats and plastic cup containers, which can release microplastics into the environment over time. The goal of this project was to design and test a new type of FTW that does not depend on plastics to support FTW flotation. The study took place …