Engineering Commons^™

Optimal Design Of Coreless Axial Flux Pm Machines Using A Hybrid Machine Learning And Differential Evolution Method, Matin Vatani, David R. Stewart, Pedram Asef, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

Coreless stator axial flux permanent magnet (AFPM) machines require computationally intensive three dimensional finite element analysis (FEA) for accurate performance evaluation, making optimization time-consuming and impractical for large-scale design studies. This paper presents a hybrid optimization approach that integrates differential evolution (DE) with artificial neural networks (ANNs) to accelerate the optimization of coreless AFPM machines. In this method, DE driven FEA simulations generate a dataset used to train an ANN surrogate model, significantly reducing reliance on direct FEA computations. The effectiveness of this approach is demonstrated through a multi-objective DE optimization, where the ANN’s predictions are validated against FEA results. …

Winding Factors And Harmonics Of Coreless Axial Flux Pm Machines, Matin Vatani, John F. Eastham, Xiaoze Pei, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

This paper provides a comprehensive analysis of the winding factor and winding harmonic distribution in coreless stator axial flux permanent magnet (AFPM) machines. The topology of this type of machine and its similarities to conventional cored AFPM machines are discussed. Popular pole/coil number combinations in coreless stator AFPM machines are identified and analyzed in detail. It is demonstrated that the winding factor in these machines varies with radius and can be expressed as the product of the conductor distribution factor, pitch factor, and coil group factor. The formulas for each factor are derived and presented in multiple forms based on …

Performance Evaluation Of Highly Modified Asphalt-Based Binders In High Friction Surface Treatment: Comparative Study With Epoxy-Based System, Alireza Roshan, Magdy Abdelrahman, Mohyeldin Ragab

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

High Friction Surface Treatments (HFSTs) are frequently used to increase skid resistance and reduce collisions, particularly in crash-prone zones, including horizontal curves and intersections. Epoxy-based binders traditionally have been the sole option for HFSTs, but their drawbacks, such as high costs and compatibility challenges, have led to the search for substitute binders, including asphalt-based options. This study investigates the comparative performance of highly modified asphalt-based binders, including polymer-modified, mastic, and highly modified emulsions, in HFST applications using two aggregate types, Calcined Bauxite (CB) and Rhyolite with different gradations, with an emphasis on their frictional properties, durability, and resistance to polishing. …

Survival Signature Estimation Using Optimization And Monte-Carlo Simulation For K ≥ 3 Classes Of Nodes On Two-Terminal Networks, Md Sazid Rahman

Graduate Theses and Dissertations

This research develops an efficient approach to estimating survival signatures for two-terminal networks with more than two classes of components. Recently, the survival signature has gained substantial attention in the literature on network reliability estimation due to its unique separability property, which enables passing the network topology information independent of the failure distribution of the components. Following recent results from the literature, estimating the two-terminal survival signature by Monte Carlo simulation entails solving a multi-objective maximum capacity path problem on a two-terminal network in each replication. We adapt a multi-objective Dijkstra’s algorithm from the literature to construct the set of …

Vision-Based Multimodal Frameworks For Human Behavioral Analysis: Applications In Group Activity Understanding And Public Health, Naga Venkata Sai Raviteja Chappa

Graduate Theses and Dissertations

Group Activity Recognition (GAR) has emerged as a crucial problem in computer vision, with wide-ranging applications in sports analysis, video surveillance, and social scene understanding. Unlike traditional action recognition focused on individuals, GAR requires understanding complex spatiotemporal relationships between multiple actors, their interactions, and the broader context in which these activities occur. This complexity introduces unique challenges, including the need for accurate actor localization, modeling of inter-actor dependencies, and understanding of temporal evolution in group behaviors. While recent advances have shown promise, existing approaches often rely heavily on extensive annotations such as ground-truth bounding boxes and action labels, creating significant …

Flexible Microelectrode-Based Impedance Immunosensor For Rapid Detection Of E. Coli O157:H7, Sonatan Kumar Biswas

Graduate Theses and Dissertations

Abstract Food contamination poses a significant threat to public health, the economy, and human health worldwide, occurring at any stage of the food supply chain, from farm to fork. Escherichia coli 0157:H7, recognized as one of the principal causes of foodborne illness, poses a considerable risk to food safety. The primary objective of this investigation is to devise a flexible microelectrode-based immunosensor capable of swiftly identifying E. coli O157:H7 cells without the need for incubation in a pure culture environment. In the development of the biosensor, the gold electrode (composed of 50% Au) underwent an initial coating process involving 2-aminoethanethiol/cysteamine, …

Using Deep Learning And Two-Photon Excitation Fluorescence Microscopy To Predict Breast Cancer Recurrence And Response To Chemotherapy, Nicholas Powell

Graduate Theses and Dissertations

Accurate prediction of breast cancer recurrence plays a critical role in guiding treatment decisions, particularly regarding the use of systemic therapy for patients. While genomic assays such as the Oncotype DX Recurrence Score offer valuable prognostic information, they are limited in accessibility and application. The work presented in this thesis explores an imaging-based approach for the prediction of breast cancer recurrence that combines multiphoton microscopy (MPM) with deep learning to classify individual breast cancer biopsy samples by risk of recurrence. Genomic differences in tumors with different recurrence potentials may translate to distinct optical and structural information that can be captured …

Analog Low Dropout Regulator Design Within A 12nm Finfet Node, Harshdeep Singh

Graduate Theses and Dissertations

Modern ICs require the use of multiple voltage regulators to regulate power, this creates the need for analog low dropout regulator (LDO) designs in more advanced nodes such as for the 12nm FinFET process. Analog design is particularly challenging in FinFET processes due to a variety of factors, such as quantized parameters, large parasitic values and length of diffusion effects. An analog LDO was chosen for its improved power supply rejection ratio (PSRR) over digital and hybrid approach which is a key metric for voltage sensitive applications. The LDO was designed through an iterative approach to address the difficulty of …

Intelligent Crowdsourcing Based On Online Social Networks, Adedamola Adesokan

Electrical and Computer Engineering ETDs

The prevalence of Online Social Networks has completely changed how individuals communicate and cooperate. This dissertation explores the integration of intelligent crowdsourcing mechanisms into OSNs, focusing on game theory, reinforcement learn- ing, and social network dynamics to enhance the allocation of tasks, participation by users, and distribution of rewards. It proposes several models that utilize trust- based models, hedonic coalition games, and influencer dynamics for optimization of crowdsourcing. The major challenges to be addressed include task selection, reward distribution, and incentivizing participation, taking into consideration aspects re- lated to social influence, trust, and user engagement. The models so proposed have …

Ultrafast Laser Surface Structuring For Wettability Control On Copper, Akshay Arvind Nagvenkar

All Theses

Wettability is a crucial surface property influencing various phenomena, including heat transfer, cell adhesion, and corrosion. Engineering devices can achieve superior performance by precisely manipulating surface wettability. As a result, extensive research has focused on developing surfaces that exhibit either extreme water attraction (superhydrophilic) or strong water repellency (superhydrophobic). Tailoring surface wettability paves the way for numerous applications, such as drag reduction in marine vessels, controlled drug delivery, efficient water collection, advanced liquid transport systems, oil-water separation, anti-corrosion coatings, friction reduction, and self-cleaning materials. Ultrafast laser surface structuring is a promising approach for engineering multifunctional surfaces, effectively modifying material properties …

Impacts Of Cognitive Workload On Veteran Driver Reaction Time: Predictive Modeling Using Bayesian And Machine Learning Methods, Kenneth Ofosu-Kwabe

All Theses

In high-demand environments, the ability to manage cognitive workload can mean the difference between optimal or safe performance and critical failure or accidents. Veterans face an elevated risk of fatal motor vehicle accidents due to post-deployment stress, combat-related injuries, and challenges readjusting to civilian driving. This study explores how cognitive workload affects reaction time performance using a driving simulator by collecting and analyzing subjective workload ratings (using the NASA-TLX survey), physiological signals from eye-tracking and performance data from a sample of 28 Veterans.

We examined how task difficulty, cognitive indicators and personal attributes influence reaction times across an interactive driving …

Tsunamigenesis On A Buoyant Granular Layer As A Model Of Ice Mélange In Ice-Choked Fjords, Nathan F. Reyner

All Theses

Glacial calving events can often create destructive tsunami waves in ice-choked fjords in the arctic region, posing a threat to local inhabitants and damaging coastlines. Here the sea is covered by a polydisperse granular material called ice mélange, whose properties can affect the wave characteristics. To investigate the role of a buoyant granular layer, as a model of ice mélange, on tsunami generation, or tsunamigenesis, a series of laboratory experiments were conducted by collapsing a column of dense granular material into a body of water with a layer of buoyant particles distributed across the liquid surface. Experiments were performed over …

Bim-Based Automated System For Carbon Emissions And Construction Costs Estimation (Bas-Cc) In Modular Design And Production, Roshan Bandiwadekar

All Theses

Modular construction adopts a manufacturing-like construction process, enhancing the management of embodied carbon emissions in production and construction phases. However, estimating these emissions presents challenges due to the involvement of diverse stakeholders across various lifecycle stages. Additionally, cost considerations often influence design choices and material selections in modular constructions, neglecting the impact of embodied carbon emissions. To address these challenges, we present a proof-of-concept for an automated Building Information Modeling (BIM)-based system to estimate both carbon emissions and construction costs. This system automates the calculation of embodied carbon and cost implications of different modular designs and materials, enabling informed decision-making. …

Essential Components For A Uas Standard Operating Procedure Manual For State Departments Of Transportation, Nurudeen Segun Lawal

All Theses

The integration of Unmanned Aircraft Systems (UAS) within state Departments of Transportation (DOTs) has become increasingly essential for improving efficiency, safety, and regulatory compliance in transportation operations. However, the lack of a standardized approach to UAS program management has resulted in variability in policies, procedures, and implementation strategies across state agencies. This study examines how state DOTs incorporate the Association of Unscrewed Vehicle Systems International (AUVSI) Organizational Implementation Guide (OIG) 35 essential components into their UAS Standard Operating Procedures (SOPs) and identifies 13 additional components that address agency-specific operational, regulatory, and administrative needs. Through an analysis of publicly available SOPs …

Electrodeposition Of Gallium Nitride_Unraveling The Role Of Precursors, Deposition Conditions, And Substrate Effects For Semiconductor Applications, Mauricio Azier Leyva Aranzabal

Open Access Theses & Dissertations

Gallium nitride (GaN) is a wide-bandgap semiconductor noted for its remarkable optoelectronic and structural characteristics, rendering it a potential material for high-power, high-frequency, and optoelectronic device applications. This dissertation investigates the electrochemical synthesis of GaN thin films by potentiostatic and galvanostatic electrodeposition techniques using aqueous solutions of gallium nitrate (Ga(NO3)3), ammonium nitrate (NH4NO3), and auxiliary agents like potassium nitrate and urea. The main aim is to examine the essential elements affecting nitrogen incorporation and film shape while assessing electrochemical performance on various conductive substrates.A thorough investigation was performed to evaluate the impacts of electrodeposition duration, electrolyte pH, precursor molar concentrations, …

Level Of Fidelity Adaptation Of Structural Models To Support In-Space Servicing, Assembly, And Manufacturing (Isam), Maximilian Manuel Rothblatt

Open Access Theses & Dissertations

In-space servicing, assembly, and manufacturing (ISAM) operations increasingly rely on digital twin technology to perform predictive structural analysis in resource-constrained environments. A key challenge in deploying structural finite element analysis (FEA) within a digital twin lies in determining mesh fidelity settings that balance simulation accuracy with computational efficiency. This thesis presents the development of a MATLAB-based adaptive mesh refinement framework designed to identify optimal FEA mesh parameters prior to integration into a digital twin system.

The tool iteratively refines mesh resolution across faces, edges, and vertices based on von Mises stress distribution and convergence behavior. Termination criteria are governed by …

Multi-Domain Machine Learning For Biological Classification: Mallard Classification And Protein Function Prediction, Tolulope Samuel Adeyina

Open Access Theses & Dissertations

Multi-domain machine learning applications have revolutionized how we understand and predict complex biological phenomena. This dissertation presents novel computational methodologies addressing two critical problems: mallard classification using single-nucleotide polymorphisms (SNPs), and protein function prediction via interpretable topic-aware peptide embeddings. The research focuses on distinguishing mallard populations through SNP data, which are inherently characterized by ultra-high dimensionality. The research uses advanced feature-selection and dimensionality-reduction strategies alongside machine learning classification algorithms to identify minimal, yet highly predictive SNP sets crucial for accurate breed differentiation. This framework demonstrates robust performance with optimal computational efficiency, significantly aiding conservation and breed management efforts. Furthermore, the …

Binary Solid/Liquid Equilibrium Of Mixtures Of Thermally Robust Salts And Molecular Compounds For Use As Heat Transfer Fluids, Jared Ridge Mathews

Honors Theses

Fossil fuels, contributors to climate change that may bear catastrophic consequences, power the entire world. The human species is almost entirely dependent on fossil fuels for energy, but other sources of renewable and environmentally friendly energy must be developed. Concentrated solar power (CSP) is a promising source of renewable energy with hampered potential—better heat transfer fluids (HTFs) are needed for it to be economically feasible. Currently, the HTFs in industrial use are predominantly either synthetic oils or nitrate-based molten salts. Synthetic oils are only stable up to 400 °C, and molten salts often have high melting temperatures, making them prone …

Design And Optimization Of Aquaculture Gear: Development Of A Cage-Integrated Reeling Mechanism For Oyster Farming, Felicity Bryant

Honors Theses

This project encompasses the design, fabrication, and testing of a cage-integrated reeling system aimed at reducing the physical labor required in oyster aquaculture at Bama Bay Oyster Farm, the last operational oyster farm in Mobile Bay. The proposed system includes two primary components: lightweight, modular oyster cages and a dual-winch reeling device for automated retrieval. Three cage prototypes—rectangular, oval, and hexagonal—were evaluated for structural performance and fabrication feasibility. The oval design was ultimately excluded due to practical fabrication limitations. The rectangular and hexagonal designs were fabricated using recycled materials and tested under the most extreme environmental conditions derived from years …

Graphics Processing Unit-Enabled Path Planning Based On Global Evolutionary Dynamic Programming And Local Genetic Algorithm Optimization, Junlin Ou, Ge Song, Yi Wang

Faculty Publications

This paper presents a novel path planning method for real-time robotic path planning in a dynamic environment involving moving obstacles. It combines on a holistic platform a global approach to rapidly generate initial paths of prominent diversity and a heuristic approach to enable local path refinement for enhanced computational efficiency, exploration, and robustness. The global approach innovates a formulation that treats a path planning problem with a visibility graph as a Markov decision process and decomposes the process into many subproblems. A new evolutionary dynamic programming approach (EDP) is proposed to solve these subproblems in an iterative manner using …

Development And Characterization Of Quercetin-Loaded Microparticles Via Spray Drying For Pulmonary Drug Delivery Applications, Daniel Jose Perez Torres, Samantha Ann Meenach

Senior Honors Projects

Pulmonary inflammation is associated with respiratory

disorders such as pulmonary arterial hypertension and chronic

obstructive pulmonary disease. A hallmark of these diseases is

an increase in reactive oxygen species in the body, leading to

further inflammation and acerbation of these diseases.

Fortunately, a class of natural products termed plant-derived

flavonoids have been found to alleviate inflammation and

oxidative stress in lung tissue, making them promising

therapeutic agents for the treatment of pulmonary diseases.

Flavonoids are accessible and cost-effective, with quercetin

being one of the most commonly consumed flavonoids in the

human diet. Despite its therapeutic potential, the efficacy of

quercetin …

Cross-Dataset Fairness Evaluation Of Transformer-Based Sentiment Models, Sara Zuiran

Theses and Dissertations

With the growing exploration of Natural Language Processing (NLP) systems in decision-making environments, it is essential to evaluate technical and ethical aspects of the dataset and the NLP model to improve fairness. To assess fairness, the thesis examines demographic imbalances in sentiment classification models by evaluating transformer-based models fine-tuned on the Stanford Sentiment Treebank version 2 dataset (SST-2) against the demographically annotated Comprehensive Assessment of Language Model dataset (CALM). This work identifies performance disparities in sentiment prediction across demographic groups by examining sensitive attributes such as gender and race. The study evaluates both the RoBERTa and MentalBERT transformer models using …

Design And Implementation Of Asynchronous Communication In Multi-Chiplet Systems: A Comparative Study Of Pseudo-Crossbar And Bus Architectures, Matthew Clemence

Graduate Theses and Dissertations

System-on-Chip (SoC) complexity continues to present challenges in global clock distribution and power management. The Globally Asynchronous Locally Synchronous (GALS) approach addresses these issues by enabling asynchronous communication between locally synchronous chiplets. This thesis details the design and implementation of two GALS architectures employing asynchronous handshaking protocols through Multi-Threshold CMOS NULL Convention Logic (MTNCL). The first architecture, a pseudo-crossbar, uses arbiters and multiplexers/demultiplexers (MUX/DEMUX) for prioritized and dynamic communication between chiplets. The second, a bus-based approach, employs D-latches to manage communication sequentially with predetermined interrupts. This research explores the detailed implementation, functional distinctions, scalability, and integration trade-offs inherent to each …

Robust Distributed Learning Against Both Distributional Shifts And Byzantine Attacks, Guanqiang Zhou, Ping Xu, Yue Wang, Zhi Tian

Electrical and Computer Engineering Faculty Publications

In distributed learning systems, robustness threat may arise from two major sources. On the one hand, due to distributional shifts between training data and test data, the trained model could exhibit poor out-of-sample performance. On the other hand, a portion of working nodes might be subject to Byzantine attacks, which could invalidate the learning result. In this article, we propose a new research direction that jointly considers distributional shifts and Byzantine attacks. We illuminate the major challenges in addressing these two issues simultaneously. Accordingly, we design a new algorithm that equips distributed learning with both distributional robustness and Byzantine robustness. …

Effects Of The Gravity Gradient On The Path Of 1i/‘Oumuamua, Hannah R. Richardson

Poster Presentations

In October 2017, the asteroid 1I/’Oumuamua first passed into viewing range [1]. The asteroid is notable for being the first interstellar object to enter the solar system. 1I/’Oumuamua was also unusual in its geometry; it is thought to have an aspect ratio of 6:1 and a length of approximately 400 m [2] [3]. The asteroid was observed to experience a non-Keplerian acceleration estimated to be on the order of 1×10−6 m s-2 Several theories have been proposed for the cause of this acceleration, all of which are non-gravitational in nature: volatile outgassing, photon pressure, and solar winds [1][4]. However, none …

Life Cycle Analysis Of Cosmetic Products -- Assessing Environmental Sustainability And Potential Impacts, Karina Magro Machado

Theses, Dissertations and Culminating Projects

The cosmetic industry has a significant environmental footprint due to its reliance on water, energy, petrochemical-derived ingredients, and plastic-based packaging. This study performs a cradle-to-grave Life Cycle Analysis (LCA) to evaluate the environmental impacts of three cosmetic products: CeraVe Daily Moisturizing Lotion, bareMinerals Gen Nude Powder Blush, and Gillette Foamy Regular Shave Cream. The analysis was conducted using OpenLCA software and free databases, modeling each product across raw materials, packaging, manufacturing, transportation, use and end-of-life phases. The results showed that the shave cream had the highest environmental burden to three out of the four categories, especially in consumption and carbon …

Characterizing Heating And Resistance Properties Of Nichrome Burn Wire To Be Used In Cubesat Actuation, Noah Moix

Mechanical Engineering Undergraduate Honors Theses

This thesis investigates the use of Nichrome 60 wire as a burn wire mechanism, commonly utilized in CubeSats and other aerospace engineering applications requiring precise, single-use release systems. The experiment focused on characterizing the thermal and resistive behavior of Nichrome 60 wire under Joule heating conditions. Four wire configurations were tested: 34-gauge and 36-gauge wires, each at lengths of 1 inch and 2 inches. Each configuration was subjected to a constant current until thermal failure occurred. During testing, real-time measurements of electrical resistance and wire temperature were recorded. This data was used to generate resistance vs. temperature profiles for each …

Modeling Cell Buildup And Release In An Ultrafiltration Cartridge, Holiday B. Derosier

Chemical Engineering Undergraduate Honors Theses

While membrane filtration has improved greatly and has been incorporated into many modern practices, there isn’t much data on material exchange in and out of the lumen and how that effects the overall efficiency of the process. This data may help to accurately measure the reliability and efficiency of a filtration membrane system, which can lead to improvements in filtration sustainability, process lifespan, and product quality.

This project aims to model the material balance within a perfusion bioreactor ultrafiltration system in MATLAB, with a focus on bioreactors and cell buildup and release from the lumen. The results of this study …

Assessing The Fate Of Antibiotic Resistance Genes In Wastewater Treatment Processes, Gunter A. Campbell

Civil Engineering Undergraduate Honors Theses

The increasing need for clean water has paved the way for the creation of systems for reusing water, such as wastewater treatment plants (“WWTPs”), to provide potable water. But in recent years, such systems have raised concerns about the distribution of antibiotic resistance genes (“ARGs”). Bacteria are adapting to antibiotics by the evolution of resistance mechanisms, such as high mutation rates and horizontal transfer. The presence of ARGs, particularly tetracycline ("tetA") resistance genes, in wastewater effluents is of concern, as they can survive treatment, spread to bodies of water, and pose a threat to human health. In this study, the …

From In-The-Head To In-The-World: Frameworks For Understanding And Applying Computational Thinking, Justin Olmanson, Gretchen K. Larsen, Azadeh Hassani

Department of Teaching, Learning, and Teacher Education: Faculty Publications

In the five decades since Papert coined the term Computational Thinking (CT), it has become a core framework for thinking about learning, problem-solving, design, and creativity. Although CT is most commonly, and initially, associated with the cognitive orientations involved in coding and learning to code, it also includes situated and critical processes related to computational problem solving. Herein we unpack ways researchers in different fields and points in time have organized CT. We include creative coding as a uniquely generative lens for rethinking CT, outlining its potential as an expressive, constructionist, and culturally situated practice. In doing so, we explore …