Engineering Commons^™

Detecting Wireless Security Threats Through Ieee 802.11 Frame Field Anomalies, Aria Young

Williams Honors College, Honors Research Projects

It is not uncommon for most public spaces to offer Wi-Fi, while it is convenient and affordable, there are significant security risks due to its open nature. Rogue access points pose a security threat to many networks because they have the potential to bypass security measures and intercept traffic containing sensitive information. The attempt to formulate a method that one hundred percent guarantees the detection of a rogue access point has proven to be an intricate and complex problem for many to tackle, as there are numerous ways a rogue access point can be configured. This project aims to demonstrate …

Artificial Intelligence’S Role And Impact On The Engineering Discipline, Andrew Angelini

Williams Honors College, Honors Research Projects

The purpose of this Honors Research project was to explore the impact of Artificial Intelligence (AI) on the Engineering Discipline as a whole. Specifically, civil engineering’s discipline of transportation was used to display the effectiveness of AI in engineering. This discipline was used due to its wide use in engineering and overall designs that can be created within this discipline. These designs include maintenance of traffic plans, engineering plan sets, horizontal and vertical curve design, intersection design, traffic signaling, highway material design, and phasing of intersections and traffic accounting for pedestrians. Through similar prompts that were given to a publicly …

Ultrasonic Sensor-Based Sound Synthesis Using Raspberry Pi Pico W, Niraj Jaishwal

Williams Honors College, Honors Research Projects

At the intersection of Human Computer Interaction and digital art, this project transforms simple motion into musical expression. It explores an interactive real-time sound synthesis system using ultrasonic sensors to generate continuous audio. The objective is to design a system that maps physical distances into musical parameters such as pitch and amplitude, which will create a responsive audio environment. Two ultrasonic sensors are used in combination with the Raspberry Pi Pico W microcontroller running CircuitPython and Adafruit Audio Hat for real-time sound output. One sensor controls the pitch of the generated tone, while the other controls volume. This enables expressive …

Design And Development Of A Rapid Tensile Quench Rig, Tyler Jewell, Justin Naylor

Williams Honors College, Honors Research Projects

This report outlines the design process and implantation of a tensile quenching rig that incorporated forced convection and a frequency generator. When any metal is quenched, a vapor barrier forms around it. When this happens, it limits the heat flux that may occur until the barrier turns into just nucleate boiling. The vapor barrier acts as an insulator and causes the heat flux to fluctuate, causing uneven hardening which would limit the use of some materials. To combat this effect, we are trying to use forced convection, and something new, which is adding high frequency waves into the quenching process. …

Personalized Physics Learning Through Ai: Insights From Problem Generation, Chatbot Dialogues, And Intelligent Tutoring Systems, Atharva Dange

Physics Dissertations - Archive

Artificial intelligence (AI) is poised to transform science education, yet questions remain on how best to integrate these technologies into teaching and learning. This dissertation investigates the use of AI-driven tools in university physics courses through three complementary studies. In the first study, a generative language model (ChatGPT) was used to create novel physics homework problems aligned with course objectives. Analysis showed that, after expert vetting, AI-generated questions can foster higher-order problem-solving and reduce student reliance on solution memorization, though careful instructor oversight is required to ensure accuracy. The second study embedded an AI chatbot as a learning aid in …

The Bacteriostatic, Regenerative, And Immunomodulatory Properties Of Extracellular Matrix Particles For Lung Injury, Keera P. Rhoads

Theses and Dissertations

Acute respiratory distress syndrome (ARDS) is a prevalent, life-threatening lung condition, affecting nearly 200,000 Americans annually, with a 40% international mortality rate. There is no cure for ARDS, and current pharmacological treatments have limited effectiveness. Symptoms can be mitigated with mechanical ventilation, though this often leads to ventilator-induced lung injuries (VILI) and puts critically ill patients at risk of infections, including ventilator-associated pneumonia (VAP). A promising therapeutic is the extracellular matrix (ECM), a complex network of structural proteins and bioactive molecules that has been shown to have anti-inflammatory properties and prevent fibrosis. We aim to utilize the regenerative and immunomodulatory …

Multiphysics Modeling Of Material Response To High-Intensity X-Ray And Laser Pulses: Heating, Ablation, And Plasma Expansion, Youssef Abouhussien

Theses and Dissertations

This dissertation presents a computational framework to investigate material response under high-intensity X-ray fluxes produced by an exo-atmospheric nuclear detonation and laser-material irradiations, with a focus on heating, ablation, and plasma expansion phenomena relevant to satellite vulnerability and high-energy-density environments. A hybrid Monte Carlo and Two-Temperature Model (MC-TTM) was developed to simulate X-ray and laser energy deposition and thermal relaxation in metals and semiconductors across a range of X-ray and laser pulse durations from femtoseconds to nanoseconds. Results demonstrate distinct thermal behavior between materials, with ablation thresholds and phase transitions captured in good agreement with experimental data.

In parallel, a …

Exploring The Stem Career Identity Development Of Black Women Across Their Lifespan, Veronica Hurd

Theses and Dissertations

Although STEM is the fastest-growing career sector, Black women are grossly underrepresented as they account for 2.5% of the workforce. Research highlights that this underrepresentation is due to racialized structures in K-12, postsecondary, and career settings that restrict Black girls’ and women’s STEM opportunities. While macrosystems such as hegemonic ideologies, attitudes, and social conditions shape Black girls’ and women’s opportunities in STEM, they continue to persist and achieve their career goals. To explore these barriers and Black women’s persistence in this industry, this study draws from the autobiographical memories of 10 Black women in the field or formerly in the …

Optical Study Of Small Jet Engine Combustion Ignition, Bryce Anthony Ullman

Browse all Theses and Dissertations

Improving the ignition reliability in small-scale gas turbine engines is critical for safety aspects of auxiliary power units (APUs). To better understand the ignition characteristics of these small-scale combustors, an optically accessible combustor is designed and tested. The combustor accommodates twelve prevaporizer tubes (PVTs) in accordance with the commercial-off-the-shelf (COTS) rendition and allows for interchangeable materials (quartz and Inconel) and igniter positions. Another notable design feature introduces a quartz outer combustor liner to allow visualization into key regions of the combustor. The study aims to replicate a COTS ignition sequence using glow plug igniters and examine the effects of different …

Transient Power And Thermal Management Of A Hypersonic Vehicle, Jacob H. Jadischke

Browse all Theses and Dissertations

Design of high speed vehicles necessitates incorporating power generation and thermal management systems. Power generation is required as traditional high-speed propulsion sources do not contain rotating components to extract power, and the harsh external thermal environment calls for thermal management. To size these systems, the transient power requirements and the heat generated inside the vehicle must be understood. Sizing these systems at the earliest stages of the vehicle design allows for a more optimized geometry and a trajectory to design the most favorable vehicle. Characterization of these low-quality power and thermal loads from the actuation and fuel pump subsystems has …

Enhanced Diagnostics And Surveillance Of Enteroviruses Including Serotypes Associated With Acute Flaccid Myelitis, Denise Lynette Kramer

Browse all Theses and Dissertations

Prior to 2014, Enterovirus D68 infections typically caused symptoms resembling the common cold. From 2014-2018, D68 was associated with an increase in acute flaccid myelitis. However, since 2020, neurological complications have all but disappeared. We selected 1076 respiratory specimens previously determined to be positive for rhinovirus or enterovirus from Department of Defense members and their beneficiaries collected globally from October 2018 through January 2024 and underwent sequencing. Of these specimens, 93.7% were identified as rhinoviruses, while 6.3% were enteroviruses, including 30 enterovirus D68. We utilized the Nextstrain bioinformatic pipeline to reconstruct the phylogenetic relationship of these 30 D68 viruses. Twenty-two …

Leveraging Counterfactuals For Enhanced Natural Language Inference: A Multitask Knowledge Distillation Approach, Brian J. Davis

Browse all Theses and Dissertations

Natural-language inference (NLI) asks whether a hypothesis is entailed by, contradicts, or is neutral with respect to a premise. Modern transformers reach high raw accuracy on benchmarks such as SNLI, MNLI, and ANLI, yet they often rely on brittle lexical shortcuts and provide little insight into their decision process. This thesis shows that counterfactual-augmented knowledge distillation can simultaneously boost robustness and supply faithful, token-level explanations—without scaling model size. Four T5-v1_1 students (60M, 220M, 770M, 3B parameters) are trained under four curricula: (1) standard fine-tuning, (2) fine-tuning with free-text rationales, (3) multi-task distillation with naive counterfactuals, and (4) multi-task distillation with …

Hardware Trojan Detection In A Segmented Mixed-Signal Circuit Via Leakage Current, Christopher James Otey

Browse all Theses and Dissertations

As computers and integrated circuits become more commonplace, the risk of a Hardware Trojan attack becomes more worrisome. Trojans can exploit design flaws or be inserted between essential components to leak information, change the circuit function, or destroy the circuit altogether. Several methods of trojan detection and prevention have been introduced, however few can handle combined analog and digital circuits, known as mixed-signal circuits. This thesis demonstrates a Hardware Trojan detection method implemented in an Analog-to-Digital Converter (ADC), which is a mixed-signal circuit. The detection method involves splitting the circuit into segments with approximately equal leakage currents (a large part …

Computational Analysis Of A Hafnium-Titanium Alloy Mechanical Properties From First Principles, Abdul Mughni

Browse all Theses and Dissertations

Hafnium and titanium, along with zirconium, are refractory metals with unique properties suitable for extreme-environment applications. Utilizing alloys based on these elements can provide suitable materials with engineered properties. Understanding their mechanical properties is necessary to determine appropriate applications. This thesis research aims at employing quantum-based atomistic simulations to estimate mechanical properties of pristine hafnium, titanium and an alloy based on these elements. The results are compared to available experimental data and the corresponding implications are explored.

Data-Driven Prediction Of Temperature Distribution In Multi-Laser Powder Bed Fusion Using Convolutional Neural Networks, Majid Dousti

Browse all Theses and Dissertations

Additive Manufacturing (AM), particularly Laser Powder Bed Fusion (L-PBF), has gained significant traction in fabricating complex, high-performance metallic components. However, the inherent complexity and computational cost of high-fidelity simulations pose challenges for real-time monitoring and optimization of multi-laser powder bed fusion processes. This study proposes a data-driven surrogate modeling approach using a deep learning architecture to efficiently and accurately predict three-dimensional temperature distributions during ML-PBF. A 3D convolutional neural network (CNN) model, named Decoder-CNN, is developed and trained on a dataset of simulated thermal fields corresponding to various process configurations, including different laser power, scanning speed, and beam arrangements. The …

Optimizing Cloud Computing Resources For Operational Cost And Application Performance Using Machine Learning, Isaac K. Matthew

Browse all Theses and Dissertations

As AI-driven workloads accelerate the growth of cloud initiatives and spending, resource waste also increases due to persistent inefficiencies in cloud compute and infrastructure management. Overprovisioned resources and suboptimal configurations often lead to operational inefficiencies and unnecessary financial overhead. These challenges arise from the difficulty of anticipating resource demands in dynamic workloads and selecting suitable virtual machines to ensure optimal performance. Our research proposes a holistic, data-driven framework for managing cloud compute resources that reduces costs without compromising application performance. We integrate a predictive, model-driven, threshold-based autoscaling solution for cloud-native applications with an optimized instance right-sizing approach to select cost-effective …

Evaluating Geometric Accuracy In 3d Printing (3dp) Comparative Study Of Different 3dp Processes Using Cmm And Vision Measurement Tools, Alexander Adams

Browse all Theses and Dissertations

This study investigates how various additive manufacturing (AM) technologies and parameters influence part quality by fabricating three uniquely designed artefacts. Artefact 1 is a rectangular block with stepped arches, thin and solid extruded features, and holes of varying shapes and sizes. Artefact 2 consists of a base plate with angled overhangs from 15 to 90 degrees. Artefact 3 includes a tall cylinder, a five-step cylinder, and two half arches of different scales. Each artefact was printed ten times using: metal PBF (Inconel 718), nylon PBF (Nylon 12), Vat Polymerization (GRY photopolymer), and material extrusion (nylon carbon fiber). Dimensional analysis was …

Reducing Operator Training Time Through Virtual Reality: A Case Study On The Lpkf Protomat E44 Machine, Joshua C. Patel

Browse all Theses and Dissertations

This thesis presents the development of an immersive virtual reality (VR) simulation that replicates the operation of the LPKF ProtoMat E44 PCB milling machine. Aimed at reducing operator training time and improving procedural understanding, the simulation offers an interactive and realistic environment where users can safely engage with machine workflows and start-up sequences. The emphasis is on accurate representation, usability, and maintaining immersion to support intuitive learning. Although formal evaluation is outside the scope of this work, the system is designed to serve as a foundation for cost-effective, scalable training in technical and manufacturing contexts, offering a modern alternative to …

Study Of Fiber-Loaded Slurries For Ceramic Matrix Composite Fabrication By Additive Manufacturing, Gaspard Matondo

Browse all Theses and Dissertations

We studied the additive manufacturing of an alumina-matrix composite reinforced with alumina fibers using the Admatec Admaflex 3D printer, which utilizes digital light processing technology. Oxide-oxide composites are composite materials in which both the matrix and the reinforcing element are ceramic oxides. Monolithic alumina ceramic exhibits a good combination of thermal and mechanical properties, including thermal shock resistance, high melting point, thermal oxidation resistance, good thermal conductivity, hardness, and mechanical strength. However, it is very brittle. Introducing alumina fiber as a reinforcing material into the alumina matrix is expected to enhance mechanical properties, particularly toughness, making the ceramic matrix composite …

Reinforcement Learning For Adversarial Systems Using Relational Observations, Sophia Christine Gilson

Browse all Theses and Dissertations

This thesis investigates the integration of relational observations with the reinforcement learning (RL) framework for improved generalization capability. A hide-and-seek simulation environment is designed in Unity for proof-of-concept demonstration. Two observation representations—relational (analogical) and standard positional—are designed to evaluate agent learning and generalization capabilities. Agents are trained using the Proximal Policy Optimization (PPO) and Soft Actor Critic (SAC) algorithms in a random-room environment and tested in both the random-room environment and a novel environment with greater spatial complexity and path obstructions. Comparative studies indicate that relational representation of objects in the adversarial environment could potentially improve the generalization capability of …

Scalable Real-Time Stream Clustering For Unbounded Text Streams, Nathaniel C. Crossman

Browse all Theses and Dissertations

Social media, AI systems, IoT sensors, and other platforms generate vast amounts of streaming data. Given this vast volume of information, techniques that can reduce and aggregate data into meaningful topics are essential. One such technique is the two-phase stream clustering approach. In the first, online micro-clustering phase, the system forms micro-clusters from the incoming data stream, incrementally merges new items into related existing micro-clusters, and prunes or fades micro-clusters as they become inactive, producing a constantly updating yet compact set of micro-clusters representing potential topics and subtopics of the stream. In the second, offline macro-clustering phase, these micro-clusters are …

Patient Subset Classification Using Encoded Embeddings And Knowledge Graph Retrieval-Augmented Generation, Benjamin A. Holmes

Browse all Theses and Dissertations

The widespread adoption of electronic medical records has created a vast reservoir of clinical data that can be leveraged to better understand how interventions relate to patient outcomes. Much of this information, however, exists as unstructured free-text, posing significant challenges for traditional statistical and machine-learning methods. Solving these challenges would allow the extraction of specific patient subpopulations (clinically relevant cohorts of individuals who share overlapping symptoms, risk factors, or diagnostic criteria), which could be used in precision medicine. Despite this promise, extracting these subpopulations from unstructured medical notes is an ongoing challenge due to the variability of clinical language and …

Using Unsupervised Machine Learning To Experimentally Categorize Separation On Low-Pressure Turbine Blades, Aaron B. Suter

Browse all Theses and Dissertations

Laminar boundary layer separation can significantly degrade the efficiency of Low-Pressure Turbine (LPT) blades. While active flow control (AFC) methods can mitigate these losses, energy-efficient implementation requires activating the system only when performance decreases. This study validates an unsupervised machine learning framework that utilizes sparse, discrete surface-pressure measurements to distinguish between high and low aerodynamic loss states. A fuzzy c-means (FCM) clustering model was trained on limited pressure data obtained in a low-speed linear cascade across Reynolds numbers from 30,000 to 160,000 and used to categorize the flow regime in real time. At Re = 40,000, vortex generator jet (VGJ) …

Vagus Nerve Stimulation Ameliorates Cognitive Impairment Caused By Hypoxia, Birendra Sharma

Browse all Theses and Dissertations

Hypoxia disrupts brain function due to the high demand for oxygen, leading to significant cognitive impairments. While vagus nerve stimulation (VNS) has been shown to enhance cognition, its ability to counteract hypoxia-induced deficits remains unclear. In this study, male Sprague–Dawley rats were assigned to sham, hypoxia, or VNS + hypoxia groups, with VNS delivered during hypoxia (8% oxygen) using biphasic pulses (100 μs, 30 Hz, 0.8 mA). Cognitive performance was evaluated using multiple behavioral paradigms, and hippocampal tissue was analyzed for neurotrophin expression through quantitative PCR and immunohistochemistry. Among the behavioral measures, hypoxia specifically impaired performance on the passive avoidance …

Utilizing Optimization Tools For Passive Flow Control Passage Loss Reduction In Low-Pressure Turbines, Bryant Robert Duane Burton

Browse all Theses and Dissertations

Low-pressure turbines (LPTs) play a crucial role in fuel efficiency and thrust generation of aero-engines. Traditional LPT designs, however, involve multiple stages and numerous blades, resulting in increased weight and manufacturing costs. The challenge of modern- day researchers is to reduce the weight and cost but maintain the high efficiency of LPTs. To address this, one approach is to increase the aerodynamic loading of individual blades, reducing the blade count. However, this can lead to increased secondary losses caused by flow separation, particularly in the endwall regions. This research focuses on optimizing the blade profile at the junction with the …

Quantification Of Porosity In Hfb2–20%Sic Using Convolutional Neural Networks, Cameron J. Floyd

Browse all Theses and Dissertations

Ultra-high-temperature ceramics, commonly used in aerospace applications, operate in high-temperature oxidizing environments where a surface scale forms and regulates oxy gen access. For hafnium diboride–silicon carbide (HfB2–SiC), that scale consists of a borosilicate glass layer over a porous HfO2 skeleton. Oxygen transport through this poros ity governs the kinetics of mechanistic models, requiring reproducible inputs for accurate pore fraction (PF), pore-size distributions, and ultimately tortuosity. This thesis replaces rule-based SEM thresholding with a convolutional neural network that segments pores and predicts the pore-radius distribution for transport models. The resulting calibrated porosity maps and size distributions transfer within the acquisition domain …

Effect Of Build Orientation And Environmental Conditions On Mechanical And Geometric Properties Of Polymeric Parts Fabricated By The Powder Bed Fusion Process, Adedamola O. Adeyemi

Browse all Theses and Dissertations

Polyamide-12 (aka PA12) is a synthetic thermoplastic polymer that has been used in various applications, including the electronic and electrical, oil and gas industrial manufacturing and automotive industry. There are several ways to manufacture parts with PA12 and PA12 based composites. Injection molding, a traditional manufacturing process, has been the standard manufacturing route for polymers for a long time. Recently, however, additive manufacturing (AM) processes, such as powder bed fusion (PBF) and material extrusion (ME) have been introduced. PBF is a manufacturing process characterized by the selective sintering of successive layers of powdered material. It is the most effective AM …

Generative Adversarial Networks (Gans) For High-Dimensional Biological Data, Harigovind Harikumar

Browse all Theses and Dissertations

This thesis investigates the application of Generative AI models, mainly Generative Adversarial Network (GAN) models to high dimensional and low sample size biological datasets like Motion Sickness, Breast Cancer, Crohn, and Melanoma. We utilized and compared three generative AI frameworks: Vanilla GAN, Wasserstein GAN (WGAN), Locality-Sensitive Hashing GAN (LSH-GAN) and Omics GAN. To address the challenges associated with high-dimensionality and low sample size, which was leading to very poor outputs of biological synthetic samples, we came up with an approach to stop the model when it reaches its saturation level. That is, we printed the loss plots to see where …

The Role Of Trpm7 In Mouse Development And Immune Cell Function, Jananie Rockwood

Browse all Theses and Dissertations

Transient receptor melastatin 7 (TRPM7) functions both as an ion channel and a protein kinase. TRPM7 has been implicated in Mg2+ homeostasis, embryogenesis, cardiac automaticity, and immunity. The purpose of this research was to deepen our understanding of TRPM7 channel and kinase functions. To this end, we used two transgenic mouse models: the TRPM7 gain-of-function (GOF) and TRPM7 kinase-dead (KD) mice to address the consequences of increased channel activity and kinase inactivation, respectively. Global deletion of TRPM7 or the kinase domain alone are embryonic lethal, therefore, we used the TRPM7 GOF mouse to investigate germline transmission. We examined embryo development …

Pixmix Attack: Implementation And Evaluation Of A Novel Pixel Injection On Digital Video Port (Dvp) Interface In Embedded Camera Systems With Pcb Hardware Trojan, Sayed Md Tashfi Nowroz

Browse all Theses and Dissertations

Image sensors are at the heart of machine vision systems in robotics, industrial automation, and surveillance systems which ideally operate with minimal human supervision and only occasional maintenance. The image sensors convert visible light into electrical signals which are locally decoded to image on the printed circuit board (PCB) by an ordinary embedded processor System on Chip (SoC). This thesis investigates a critical vulnerability in such systems, targeting the communication protocol at the signal level during runtime. Specifically, it focuses on a novel attack in the Digital Video Port (DVP) protocol, possible to exploit with PCB-based hardware Trojans, to craft …