Engineering Commons^™

Mid-Wave Infrared Imaging Of Supersonic Combustor Exhaust Flow, Nathan Childs

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A study was completed on the application of mid-wave infrared (MW-IR) imaging for diagnostics in supersonic combustion exhaust flows, with the objective of enhancing optical access and measurement accuracy. Other optical based techniques of thermography require complicated setups and analysis to determine the temperature of a flow with high accuracy, where MW-IR is a more simplistic "point and shoot" technique. The simplicity of MW-IR comes with the trade off of gaining simplicity but adding uncertainty into the measurements. The MW-IR camera was positioned to view the exhaust of the combustor to provide an unobstructed view of the flow, addressing limitations …

Laminar Separation Control Of An Eppler 387 Airfoil, Vincent R. Sheeler

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A variety of aerodynamic devices operate at low Reynolds number conditions, such as unmanned aerial vehicles and low-pressure turbines in gas turbine engines. At low Reynolds numbers, many airfoils experience laminar boundary layer separation as the fow lacks the energy to overcome the adverse pressure gradient. Researchers have documented a variety of methods which can suppress laminar separation, and now focus on ways to reduce energy requirements to provide efective fow control. Aspects of fow control strategy such as actuator location and pulsing at frequencies which exploit natural instabilities in the fow can reduce energy requirements. In a study by …

Mobile Weather Satellite Receiver, Luke Datsko, Sam Watts, Jason Do, Adam Bechtler

Williams Honors College, Honors Research Projects

The "Mobile Weather Satellite Receiver" project aims to create a portable, user-friendly device that receives and displays weather information from geostationary satellites, addressing the limitations of traditional weather sources like the Internet and weather radio, particularly in remote areas. This device will collect and demodulate satellite data, including imagery and Emergency Managers Weather Information Network (EMWIN) forecasts, to provide users with detailed local forecasts and real-time alerts.

Designed with a user-centric approach, the system includes a satellite dish, Software Defined Radio (SDR), a Raspberry Pi, and a custom software interface for ease of use. Its portability and ability to function …

An Improved Method To Protecting Skin Graft Dressings Following Surgery In Severe Burn Patients, Andrew Martin, Matt Flaker, Hailey Essinger

Williams Honors College, Honors Research Projects

Severe burns, including deep second- and third-degree burns, affect over 450,000 people annually in the U.S., often requiring skin grafts for treatment. Recovery involves wearing wound dressings covered by bandage wraps for at least two weeks. While wraps are breathable, versatile, and simple, they can be painful to apply, especially for larger patients, and their compression varies based on the person applying them. This poses challenges when untrained caregivers are involved. Additionally, wraps often slip during physical therapy. Burn care units seek a new solution that matches current wraps in breathability and comfort but offers quicker application, controlled compression, and …

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 …

Deep Learning-Assisted Diagnostic System: Apices And Odontogenic Sinus Floor Level Analysis In Dental Panoramic Radiographs, Pei Yi Wu, Yuan-Jin Lin, Yu-Jen Chang, Sung-Tsun Wei, Chiung An Chen, Kuo-Chen Li, Wei-Chen Tu, Patricia Angela R. Abu

Department of Information Systems & Computer Science Faculty Publications

Odontogenic sinusitis is a type of sinusitis caused by apical lesions of teeth near the maxillary sinus floor. Its clinical symptoms are highly like other types of sinusitis, often leading to misdiagnosis as general sinusitis by dentists in the early stages. This misdiagnosis delays treatment and may be accompanied by toothache. Therefore, using artificial intelligence to assist dentists in accurately diagnosing odontogenic sinusitis is crucial. This study introduces an innovative odontogenic sinusitis image processing technique, which is fused with common contrast limited adaptive histogram equalization, Min-Max normalization, and the RGB mapping method. Moreover, this study combined various deep learning models …

Precision Medicine Assessment Of The Radiographic Defect Angle Of The Intrabony Defect In Periodontal Lesions By Deep Learning Of Bitewing Radiographs, Patricia Angela R. Abu, Yi Cheng Mao, Yuan Jin Lin, Chien Kai Chao, Yi He Lin, Bo Siang Wang, Chiung An Chen, Shih Lun Chen, Tsung Yi Chen, Kuo Chen Li

Department of Information Systems & Computer Science Faculty Publications

In dental diagnosis, evaluating the severity of periodontal disease by analyzing the radiographic defect angle of the intrabony defect is essential for effective treatment planning. However, dentists often rely on clinical examinations and manual analysis, which can be time-consuming and labor-intensive. Due to the high recurrence rate of periodontal disease after treatment, accurately evaluating the radiographic defect angle of the intrabony defect is vital for implementing targeted interventions, which can improve treatment outcomes and reduce recurrence. This study aims to streamline clinical practices and enhance patient care in managing periodontal disease by determining its severity based on the analysis of …

A Novel Real-Time Threshold Algorithm For Closed-Loop Epilepsy Detection And Stimulation System, Liang Hung Wang, Zhen Nan Zhang, Chao Xin Xie, Hao Jiang, Tao Yang, Qi Peng Ran, Ming Hui Fan, I. Chun Kuo, Zne Jung Lee, Jian Bo Chen, Tsung Yi Chen, Shih Lun Chen, Patricia Angela R. Abu

Department of Information Systems & Computer Science Faculty Publications

Epilepsy, as a common brain disease, causes great pain and stress to patients around the world. At present, the main treatment methods are drug, surgical, and electrical stimulation therapies. Electrical stimulation has recently emerged as an alternative treatment for reducing symptomatic seizures. This study proposes a novel closed-loop epilepsy detection system and stimulation control chip. A time-domain detection algorithm based on amplitude, slope, line length, and signal energy characteristics is introduced. A new threshold calculation method is proposed; that is, the threshold is updated by means of the mean and standard deviation of four consecutive eigenvalues through parameter combination. Once …

Improving The Accuracy Of Neighborhood Median Pixel Method (Nmpm) In Classifying Landsat-8 Oli Images By Optimizing The Scoring System’S Point Values, Abraham T. Magpantay, Proceso L. Fernandez Jr

Department of Information Systems & Computer Science Faculty Publications

The Neighborhood Median Pixel Method has previously been introduced as an image processing technique in remote sensing, developed to classify Landsat-8 OLI satellite image pixels into categories of vegetation, water, and built-up areas. This method relies on a lookup table based on the median pixel values within a pixel’s neighborhood and a scoring system that assigns point values for classification. While a 9x9 neighborhood size was originally proposed, a succeeding study suggested a 13x13 neighborhood for better classification accuracy. This study focuses on refining the scoring system used in the Neighborhood Median Pixel Method, particularly the original set of arbitrary …

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 …

Intercellular Stress Generation During 1d Collective Migration Of Cancer Cells, Logan Waddle, Jian Zhang

2025 Research Poster Competition

Physical forces drive many cellular processes such as migration and proliferation. A metastatic tumor will have invasive strands/chains that extend from the main tumor. These chains of cells collectively migrate away from the main tumor to establish new colonies elsewhere in the body. However, how physical forces drive this collective invasion and the required energy for this process is not well understood. Invasion of a metastatic tumor to surrounding tissues leads to a majority of cancer-associated death and is often a collective effort among cells, it is therefore important to fully understand the process behind collective cancer invasion.

The goal …

Llm-Driven Fmea For Safe Human-Robot Collaboration In Disassembly, Morteza Jalali Alenjareghi, Samira Keivanpour, Yuvin Adnarain Chinniah, Sabrina Jocelyn

Articles dans des actes de congrès

Disassembly operations often present unstructured and unpredictable scenarios, such as handling hazardous materials, addressing ergonomic strain, and managing dynamic robot interactions that pose safety risks. To tackle these challenges, we propose an innovative use of large language models (LLMs) to enhance failure mode and effect analysis (FMEA) in the context of human-robot collaboration (HRC) for disassembly tasks. We developed an LLM system leveraging retrieval-augmented generation (RAG) for real-time risk analysis and recommendation generation. RAG retrieves domain-specific information from the FMEA knowledge database, enabling accurate risk analysis, contextual understanding, and relevant recommendations based on user input and operational data. Evaluation of …

Stakeholder Perspective-Taking In Engineering Design; A Neurocognitive Approach, Megan Taylor, Yakhoub Ndiaye, Jenn Campbell

2025 Research Poster Competition

During the engineering design process, the ‘black box’ of a designer's mind determines who the stakeholders are, which stakeholder needs they are addressing and how they will address them. This process can build bias into engineering designs, leading to less equitable, accessible, and inclusive engineered artifacts. Design neurocognition, a new field that aims to determine the unknowns of a working designer’s mind, has arisen because of this uncertainty. The fNIRS (Functional Near-Infrared Spectroscopy) allows insight into the prefrontal cortex during decision making processes by analyzing the change in oxygenated blood in the surface of the prefrontal cortex, about 3 cm …

Exploring User Sentiment On Social Issues Via Neural Network Transfer Learning In Digital Communities, Ananya R. Vangoor

2025 Research Poster Competition

Understanding public sentiment on social issues is crucial for gauging the stance of the general population. Traditionally, surveys have been a common approach for this. However, to capture more candid opinions, social media provides a rich source of unadulterated opinions. By analyzing social media statements, we can gain insights into the perspectives of specific groups. More specifically, we will investigate the attitudes of the public into the relationship between hard work and success in the workplace.

To begin, I will be training a neural network on X, formerly known as Twitter, tweets to categorize each tweet as either pro-luck or …

Analyzing Unmanned Aircraft System (Uas) Incidents From Nasa Asrs Data Using Unsupervised Machine Learning, Kacey Haws, Neelakshi Majumdar

2025 Research Poster Competition

The NASA Aviation Safety Reporting System (ASRS) assembles voluntarily submitted aviation safety incident reports in their database to act on the information provided. This database allows the government, companies, and citizens to submit incident or situational reports to its database to discern recurring issues in the National Aviation System (NAS) so that the proper officials can act [1]. The narratives provided in these reports are text-based, resulting in large amounts of data to process. Previous work in the University of Arkansas Aerospace Systems Engineering and Transportation Laboratory (ASYST) lab involved parsing unmanned aircraft system (UAS) incident reports manually. While these …

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 …

Pla Polymer Binder In Core Production - Influence On Final Casting Dimensions, Artur Soroczyński, Krzysztof Rechowicz

Virginia Digital Maritime Center (VDMC) Faculty Publications

The foundry industry is seeking an ecological alternative to synthetic molding resins. This study evaluates the technological properties of core sands bonded with biodegradable polylactide (PLA). Cores prepared on a 2% quartz sand matrix were subjected to casting processes using two alloys with extremely different pouring temperatures: gray cast iron (approx. 1200 °C) and AK11 silumin (approx. 710 °C). The research methodology included macroscopic assessment, dimensional analysis using 3D scanning (GOM Inspect), and qualitative knock-out assessment supported by numerical temperature field simulation. The results showed that the high crystallization temperature of cast iron leads to complete thermal degradation of the …

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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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 …