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A Federated Learning Framework For Data-Sovereign Predictive Maintenance In Distributed Smart Manufacturing, Md Sazol Ahmmed, Sriram Praneeth Isanaka, Frank Liou May 2026

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 May 2026

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 …


Integrated Geophysical, Geotechnical, And Mineralogical Characterization Of Expansive Weches Formation Soils In East Texas: Implications For Infrastructure Design, Samuel Annobil May 2026

Integrated Geophysical, Geotechnical, And Mineralogical Characterization Of Expansive Weches Formation Soils In East Texas: Implications For Infrastructure Design, Samuel Annobil

Electronic Theses and Dissertations

This study investigates the geotechnical, geophysical, and mineralogical characteristics of soils derived from the Weches Formation in Nacogdoches County, East Texas, with emphasis on the relationships among electrical resistivity, moisture condition, compaction state, and mineralogical composition. The Weches Formation is well known for producing clay-rich, moisture-sensitive soils that pose challenges to subgrade performance because of their plasticity and swelling behavior. Representative soil samples were collected and subjected to laboratory testing, including particle size analysis, Atterberg limits, Standard Proctor compaction, free swell tests, electrical resistivity measurements, and X-ray diffraction (XRD) mineralogical analysis. The soils are predominantly fine-grained and clay-rich, with USCS …


Reward Representation Learning, Gregory M. Hyde May 2026

Reward Representation Learning, Gregory M. Hyde

Dartmouth College Ph.D Dissertations

The \emph{Markov decision process} (MDP) has long served as the canonical model for sequential decision-making. However, it assumes that the reward function is Markov with respect to a given state representation---an assumption that often does not hold in practice. Instead, agents typically only perceive streams of observations and actions and must infer the latent structure according to which reward unfolds over time. From this perspective, reward prediction is initially non-Markov, reflecting a mismatch between the agent's current representation and the underlying structure of the environment.

In this thesis, we advance the view that reward is not simply a signal to …


Board-Level Operating System Infrastructure In Rust, Lydia Klaus May 2026

Board-Level Operating System Infrastructure In Rust, Lydia Klaus

McKelvey School of Engineering Graduate Student Theses & Dissertations

Memory and multi-threading problems are the cause of many exploits and security vulnerabilities, and errors of this nature are easy to cause in programming languages such as C and C++. Despite this, these languages are still heavily used for systems programming and underpin the majority of operating system kernels. This is partially due to a lack of suitable replacements; however, Rust is becoming more prominent as an option for systems programming. This language features a much more stringent approach to memory and multi-threading safety. It also aims to support a wide range of hardware targets, including microcontrollers, which have long …


Data-Driven Multimodal Mri Representation Learning For Subtype Discovery And Disease Progression Modeling In Parkinson’S Disease, Zihan Zhou May 2026

Data-Driven Multimodal Mri Representation Learning For Subtype Discovery And Disease Progression Modeling In Parkinson’S Disease, Zihan Zhou

McKelvey School of Engineering Graduate Student Theses & Dissertations

Parkinson’s disease (PD) exhibits substantial clinical and neuroanatomical heterogeneity, limiting robust patient stratification and clinically meaningful progression modeling from MRI. We propose a unified multimodal 3D generative representation-learning framework that learns an interpretable latent space from co-registered baseline T1/T2 MRI with an edge-aware channel. Confound-corrected latent embeddings support unsupervised subtype discovery, while disease duration provides weak supervision to orient a continuous progression axis. On an independent external cohort (PPMI, N=171), the discovery-trained subtype structure shows significant partial replication (ARI=0.35; permutation test p=0.001) and enables longitudinal clinical stratification: mixed-effects modeling reveals subtype-dependent MDS-UPDRS III progression, with the strongest effect in subtype …


Analysis Of Oscillating Flow Over A 2-D Airfoil With Flow Reversal, Colter Couillard-Rodak May 2026

Analysis Of Oscillating Flow Over A 2-D Airfoil With Flow Reversal, Colter Couillard-Rodak

McKelvey School of Engineering Graduate Student Theses & Dissertations

Finite-state models are useful tools in modeling the aerodynamics of rotorcraft in flight simulators. 2-D and 3-D finite-state models have been developed and compared to closed form solutions, however these models are currently unable to handle situations where the freestream changes directions and the rotor re-enters its own wake. A 2-D finite state model was previously developed that includes a parameter that accounts for the change in free stream. This model, however, contains an inherent stability issue at the instant that the velocity changes direction.

The effects of this instability can be mitigated in certain flow conditions. A purely oscillatory …


Temporal Logic Planning In Semantic Maps Of Unknown Environments Using Tl-Rrt, Dongrui Yang May 2026

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 …


Side-To-Side Differences In Three-Dimensional Femoral Head Coverage Associated With Initial Symptom Development In Patients With Bilateral Developmental Dysplasia Of The Hip, Jiayi Sun May 2026

Side-To-Side Differences In Three-Dimensional Femoral Head Coverage Associated With Initial Symptom Development In Patients With Bilateral Developmental Dysplasia Of The Hip, Jiayi Sun

McKelvey School of Engineering Graduate Student Theses & Dissertations

Developmental dysplasia of the hip (DDH) is characterized by insufficient acetabular coverage of the femoral head and is a recognized cause of hip pain, instability, and early osteoarthritis. Although bilateral deformity is common, symptoms often first develop in only one hip. The purposes of this study were: (1) to determine whether, in patients with bilateral DDH, side-to-side differences in three-dimensional (3D) femoral head coverage vary according to radiographic symmetry defined by the lateral center-edge angle (LCEA); and (2) to determine whether hips that appear radiographically symmetric still demonstrate focal 3D asymmetry.

This retrospective imaging-based study included patients with bilateral DDH …


A Study Of Visualized Diagnostics In Early Stage Digital Twin Implementation Of An Industrial Control System, Michael R. Kinzel May 2026

A Study Of Visualized Diagnostics In Early Stage Digital Twin Implementation Of An Industrial Control System, Michael R. Kinzel

All-Inclusive List of Electronic Theses and Dissertations

Industrial Control Systems (ICS) are used for process control in almost all industries. An ICS combines Operational Technologies (OT) with Information Technologies (IT) to allow human supervision of a process through surveillance of process variables and manipulation of controlling elements such as valves to maintain stable process conditions. ICSs have been in-service for several decades and may remain operational past their technological service life. Organizational personnel interact with the ICS through visual displays that both indicate the process variables and also the controlling elements. The Human Machine Interface (HMI) allows visibility of the process and the ability to manipulate controlling …


Dirt Finder (Drtfndr): A Marketplace Application For Construction Earthwork, Evan A. Reed May 2026

Dirt Finder (Drtfndr): A Marketplace Application For Construction Earthwork, Evan A. Reed

Construction Management

The construction industry regularly produces a surplus of earthwork materials: clean fill, topsoil, gravel, and crushed concrete, that are disposed of at considerable cost. All the while, contractors actively seek those same materials, and no dedicated digital platform existed to connect these two groups efficiently. DrtFndr ("Dirt Finder") is a mobile-first web application developed to address this gap, providing a marketplace where contractors can post available or needed earthwork materials, browse geographically filtered listings by material type and proximity, and connect directly with other users. The application was built using Base44, an AI-powered application development platform, and includes real-time mapping, …


Sb 1953 Field Execution Under Hcai Oversight: Seismic Retrofit At Zsfg Building 5, Victor Lucas May 2026

Sb 1953 Field Execution Under Hcai Oversight: Seismic Retrofit At Zsfg Building 5, Victor Lucas

Construction Management

Every hospital in California must be seismically compliant by 2030 under Senate Bill 1953, which is enforced by the Department of Health Care Access and Information (HCAI). HCAI approves and inspects all hospital construction in the state, and its authority reaches into the field, so a contractor cannot simply build to an approved drawing the way it would on a commercial job. This paper explains how that approval system governs the work, written for construction professionals entering hospital work in California whose experience to that point has been commercial. It uses the ZSFG Building 5 Voluntary Seismic Upgrade, a 1976 …


Sheep Pen Improvements At City Farm Slo, Ryan S. Bodmer May 2026

Sheep Pen Improvements At City Farm Slo, Ryan S. Bodmer

Construction Management

City Farm SLO is an urban non-profit educational farm located in San Luis Obispo, CA. It serves the community through offering farm learning programs, including hands-on experience in sustainable farming practices and livestock care. This project, completed over the winter and spring quarters, focused on delivering an upgraded sheep pen to improve access and safety for both volunteers and sheep. The project consisted of developing design plans, coordination of materials and allowable working times with the owner, where the animals were either moved out of the working area or when work would not jeopardize animal health, schedule creation, cost estimates, …


An Experimental Study On Turbine-Based Energy Harvesters For Thermal Underwater Gliders, Stephen Edward Coster May 2026

An Experimental Study On Turbine-Based Energy Harvesters For Thermal Underwater Gliders, Stephen Edward Coster

Theses and Dissertations

Buoyancy-driven underwater gliders have been optimized for long-duration missions primarily for continual monitoring of the ocean’s water column. However, longer missions and higher-powered sensors have increased the energy requirements of gliders. While current solutions aim to increase battery capacity, the development of energy-harvesting systems (EHMs) could greatly improve mission capabilities in both ability and duration. This thesis discusses the experimental testing of an underwater glider with an EHM as detailed in the theoretical study, “Development of a Turbine-Based Ocean Thermal Energy Harvesting Mechanism Applied to the Underwater Glider” by Hongbo Hou, PhD. The rear-mounted turbine captures energy using the kinetic …


A New Approach To Generate Combinatorial Patterns In Logical Analysis Of Data And Its Application To Predict College Retention, Salihah Ahmed E. Jaafari May 2026

A New Approach To Generate Combinatorial Patterns In Logical Analysis Of Data And Its Application To Predict College Retention, Salihah Ahmed E. Jaafari

Theses and Dissertations

Student retention and degree completion remain central challenges for higher-education institutions, with significant implications for student success, institutional effectiveness, and public accountability. While advances in predictive analytics have enabled earlier identification of students at risk of withdrawal, many commonly used machine learning approaches suffer from limited interpretability, constraining their practical usefulness for advising, intervention, and policy decision making. This dissertation addresses the problem of predicting student persistence by developing and evaluating optimization based, interpretable classification models within the Logical Analysis of Data (LAD) framework. Building on existing LAD formulations, this research introduces two novel pattern generation models, the Best Term …


Moodify: A Mood-Based Music Recommendation System, Meghana Kagitha May 2026

Moodify: A Mood-Based Music Recommendation System, Meghana Kagitha

Theses and Dissertations

Music has long been recognised as a powerful tool for emotional regulation, yet existing music streaming platforms often fail to align song recommendations with a user's current emotional state. Moodify is a mood-based music recommendation system designed to bridge this gap by delivering personalised playlists that reflect how a user feels in real time.

This project presents the design, development, and evaluation of Moodify, a mobile application that leverages the Circumplex Model of Emotion to capture user mood through an intuitive two-dimensional valence-arousal interface. Rather than relying on text input or manual search, users plot their emotional state directly onto …


Adaptive Artificial Potential Field Guidance And Control For Autonomous Docking With Uncooperative And Unknown Spacecraft, Steven Holmberg May 2026

Adaptive Artificial Potential Field Guidance And Control For Autonomous Docking With Uncooperative And Unknown Spacecraft, Steven Holmberg

Theses and Dissertations

The increasing demand for on-orbit servicing (OOS), active debris removal (ADR), and space domain awareness (SDA) missions has increased the need for autonomous spacecraft rendezvous and proximity operations (RPO) with uncooperative and unknown targets. Traditional guidance and control methods are typically designed for cooperative systems with known geometry and state information. This work builds on previous research to develop and evaluate an artificial potential field (APF)-based control framework capable of autonomous operation with minimal prior target knowledge and applicability to both relatively static and tumbling spacecraft.

The proposed APF formulation incorporates established safety constructs from cooperative docking systems, including an …


Moon Adaptive Technology For Extraterrestrial Architectural Robotics (Matear), Candela Noemi Solis Zampini May 2026

Moon Adaptive Technology For Extraterrestrial Architectural Robotics (Matear), Candela Noemi Solis Zampini

Theses and Dissertations

The Moon Adaptive Technology for Extraterrestrial Architectural Robotics (MATEAR) focuses on the development of an autonomous robotic system capable of providing structural building blocks directly from lunar regolith. As a sustained human presence on the Moon becomes a necessity, the costly and limited payload capacity associated with transporting construction goods from Earth creates a critical challenge. MATEAR addresses this problem through in-situ resource utilization (ISRU), integrating a regolith processing system onto a remote operated vehicle. The proposed system is designed to collect lunar dust, mechanically compact the material, and apply thermal treatment to enhance cohesion through sintering. These regolith-made bricks …


A Low Power Fpga Compute Array For Machine Learning And Artificial Intelligence Applications, Todd Wilson May 2026

A Low Power Fpga Compute Array For Machine Learning And Artificial Intelligence Applications, Todd Wilson

All Graduate Theses and Dissertations, Fall 2023 to Present

Modern small satellites often lack the ability to analyze their data in real time, relying instead on downlinking raw measurements to Earth before any scientific interpretation can occur. This delay restricts missions that require rapid awareness of environmental or space-weather events. This thesis presents the Low-power Array for Cubesat Edge Computing Architecture, Algorithms, and Applications (LACE-C3A), a hardware platform designed to enable in-orbit data processing within the power and volume limits of CubeSat-class spacecraft. 

LACE-C3A uses a modular cluster of flash-based FPGAs, which offer low power consumption, radiation resilience, and in-flight reconfigurability. The system consists of a Controller board responsible …


Ionospheric Plasma Electron Density Measurement And Theory Using Impedance Probe Techniques, Justin Wellington May 2026

Ionospheric Plasma Electron Density Measurement And Theory Using Impedance Probe Techniques, Justin Wellington

All Graduate Theses and Dissertations, Fall 2023 to Present

The ionosphere plays a critical role in how radio frequency (RF) signals, like those used in Global Position System (GPS) satellite communications, travel through space. Disturbances in the ionosphere, such as equatorial plasma bubbles (EPB), scatter these signals and cause communication dropouts or navigational errors. To study these conditions, spacecraft use instruments that measure the surrounding plasma directly. One of these instruments is an impedance probe, which applies a small electrical signal to a sensor and determines electron density from the measured impedance.

This thesis improves the modeling and interpretation of impedance probe measurements. A numerical method is developed that …


Design Of A Low-Power Magneto-Inductive Magnetometer, Rowan Antonuccio May 2026

Design Of A Low-Power Magneto-Inductive Magnetometer, Rowan Antonuccio

All Graduate Theses and Dissertations, Fall 2023 to Present

Measuring magnetic fields in space helps scientists understand phenomena that can affect satellite communications and navigation systems on Earth. This research develops a new low-power magnetic field sensor for spacecraft that improves upon existing designs by moving the sensitive parts away from electrical interference and using energy-efficient digital electronics for precise measurements. The sensor’s power-efficient design is particularly important for small satellites, where power is limited and must be carefully managed. It will fly on future NASA missions to study disturbances in Earth’s upper atmosphere that can disrupt radio signals and GPS. This work contributes to our ability to better …


Relaxed Convex Approximation For Optimal Control In Cislunar Space, Jondavid K. Hertzel May 2026

Relaxed Convex Approximation For Optimal Control In Cislunar Space, Jondavid K. Hertzel

All Graduate Theses and Dissertations, Fall 2023 to Present

This thesis develops a method of optimal control for a spacecraft in the region between the Earth and the Moon known as cislunar space. The optimal control method is developed through a modern optimization technique called “convex relaxation” to achieve a formulation that can be reliably solved by numerical computation tools. The primary research objective is to evaluate the efficacy of this method in accommodating the physical thrust constraints of a spacecraft. This approach is tested in simulation with an unstable halo orbit around the Moon in the circular restricted three-body problem (CR3BP) model. The simulation incorporates realistic disruptions from …


Effects Of Subsurface-Drip-Irrigation On Alfalfa Evapotranspiration In The Intermountain West, Namuna Dhakal May 2026

Effects Of Subsurface-Drip-Irrigation On Alfalfa Evapotranspiration In The Intermountain West, Namuna Dhakal

All Graduate Theses and Dissertations, Fall 2023 to Present

Alfalfa is one of Utah’s most important crops, but it is also the largest agricultural consumer of water. Because the state faces frequent droughts and growing pressure on limited water supplies, farmers and water managers are increasingly interested in irrigation systems that could reduce water use. Subsurface drip irrigation (SDI), which delivers water directly to plant roots through buried drip lines, has shown promising results in other regions, where it often reduces water consumption and increases yield. However, little research has evaluated SDI under Utah’s unique climate, soils, and high-elevation valleys.

This study compared an SDI system with a traditional …


Two Applications Of Lifting-Line Theory For The Design Of Efficient Aircraft, Amanda K. Olsen May 2026

Two Applications Of Lifting-Line Theory For The Design Of Efficient Aircraft, Amanda K. Olsen

All Graduate Theses and Dissertations, Fall 2023 to Present

Numerical lifting-line is a tool that can be used to evaluate the forces and moments of an aircraft wing. This method has limitations but it is beneficial in obtaining a large set of results with relatively little computational power. This research seeks to analyze two different flight scenarios through the use of two numerical lifting-line tools developed at the Utah State University AeroLab. The first scenario involves an aircraft in ground effect flight. When an aircraft flies close to the ground, a phenomenon called ground effect occurs where the lift is increased and the induced drag is decreased. Therefore, flying …


Developing And Improving Digital Image Correlation (Dic) Techniques For Challenging Environments, Prasenjit Dewanjee May 2026

Developing And Improving Digital Image Correlation (Dic) Techniques For Challenging Environments, Prasenjit Dewanjee

All Graduate Theses and Dissertations, Fall 2023 to Present

Understanding how materials and parts deform during testing is crucial for creating safer and more reliable engineering systems. Engineers need to measure not only how much a part deforms, but also where deformation concentrates before any damage or failure happens. Digital image correlation (DIC) is a camera-based, non-contact measurement method that tracks surface motion and deformation across a whole area. It is particularly useful when traditional contact-based measurement techniques cannot withstand harsh conditions or capture enough detail. This dissertation develops optical methods to improve DIC in three challenging measurement situations. First, a shortwave ultraviolet lighting technique is developed to reduce …


A Low-Cost Motion Classification System For A Stuffed Animal Using An Imu And Machine Learning, Rachel N. Guynes Apr 2026

A Low-Cost Motion Classification System For A Stuffed Animal Using An Imu And Machine Learning, Rachel N. Guynes

Honors Theses

One of the many fields that has seen the integration of robots is therapy. Zoomorphic robots (ZR) are designed to look and behave like animals to assist in Animal Assisted Therapy (AAT) practices. Studies show that ZRs can provide benefits similar to working with an actual animal; however, their high cost limits their accessibility. This thesis documents the process of building a real-time, low-cost motion classification system that can be attached to a stuffed animal to make it more interactive. Using a Random Forest (RF) classifier, the system identifies movements with approximately 81.67% accuracy.


Quantitative Fluorescence Imaging Using A Paired Agent Approach For Improving Surgical Decision Making, Sanjana Pannem Apr 2026

Quantitative Fluorescence Imaging Using A Paired Agent Approach For Improving Surgical Decision Making, Sanjana Pannem

Dartmouth College Ph.D Dissertations

Surgical resection remains to be the cornerstone of treatment for most solid tumors, where the primary objective is to remove all visible and microscopic disease. However, the extent of tumor resection is inherently limited by the surgeon’s ability to distinguish tumor from normal tissue, intraoperatively. As a result, positive surgical margins (PSM), where residual tumor remains after surgery, are a common occurrence and are associated with increased recurrence, need for adjuvant therapies, dismal patient outcomes, and high healthcare costs.

Fluorescence guided surgery (FGS) has emerged as a promising technique to enhance intraoperative visualization of tumors and may help reduce the …


Picc-Pal: A Support Band For Independent Picc Line Use, Kylie Luker Apr 2026

Picc-Pal: A Support Band For Independent Picc Line Use, Kylie Luker

Honors Theses

This project presents the design and evaluation of PICC-PAL, a wearable assistive device intended to improve independence and usability for patients managing peripherally inserted central catheters (PICC lines) at home. Current at-home PICC line management often requires help due to the fine motor skills needed to connect and secure tubing. This increases reliance on caregivers and introduces potential risks such as infection and dislodgement. Through stakeholder analysis, prior art evaluation, and iterative prototyping, a device was developed to stabilize the PICC line lumen and enable one-handed connection of medical tubing. Throughout the project, multiple design concepts were explored, with the …


Increasing The Prediction Accuracy Of Plant Oil Production Processes Through Adjusting The Parameters Of Machine Learning Models, Umidjon Ruziev, M.K. Shodiev, A.T. Rajabov Apr 2026

Increasing The Prediction Accuracy Of Plant Oil Production Processes Through Adjusting The Parameters Of Machine Learning Models, Umidjon Ruziev, M.K. Shodiev, A.T. Rajabov

Chemical Technology, Control and Management

Vegetable oil production is characterized by high variability in output indicators due to nonlinear interactions between raw material parameters, equipment modes, and heat and mass transfer conditions. Existing approaches to applying machine learning in this field, as a rule, do not account for the impact of hyperparameter adjustments on forecasting quality across specific technological stages. The article presents a systematic methodology for adjusting model parameters (Ridge regression, SVR, GBM, LSTM) applied to three key tasks: predicting residual oil content in oil cake, color index during bleaching, and free fatty acid content during deodorization. In a set of 1000 observations, including …


Rdm Interval Arithmetic Based Weapon System Evaluation, Konul Imran Jabbarova Phd Apr 2026

Rdm Interval Arithmetic Based Weapon System Evaluation, Konul Imran Jabbarova Phd

Chemical Technology, Control and Management

For solving this issue, the paper considers a hierarchical multi-criteria decision-making problem, where the choice of a company that corresponds best to the criteria is required. Data used in this problem are presented in the form of intervals, which makes it possible to cope with uncertainty in the problem solution. Several companies working in missile production industry are chosen as alternatives for analysis. Evaluation of the selected alternatives is made based on five criteria clusters. More than twenty criteria are taken into account during evaluation.

Solving this problem is achieved with the help of the technique based on computation of …