Engineering Commons^™

Murray Grading Method: Impacts On Student Self-Efficacy, Stephanie E. Handford

Honors Theses

Pre-existing assessment methods in engineering lack the ability to ensure student mastery of material, simulate real world situations, and often have ambiguity in the valuation of grades. The goal of this study is to eliminate or reduce those shortcomings by evaluating the effectiveness of a modified no-partial-credit assessment method, the Murray Grading Method. Historical data alongside an introductory statics course cohort provided data for how the Murray Grading Method impacted student grades, course opinion, self-efficacy, and study methods. The Murray Grading Method demonstrated little to no changes in course grade averages while significantly improving the lowest grades, thus increasing the …

Civil Engineering Capstone Building Design And Seismic Analysis, Ander P. Mcdade

Honors Theses

The building for the University of Mississippi civil engineering senior design class was designed and analyzed. The building is in Oxford Mississippi. The current address according to the Lafayette Parcel is 825 Sisk Avenue Suite 200. The floor plan, column, and beam design were performed based on engineering judgment and industry standards. The dead, live, snow, rain, and roof live loads were calculated to be 13.3, 50, 20, 27.51, and 20 psf respectively. The building model was created in SAP2000, which was used to generate all loads and load combinations. An analysis was performed to determine the critical loads on …

American Football Internal Helmet Padding Material And Design Testing, Spencer J. Pigman

Honors Thesis

Football helmets have evolved significantly to improve player safety and reduce the risk of concussions and traumatic brain injuries. Early leather designs offered minimal protection, while modern helmets use advanced materials to absorb and distribute impact forces more effectively. To support ongoing helmet safety research, a custom 3D-printed headform modeled from a human scan was equipped with a WitMotion BWT901BLECL5.0 accelerometer and used in controlled drop tests. The study evaluated various internal padding materials including spray foam, two sizes of bubble wrap, Oobleck, scrub sponges, KTOESHEO foam, Hijelyn air pillows, and the standard padding from a Riddell Victor youth helmet. …

Direct Computations Of Spatially Resolved Viscoelastic Moduli Of Biomolecular Condensates, Liwen Gu

McKelvey School of Engineering Graduate Student Theses & Dissertations

Biomolecular condensates are viscoelastic materials formed by liquid-liquid phase separations (LLPS) of biopolymers. In this study, we develop a modified graph Laplacian-based collective model to characterize viscoelastic heterogeneity within condensates based on results of lattice-based Metropolis Monte Carlo (MMC) simulations. By integrating random graph models and simulations of A1-LCD, a type of intrinsically disordered protein, we examine how network topology influences storage modulus, loss modulus, crossover frequency, and relaxation time spectra. Our results reveal a strong correlation between topological features and mechanical response, with the condensate interior exhibiting higher stiffness and faster relaxation than the interface. The relaxation spectra provide …

Computational Models Of Vocal Fold Lesions: Analysis Of Fluid-Structure Interaction, Manoela Rocha Neves

Electronic Theses and Dissertations

The biomechanical and aerodynamic behaviors of the vocal folds (VFs) during phonation are heavily influenced by their structural composition and pathological changes. These conditions can induce localized stiffening that disrupts vibratory symmetry and alters airflow resistance. Previous research has lacked the integration of VF lesions in computational simulations using anatomically accurate models, limiting the understanding of their effects in phonation and potential contribution to voice disorders. Addressing this gap, this thesis develops a fluid-structure interaction (FSI) model of a realistic two-layered VF structure with lesions, comparing airflow patterns, structural deformations, and vibration profiles in both healthy and diseased cases.

The …

Alterations And Improvements Of The Photoacoustic Flow Cytometry Method, Nicholas J. Taylor

Electronic Theses and Dissertations

The emergence and proliferation of antibiotic-resistant bacteria present a significant and growing challenge to global public health, with the potential to render many existing antibiotics ineffective. Infections caused by these resistant pathogens are difficult to treat, resulting in higher morbidity, mortality, and healthcare costs. A major obstacle in combating these infections is the slow pace of traditional diagnostic methods, such as blood cultures, which typically take 2-3 days to identify the causative bacteria and determine their antibiotic resistance profiles. This delay in diagnosis hinders timely interventions and appropriate treatment, further contributing to the spread of resistant infections. As such, there …

The Effects Of Flood Irrigation Vs. Pivot Irrigation On Groundwater Recharge, Tea Rainey

Graduate Theses & Non-Theses

Groundwater can be an important resource for river flow support, and this is especially true with the Big Hole River in southwestern Montana which is mainly fed by groundwater late in the summer season. Maintaining the source of groundwater is an important focus both for the Big Hole River Watershed Committee as well as local ranchers. Agriculture uses large quantities of water, and as technology advances many ranchers are turning to the use of pivot lines for irrigation. Historically, flood irrigation was used when surface water was available. Surface water sources include tributary streams as well as diversions from the …

Snowmelt Runoff Driven Hydropower Modelling Based On Spaceborne Remotely Sensed And Ground Weather Network Data, Ninad Bhagwat

Graduate Theses & Non-Theses

Identification of new optimal hydropower locations provides an opportunity to improve mankind's green energy portfolio by developing new hydroelectric plants, thereby decreasing the carbon footprint. Preliminary analysis of locating the optimal hydropower sites is generally the first step towards construction of a new hydropower plant. In this dissertation, I developed a parsimonious, yet robust tool to perform the preliminary analysis to locate optimal hydropower locations in any watershed using the remotely sensed Digital Elevation Model (DEM). Simulating the snowmelt-derived streamflow is crucial for water resources management in snow-dominated watersheds. The Snowmelt Runoff Model (SRM) is a lumped-parameter, temperature-index model that …

Experiments And Modeling Of Pmu Under Gps Spoofing Attacks, Joshua Afosa-Baffoe

Graduate Theses & Non-Theses

Phasor Measurement Units (PMUs) require an accurate timing signal, which is generally broadcast once per second and communicated to the PMU. While other timing protocols exist, internal clock actively synchronized to GPS time. This GPS dependence creates a potential cybersecurity vulnerability that requires attention. In this thesis, two critical aspects of GPS Spoofing Attacks (GSAs) were investigated. First, laboratory experiments on how a commercial PMU, compliant with the IEEE C37.118 standard, responds to a variety of GSAs. This work examines the ability of PMUs to detect certain spoofing attacks, highlighting cases where detection fails. The characteristic signature of the PMU …

Fenitization Of Mafic Wallrock Associated With Emplacement Of Ree-Rich Carbonatites Of Sheep Creek, Southern Ravalli County, Montana, Tage Young

Graduate Theses & Non-Theses

The Sheep Creek area of southern Ravalli County, Montana, contains numerous small, carbonatite-related deposits rich in niobium (Nb) and rare earth elements (REE). The carbonatite bodies are typically < 2 m wide, strike northeast or east, and dip moderately to steeply to the north. The carbonatites are locally deformed, and are conformable to foliation in the host rocks. The host rocks belong to a 1.37 Ga, bimodal, metaigneous complex consisting of granite/augen gneiss and diabase/amphibolite. When found in close proximity to a mineralized carbonatite body, the mafic wall rock is altered to a fenite assemblage that includes phlogopite, albite or Na-rich plagioclase, calcite ± dolomite, magnetite, and sodic amphiboles (riebeckite, winchite). The mineral transformations are consistent with observed changes in the bulk chemistry of the mafic wall rocks, including consistent increases in K2O, Na2O, and H2O/CO2 and consistent decreases in SiO2 and Al2O3. Relatively minor changes in FeO and MgO were found to take place during the fenitization process. Fenite alteration is most strongly developed adjacent to carbonatites that are strongly mineralized with Nb-REE minerals. Unmineralized carbonatites have fenite zones that are weak or absent. Although the fenites themselves are not strongly enriched in REE, transfer of SiO2 and Al2O3 from the fenites back into the carbonatite bodies may have triggered deposition of REE-rich allanite and other silicate minerals (Ba-feldspar, actinolite, quartz) that are locally abundant in the carbonate lodes. An influx of silica may also have lowered the solubility of REE-phosphate in the carbonatite melts, resulting in deposition of monazite. Most fenites that have been described in previous studies around the world formed by alteration of felsic country rock (granite, gneiss, siliciclastic metasediments). These fenites are rich in alkali feldspar and aegirine, and form conspicuous, pink-colored outcrops that surround the central carbonatite complex. Because the country rock in the Sheep Creek area has a mafic starting composition, the fenites in this study have a completely different mineralogy, being rich in biotite, albite, and matrix calcite. These fenites erode to a crumbly grus soil, do not crop out well, and are therefore easy to miss or ignore in the field. However, recognition of these rocks is important because they are vectors to a nearby mineralized carbonatite.

Designing And Mcat Study App That Updates Automatically And Includes A Novel Goal Of Optomizing A User's Mental Health, Richard Vasquez

Graduate Theses & Non-Theses

This project investigates the multifaceted role of heart rate variability (HRV) as both a physiological and cognitive marker of human performance, with particular emphasis on its implications for academic preparation and decision- making. Drawing from recent literature, I examine the influence of exercise, sleep quality, stress management, and slow-paced breathing on HRV, highlighting its predictive value for executive function, emotional regulation, and adaptive decision-making. Additionally, the paper introduces a conceptual framework for an educational application that leverages HRV monitoring and breathing interventions such as, resonance breathing to enhance study effectiveness. Additionally, the application will feature a supplemental website to reinforce …

The Crystal Mountain Fluorite Deposit: Scandium-Rich Mineralization And Geochronology, Natalie Kilanowski-Doroh

Graduate Theses & Non-Theses

The Crystal Mountain fluorite mine is located in the Sapphire Mountains of the Bitterroot National Forest, near Darby, Montana. Crystal Mountain was a significant US producer of high-purity fluorspar between 1952 and 1972. As well, the deposit is rich in yttrium (Y) and scandium (Sc), and could possibly be a domestic source of these critical metals. The ore occurred as lodes of massive fluorite up to 10 m thick and 100 m long (now mined out), with few other associated minerals. Recent studies have speculated that Crystal Mountain may be a rare example of a magmatic fluorspar deposit. The main …

Development Of Predictive Maintenance For Centrifugal Pumps, Elliot B. Lange

Honors Capstones

Over prolonged periods of time, mechanical machinery requires regular maintenance to ensure optimal performance. Conventionally this maintenance is done on a regular schedule with predefined procedures to repair all aspects of the machine. As machine learning models become more applicable in everyday life, these algorithms can be leveraged to predict failures in mechanical devices. This project worked toward creating a predictive maintenance machine learning model for centrifugal pumps that can identify and predict discrete failure modes. As a result of the project, a pump loop setup was constructed. The purpose of this report is to provide a guide for how …

Design And Development Of A Stethoscope Attachment For Instant Heart Murmur Detection, Caitlin K. Cherwin, Dillon Desai

Honors Theses

Heart murmurs are critical indicators of potential cardiovascular conditions yet their detection can often go unnoticed due limitations in equipment and is dependent on clinician experience. Cardiovascular disease remains a leading cause of death worldwide, therefore, early detection of heart murmurs play a crucial role in improving patient outcomes. Many established methods of detection are expensive and often unreliable allowing there to be room for a device which is more cost and result effective. This paper presents the development of a device that attaches onto a regular stethoscope and analyzes auscultatory sounds to diagnose the possibility of a present murmur. …

Training Safety Control Filters Using High-Dimensional And Un-Labeled Data, Yuxuan Yang

McKelvey School of Engineering Graduate Student Theses & Dissertations

Synthesizing control policies that preserve the safety of autonomous systems is a challenge that remains to be solved. Towards that goal, control barrier functions (CBFs) have been developed as mathematical constructs that can be used in real-time to correct safety-violating nominal actions to ones which preserve the safety of control systems. However, synthesizing CBFs using correct-by-construction methods has not been scalable. Instead, recent research has proposed data-driven approaches for learning CBFs in the form of neural networks. Two main challenges face such approaches: (1) labeling states as unsafe or safe ones requires the knowledge of the states in the backward …

New Signal Identification Algorithms For Enhanced Gamma-Ray Burst Detection In The Advanced Particle-Astrophysics Telescope, Longhao Huang

McKelvey School of Engineering Graduate Student Theses & Dissertations

This work presents a series of algorithmic advancements aimed at improving photon signal identification and gamma-ray burst (GRB) source localization for the Advanced Particle-astrophysics Telescope (APT) and its Antarctic Demonstrator (ADAPT). These advancements are aimed at identifying valid signals in noisy environments. Previous methods failed to effectively distinguish real photon signals from noise, prompting us to develop a new photon detection algorithm with peak counting. Instead of integrating all waveform data in the observation window, we use multiple thresholds to accurately identify single-photon and two-photon arrival events, minimizing false counts due to amplifier noise. The new peak count algorithm also …

Adaptive Noise Estimation And Denoising With Deep Learning For Nmr Spectroscopy, Naveen Asokan

McKelvey School of Engineering Graduate Student Theses & Dissertations

Nuclear Magnetic Resonance (NMR) spectroscopy is a powerful analytical technique widely used for molecular structure elucidation in chemistry, biology, and medicine. However, spectral accuracy is often degraded by noise—particularly in low acquisition time settings—resulting in reduced resolution and obscured chemical features. While traditional noise reduction techniques such as signal averaging can improve spectral quality, they require longer acquisition times, limiting their utility in real-time and high-throughput applications.

This thesis presents a deep learning-based denoising framework designed to enhance the quality of complex-valued NMR spectra. The proposed model, built upon a U-Net architecture, incorporates both real and imaginary components of the …

Soft, Adhesive Dry Electrodes For Improved Electrophysiological Signal Acquisition With Motion Tolerance And Long-Term-Recoverability, Ryan Andersen

McKelvey School of Engineering Graduate Student Theses & Dissertations

Soft electronic devices and sensors have seen substantial interest devoted to them for the purpose of recording and analyzing various electrophysiological signals including for the use of electrocardiography (ECG), electromyography (EMG), and electroencephalography (EEG). Dry electrodes specifically have enormous potential compared to traditional commercial electrodes for long-term, real-time monitoring of biopotential activity. Gel-based commercial electrodes have notable drawbacks such as limited flexibility, skin irritation that decreases comfort, inconsistent signal quality due to poor conformal contact, and degraded signal quality over long-term monitoring due to drying out.

Herein, we report a soft, adhesive dry electrode that utilizes chemical additives to promote …

Strategic Reactor Allocation For Deadlock-Free Execution, Jeevan Sivamohan

McKelvey School of Engineering Graduate Student Theses & Dissertations

As it becomes harder to increase the computation power of a single machine, we are turning towards parallel and distributed systems to extract additional performance by breaking down the problem into pieces and solving it simultaneously. While this provides a great opportunity for increased performance,e it comes with additional problems not present in the sequential approach. One such problem is deadlock. Deadlock is defined as the state in which program execution stalls because the system has run out of resources to manage and execute the program properly, or there exists some circular dependency in the data between parallel or distributed …

Generic Fpga Preprocessing For Astrophysics Instruments In Hls, Qinzhou Song

McKelvey School of Engineering Graduate Student Theses & Dissertations

FPGAs are widely deployed on high-energy astroparticle physics instruments to preprocess large volumes of streaming data from various sensors. Increasingly, these deployments are finding their way to space-borne instruments, where constraints on size, weight, and power (SWaP) require careful balancing of speed and resource utilization. Although telescope designs vary widely, they often share common preprocessing elements, including channel-level readout, pedestal subtraction, waveform integration, and zero suppression from front-end ADCs, as well as identification and centroiding of signal islands across groups of multiple channels. High-Level Synthesis (HLS) tools allow these designs to be expressed at a conceptual level, which automates a …

Facilitating Design Of Effective, Scalable Digital Mental Health Care, Himanshu Mahesh Patil

Dartmouth College Master’s Theses

This thesis tackles the challenges of designing effective, scalable digital mental health care solutions by integrating psychological research with human-computer interaction (HCI) principles. An exploration of self-care technologies (SCTs) for mental health is conducted to highlight challenges to comparative analysis, like fragmented research outcomes. Two research questions are posed to investigate how mental health interventions can be designed to be effective and overcome practical challenges to implementation. A theoretical framework in clinical psychology is adapted to bridge the gap between psychology and HCI. A methodology for conducting standardized, structured comparative analysis of mental health interventions is identified. The identified method …

Learning-Based Mri Reconstruction Method With Coil Sensitivity Estimation And Prior Adaptation, Haoyu Zhang

McKelvey School of Engineering Graduate Student Theses & Dissertations

Magnetic Resonance Imaging (MRI) reconstruction from undersampled multi-coil k-space data is a challenging inverse problem, typically relying on fixed priors such as precom puted coil sensitivity maps. To improve adaptability, we propose a novel framework named Learning-based Coil sensitivity Estimation and Prior Adaptation (LCEPA). LCEPA formu lates reconstruction as a bilevel optimization, using a Joint Deep Equilibrium (Joint DEQ) model in the inner loop to simultaneously estimate images and coil sensitivity maps, while the outer loop adaptively fine-tunes image and coil priors using supervised data. Experiments demonstrate that LCEPA surpasses state-of-the-art methods in terms of PSNR and SSIM, showcasing robust …

The Role Of Piezo1 In Mediating Chondrocyte Cell Signaling And Senescence, Sophie Gretler Paradi

McKelvey School of Engineering Graduate Student Theses & Dissertations

Osteoarthritis (OA), the leading cause of disability, is driven by articular cartilage degeneration and inflammation. Mechanosensitive ion channels PIEZO1 and PIEZO2 have been implicated in OA progression via calcium signaling in chondrocytes. This study investigates the role of conditional Piezo channel knockout (cKO) in modulating calcium signaling and senescence in OA, particularly under the supra-physiologic inflammatory condition of a high-fat diet (HFD). Using calcium imaging, we found that Piezo1 cKO and dual Piezo1/2 cKO significantly reduced Yoda1-induced calcium signaling, while Piezo2 cKO alone had no effect. Under HFD conditions, Piezo1 cKO showed a non-significant trend toward reduced calcium influx, potentially …

Structural Controllability For Switched Linear Ensemble Systems, Yi Li

McKelvey School of Engineering Graduate Student Theses & Dissertations

No abstract provided.

Partially Supervised Reinforcement Learning For Gps-Denied Navigation, Ethan Weilheimer

McKelvey School of Engineering Graduate Student Theses & Dissertations

Navigating dynamic environments is a key challenge for autonomous agents, yet most existing research focuses on 3D settings or settings where the agent has full access to relevant semantics. In this work, we propose a learning framework for aerial navigation in the presence of changing dynamics and limited positional information. Specifically, we consider a drone navigation task where a drone at one time has access to GPS location information, which it has now lost and needs to navigate in the same area but at a future time with no GPS signal and differing transition dynamics. To address this, we introduce …

Automated Beam Stitching And Segmentation Procedure For Space Division Multiplexing Optical Coherence Tomography Angiography, Andrew J. Song

McKelvey School of Engineering Graduate Student Theses & Dissertations

Optical Coherence Tomography Angiography (OCTA) has revolutionized ophthalmic imaging and its capability to produce high-resolution 3D maps of the retinal microvasculature is instrumental in diagnosing retinovascular diseases such as diabetic retinopathy and age-related macular degeneration; However, the existing OCTA devices often suffer from slow acquisition speed limiting the field-of-view (FOV) in the clinic. Space Division Multiplexing OCTA (SDM-OCTA) address these limitations by acquiring multiple beams simultaneously, achieving manyfold faster acquisition speeds than single beam OCTA systems. But as each beam contains only part of the image, SDM-OCTA requires additional processing steps to produce coherent wide-field images. Though manual stitching and …

Functional Devices Based On Freestanding 2d Materials, Shijue Xu

McKelvey School of Engineering Graduate Student Theses & Dissertations

Two-dimensional (2D) materials have attracted extensive attention in the field of nanoelectronics due to their atomic-scale thickness, high surface-to-volume ratio, tunable electronic properties, and compatibility with low-temperature processing. These characteristics make them highly suitable for the construction of emerging device architectures, particularly in both ionic and electronic devices.

In this work, we investigate the application of 2D materials in two distinct classes of devices: ionically-driven memristors and electronically-dominated metal–semiconductor contacts. For the memristor study, we fabricate heterostructure-based resistive switching devices using h-BN and WSe₂ as active layers. These 2D material-based memristors exhibit stable power consumption loops and high linearity …

Comparative Analysis Of Intrinsic Reward-Based Reinforcement Learning Algorithms, Chengyu Li

McKelvey School of Engineering Graduate Student Theses & Dissertations

Reinforcement learning agents often struggle in tasks with sparse or delayed rewards, since they receive little guidance about which actions to pursue. This thesis investigates how adding intrinsic rewards can help address that issue. We focus on three main methods: Count-Based bonuses, where states are hashed and infrequent states receive higher rewards; Random Network Distillation (RND), where a predictor network learns to match the output of a fixed random target; and the Intrinsic Curiosity Module (ICM), which uses an inverse and a forward model to highlight transitions the agent cannot yet predict.

We implement these approaches under a single Proximal …

A Proposed Metals Recovery Assessment Protocol To Evaluate Mine Waste For Critical Minerals And Rare Earth Recovery Prior To Site Remediation, Claire Mbia

Graduate Theses & Non-Theses

The Metals Recovery Assessment (MRA) protocol involves collecting and evaluating information to assess the possibility for recovery of critical or rare earth minerals at mine sites to offset remediation or redevelopment costs associated with land reuse at Superfund or closed mine sites. This protocol provides a tool to implement metals recovery in conjunction with property reuse, and may involve a review of available records, visual inspections of the site, sample collection and discussions with local government officials and community members. The selection for metals recovery would be intended to both achieve metals reduction which may be required for the protection …

Unraveling The Impact Of Vessel Geometry In Resonant Acoustic Mixing, Jefferson Guthrie

Graduate Theses & Non-Theses

This study aimed to advance the understanding of ResonantAcoustic® Mixing (RAM) and its application in industrial powder processing. RAM, which consists of vertically oscillating boundaries operating at nominally 60 Hz with accelerations up to 100 g’s, is particularly effective for mixing fine powders and materials. RAM is able to complete mixing processes 10 to 100 times faster than traditional methods without the risk of cross contamination. Despite RAM’s growing potential, the underlying mechanisms of RAM are not fully understood, limiting its optimization and broader adoption. Research in this study sought to bridge existing gaps in understanding by investigating the influence …