Engineering Commons^™

Elevate Hardcase, Caleb J. Bailey, Colby M. Cordoba, Marissa Mccleod, Shaan Sandhu

Mechanical Engineering

The Elevate Hardcase project developed a portable mechanical elevation system that allows users to access rugged hard cases at a comfortable working height without needing a separate table or placing the case on uneven ground. The design focuses on improving ergonomics, portability, stability, and quick setup for users in field environments such as photography, hunting, and maintenance. Through customer research, concept development, prototyping, analysis, and testing, the final system was designed to support a loaded hard case, provide height adjustability, remain stable on uneven terrain, and be deployed by a single user in under five minutes. The final prototype demonstrates …

Design And Production Of A Carbon Fiber Longboard, John R. Beebe, Jacob Williams, Julia Stradinger, Vince Fitchtel, Jordan Cochran

Honors Theses

This thesis contains an overview of the design, prototyping, and manufacturing of a carbon fiber long board. The purpose of this capstone was to create a viable product for the real-world market and then determine how to manufacture it at scale with sustainable financial practices. In order to accomplish this task, engineering, accounting, and manufacturing challenges had to be overcome throughout all stages. The production process involved the carbon fiber layup, baking, water jet cutting, and assembly of the carbon fiber longboard. In order to optimize this process, continuous improvement and lean manufacturing problem solving techniques were applied. After a …

What Types Of Uncertainty Emerge In Instructional Aviation Incidents?, Abigail Henson

Mechanical Engineering Undergraduate Honors Theses

This study utilized narrative reports from the National Aeronautics and Space Administration (NASA) Aviation Safety Reporting System (ASRS) database to examine the types of uncertainty present in near-miss instructional aviation incidents occurring within the United States between 2015 and 2025. The final dataset consisted of 86 reports, with each report containing a set of narrative accounts from both the student pilot and the flight instructor operating under Part 91 regulations. Each instructional event was classified using a combined framework incorporating uncertainty categorizations and the Human Factors Analysis and Classification System (HFACS). Results indicate that epistemological uncertainty was the most common …

A Maximum Energy Release Rate Computational Framework For Fatigue Crack Trajectory And Life Prediction Under Mixed-Mode Proportional And Nonproportional Loading, Nahla Helmy Matar

Theses and Dissertations

The problem of mixed-mode fatigue crack growth has been a persistent research challenge. The determination of fatigue crack propagation direction directly impacts the safety and integrity of components and structures, making it crucial in various industrial applications, including welded drilling pipes, aerospace, and automotive engineering. Unlike uniaxial loading, mixed-mode cracks tend to change direction frequently (kinking), and nonproportional loading adds to the complexity of the problem. This research aims to estimate the crack propagation direction and fatigue crack life in linear elastic materials subjected to mixed-mode (I+II) loading conditions under proportional or non-proportional cyclic loading. Numerical software was developed based …

Simulation-Based Assessment Of Operational And Retrofit Solutions For Effluent Compliance Of A Capacity-Limited Oxidation Ditch Wwtp, Ahmed Sameh Harash

Theses and Dissertations

Oxidation-ditch wastewater treatment plants (WWTPs) across Egypt's Nile Delta are increasingly carrying hydraulic and organic loads beyond what they were designed for. This work can be considered pioneering as this work compared operational and structural retrofit alternatives for such a plant within a single verified simulation framework. The present study fills that gap by building a digital twin of the Qaha WWTP, a dual-train Carrousel oxidation ditch in Qalyubia Governorate, calibrated to a baseline flow of 7,420 m³/day in the SUMO24 platform (a third-generation, open-source wastewater treatment process simulation software) using the SUMO2c biokinetic model (a simplified variant of Activated …

Dynamic Baseline Schedule Updates Using Digital Twinning: A Case Study On Aluminum Formwork Construction, Ahmed Hamdi Sweilam

Theses and Dissertations

Repetitive high-rise construction using aluminum formwork couples consecutive floor cycles through a reused panel set and a floor-level inspection and pour barrier, so productivity loss compounds upward rather than being absorbed locally. The baseline schedule is nevertheless fixed before execution and is not revised as evidence of realized productivity accumulates. This thesis develops a simulation-based digital twin that updates the baseline from observed as-built durations and acts on its own forecast. A discrete-event simulation of a ten-story residential tower is built in AnyLogic® and verified analytically at 180.00 hours per floor. After each completed floor the twin infers activity productivity …

Sustainable – Low-Cost - Upgrade Of Activated Sludge Process For Nitrogen And Phosphorus (N&P) Removal From Wastewater, Abanoub N. Basta

Theses and Dissertations

Many municipal wastewater treatment plants (WWTPs) in developing countries were designed primarily for organic matter and suspended solids removal and therefore face increasing difficulty in meeting modern nitrogen (N) and phosphorus (P) discharge requirements. Conventional biological nutrient removal upgrades commonly require additional reactor volume, recirculation systems, aeration energy, and capital investment. Accordingly, sustainable retrofit strategies that improve nutrient removal within existing treatment footprints are increasingly needed, particularly in water-scarce and land-constrained regions.

This study investigated the integration of water hyacinth (Eichhornia crassipes) into the aeration stage of an activated sludge process as a hybrid nature-based enhancement for nitrogen and phosphorus …

A Comparative Study: Force Majeure And The Theory Of Unforeseen Circumstances Across Different Jurisdictions In The Middle East, Omar Hamed Sawan

Theses and Dissertations

The motivation behind this study stems from recent global disruption events that impact construction projects worldwide. These events vary across a wide spectrum, whether they are political events such as the Russo-Ukraine war or the war in the Middle East, economic events such as inflation or currency devaluations; or environmental events such as climate change and the emergence of public health crises like the Covid-19 pandemic. These series of events underscore the growing importance of understanding how the different legal frameworks address unforeseeable events in the construction industry. In this context, force majeure and the theory of unforeseen circumstances (also …

Deep Brain Stimulation In Early-Stage Alzheimer's Disease: A Systematic Review Of Neuropsychological Outcomes, Nora Huey

Doctoral Dissertations

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decline, memory impairment, and disruption of neural networks involved in cognitive functioning. Although existing treatments may provide symptomatic benefit, there remains a need for interventions capable of slowing or stabilizing disease progression. Deep brain stimulation (DBS) has emerged as a potential neuromodulatory intervention for early-stage AD through stimulation of memory- and cognition-related neural circuitry. This dissertation employed a systematic review research methodology to examine teh neuropsychological and neurobiological outcomes associated with DBS targeting the fornix (DBS-f) and nucleus basalis of Meynert (DBS-NBM) in individuals with early-stage AD over 12–24 …

Power At Sea Develop Phase, Jake Lauer, Isabella Heinemann, Bailey Gargasz, Zachery Boyer

Mechanical Engineering

This project develops a renewable, wave-powered charging system designed to extend the mission duration of Autonomous Underwater Vehicles by eliminating the need for frequent manual battery replacement. Building upon a prior oscillating water column prototype from the CONCEPT phase, the team redesigned and tested an improved system capable of converting wave-induced air motion into electrical power using a Wells turbine. Key enhancements include doubling the column diameter to increase displaced air volume, integrating a flared inlet and bi-directional nozzle to improve airflow, and selecting corrosion-resistant materials suitable for long-term deployment in marine environments. Multiple prototypes were constructed and evaluated through …

Extending Geometric Acoustic Ray Tracing To Multi-Room Environments: A Case Study On Gunshot Sound Transmission Between Adjacent Rooms, Tyler Ton

Theses and Dissertations

Accurate localization of gunshots in multi-room building environments remains a challenging problem in acoustic forensics and public safety applications. Existing approaches model sound propagation within a single room, neglecting the transmission of acoustic energy through walls and other building materials. This thesis presents a study on modeling multi-room gunshot acoustic transmission, combining geometric ray tracing with structural acoustic transmission-loss modeling to generate impulse responses for two horizontally adjacent rooms separated by a shared wall, providing a foundation for future inter-room gunshot localization work. The proposed system uses GSound-SIR, a geometric acoustics engine, to simulate sound propagation in both of the …

Comparative Performance Of Physiological Vital-Sign Forecasting Under Random And Patient-Wise Splitting Using Deep Learning, Lavanya Vasavi Chittem Reddy

Theses and Dissertations

Physiological vital-sign forecasting estimates future measurements based on recent temporal patterns and can support analysis of continuously recorded monitoring data. This study comparatively evaluated deep feedforward, recurrent, bidirectional recurrent, long short-term memory, and bidirectional long short-term memory architectures for one-step-ahead forecasting of peripheral oxygen saturation, heart rate, and pulse rate. Each model received consecutive observations of peripheral oxygen saturation, heart rate, pulse rate, respiratory rate, and age, while separate single-output models predicted the next value of the selected target.

Random and patient-wise data splitting were compared using identical input definitions, preprocessing procedures, model architectures, and training hyperparameters. The strongest architecture …

A Data-Driven Koopman Framework For Station-Keeping On Near Rectilinear Halo Orbit, Anusha Sharma Malladi

Theses and Dissertations

Cislunar missions have gained significant attention in recent decades, motivating the need for efficient modeling and reliable control. In this work a Koopman operator based framework is developed for approximating the error dynamics around a reference Near Rectilinear Halo Orbit (NRHO) in the Earth-Moon Circular Restricted Three-Body Problem (CR3BP). A decoder free neural network is used to learn a lifted linear representation of the nonlinear CR3BP dynamics and a residual based approach is used to identify the corresponding control input matrix. The model is then implemented in a receding-horizon target point controller and compared with uncontrolled propagation and a State …

Developing Imitation Learning Policies By Exploring Diffusion Framework For Quadcopters, Likith Swamireddy

Theses and Dissertations

Imitation learning offers a promising approach in developing near-optimal onboard policies for nonlinear systems, by learning from computationally expensive trajectory planners during offline training. Existing State-of-the-art methods commonly learn deterministic mappings from observations to actions by training fast neural networks to mimic the expert demonstrations, which can limit their ability to capture the action distribution, when the policy is trained on multiple possible expert commands to reach the same target, and this may lead to unsafe scenarios in the obstacle environments. To address these challenges, this study explores Diffusion Models (DMs) as a feedback controller for quadcopters that learns the …

Cascaded Pid Control Of A Passive Bio-Inspired Rotating Empennage Aircraft, Zachary T. Jenkins

All Graduate Theses and Dissertations, Fall 2023 to Present

This thesis presents an autopilot for a Bio-Inspired Rotating Empennage (BIRE) aircraft. Most airplanes control yaw using a vertical stabilizer and a moving rudder, a design that has stayed essentially unchanged for nearly a century but adds weight, drag, and surface area to the aircraft. The BIRE removes the vertical tail entirely and instead allows the horizontal tail to rotate about the body x-axis of the airplane; tilting the horizontal tail produces a yaw force, doing the job of a rudder. This thesis first develops a controller for the BIRE where the empennage angle is commanded directly, then extends …

Psychometric Evaluation And Cognitive Correlates Of The Tactile Mental Cutting Test: Investigating Reliability, Validity, Gender Differences In Spatial Ability, Executive Function And Social Emotional Competence Among Native American Elementary Students, Sujata Basnet

All Graduate Theses and Dissertations, Fall 2023 to Present

Spatial ability-the ability to understand, visualize, and mentally manipulate shapes and objects-is important for learning in science, technology, engineering, and mathematics (STEM). However, many traditional spatial ability tests rely heavily on drawings and other visual representations and have often been developed and evaluated with populations that do not adequately represent culturally diverse students. As a result, there is a need for assessment approaches that are developmentally appropriate, engaging, and potentially more inclusive for young learners. The Tactile Mental Cutting Test (TMCT) provides one such approach by allowing students to explore three-dimensional objects through touch and physical manipulation while solving spatial …

Adaptive Active Snore Noise Control Using Microphone And Loudspeaker Arrays, Nathan Walker

All Graduate Theses and Dissertations, Fall 2023 to Present

Snoring can wreck a good night’s sleep, not just for the snorer but for their partner, and over time it can strain relationships. Common fixes like CPAP machines, nasal strips, and earplugs either have to be worn or don’t do much against the deep, low-pitched rumble that makes snoring so hard to ignore.

This research explores a different approach, a device that doesn’t need to be worn at all. It uses a small set of microphones to listen to the snoring and a set of speakers to play back carefully timed anti-snore noise, which is sound designed to cancel out …

Multimodal Deep Learning Architecture For Biomass Prediction Using Aerial Imagery, Sadikul Alim Toki

All Graduate Theses and Dissertations, Fall 2023 to Present

Grape growers rely on knowing how much leaf area their vines have, since canopy size affects how much water a vine needs, how healthy it is, and how much fruit it will produce. Measuring this by hand, plant by plant, across an entire vineyard takes enormous time and labor, so researchers have turned to cameras mounted on drones and satellites as a faster alternative. Drones capture very detailed images but only over small areas per flight, while satellites can photograph an entire farming region at once but cannot make out individual plants. 

This thesis builds a computer vision model, a …

Physics-Data-Hybrid Modeling And Control For Vtol Aircraft, Samantha Dawn Burton

All Graduate Theses and Dissertations, Fall 2023 to Present

Vertical takeoff and landing (VTOL) aircraft are hybrid aircraft having both a helicopter flight mode and a fixed-wing plane flight mode. The objective of this dissertation is to examine and evaluate a new approach, physics-data-hybrid (PDH), for VTOL aircraft modeling and control. The PDH approach combines traditional, physics-based methods (Newtonian mechanics) with data driven methods (a machine learning technique called a Koopman operator model) to create an efficient and accurate modeling and control framework—mitigating the disadvantages of the purely physics-based and purely data-driven methods. The PDH approach is used to model scenarios when the VTOL aircraft transitions between helicopter mode …

Flight System Development For A Bio-Inspired Rotating Empennage Experimental Unmanned Aerial Vehicle, Ashton Gilbert

All Graduate Theses and Dissertations, Fall 2023 to Present

Unmanned aerial systems, commonly known as drones, are increasingly used for research, environmental monitoring, and testing new aircraft concepts. Many commercially available drone flight controllers work well for standard aircraft designs, but they can be difficult to adapt for experimental vehicles that use unconventional control methods or require detailed monitoring during testing. This creates challenges for researchers who need flexible and reliable tools to safely evaluate new flight technologies. This work presents the development of a custom drone flight control system designed specifically for experimental research. The system integrates custom electronics and software that allow researchers to easily modify control …

Scalable Quality Assessment Of Ground Motion Records Via Interpretable Deep Learning Architectures, Ali Montazeri Namin

All Graduate Theses and Dissertations, Fall 2023 to Present

Earthquake engineers rely on accurate recordings of ground shaking to design safe and resilient buildings. However, sorting through thousands of these recordings to find the reliable ones and throwing out those ruined by sensor errors or background noise is traditionally done by hand. Because modern seismic networks collect massive amounts of earthquake data every day, this manual checking process is much too slow. To fix this, researchers are turning to artificial intelligence to automatically check the quality of these recordings.

While artificial intelligence offers a fast solution, there are limitations. These computer models can become massive and expensive to run, …

Enhancing Agricultural Sustainability Under Climate Change: A Multi-Scale Framework Integrating Climate Extremes, Resource Efficiency, And Data-Driven Modeling, Shahryar Fazli

Computational and Data Sciences (PhD) Dissertations

Agricultural systems are increasingly challenged by climate variability, where shifting temperature regimes, hydrological variability, and the rising frequency of compound and cascading extremes threaten global food security and resource sustainability. Addressing these challenges requires integrated frameworks that bridge biophysical monitoring, predictive modeling, and adaptive decision-making. This dissertation develops a data-driven, multi-scale framework to quantify and enhance agricultural resilience by integrating remote sensing, climate analytics, and machine learning across the United States, with a focus on California and the Western U.S.

First, hyperspectral and thermal remote sensing data from EMIT and OpenET are integrated to characterize crop nitrogen–water interactions and assess …

Comparative Evaluation Of Abs And Paraffin Wax As Fuels For Commercial Hybrid Rocket Thrusters, Logan J. Mecham

All Graduate Theses and Dissertations, Fall 2023 to Present

Hybrid rockets store solid fuel and fluid oxidizer separately, mixing only upon entry to the combustion chamber. This arrangement is generally safer to handle than a mixed solid propellant and simpler than a fully liquid engine, presenting an alternative for tactical rocket motors currently dominated by solid-propellant systems. Two commonly studied solid-phase hybrid fuels are three-dimensionally printed acrylonitrile butadiene styrene and paraffin wax. Paraffin is known for its high regression rate, which has been suggested to enable shorter grains and more compact overall systems, while the printed polymer is stronger, prints directly to shape, and retains structural integrity under military …

Comparative Biomechanics Of Ladder Climbing: Informing Phase-Specific Exoskeleton Control For Construction Tasks, Ehsan Shourangiz

LSU Doctoral Dissertations

Active exoskeletons are increasingly adopted in construction and other physically demanding industries to reduce physical strain, lower the risk of work-related injuries, and enhance workers’ performance. However, current devices are primarily designed for repetitive, structured tasks and do not adapt well to dynamic movements such as ladder climbing. Vertical ladder climbing is common in industrial construction for accessing tanks, scaffolds, and elevated platforms and A-frame ladders are widely used for short-duration elevated work such as overhead electrical, mechanical, and plumbing (MEP) installation, making ladder climbing a frequent and unavoidable part of the job. Because workers often transition between these ladder …

C-Band Radar Design Using The Radio Frequency System On A Chip 4x2 For Snow And Land Motion Detection Avalanche And Landslide Radar, Trevor T. Wiseman

Theses and Dissertations

In this thesis a radar system to track targets (people) and detect avalanches is developed. The radar system uses linear frequency modulated continuous wave (LFMCW) radar with a phased antenna array. Common signal processing and RF techniques are used to create a signal on an FPGA, transmit it, and receive return signals. The distance to targets as well as movement is determined by measuring the frequency difference. Advanced techniques are used, such as digital beamforming, to determine the direction of arrival of the returning signal. The results show accurate range measurements of targets in a test range up to 20 …

A Generalized Coherence Framework For Contribution Analysis In Multi-Input Systems With Correlated Inputs, With Application To Essential Tremor, Nolan H. Howes

Theses and Dissertations

Quantifying the contribution of individual inputs to an output is a fundamental problem in the analysis of dynamic systems , with applications spanning numerous engineering disciplines. Traditional coherence-based methods provide useful tools for contribution analysis when inputs are uncorrelated; however, they generally fail when correlation exists between inputs. Because correlated inputs are common in both engineered and biological systems, this limitation restricts the usefulness of conventional coherence analysis in many practical applications. The purpose of this dissertation was to develop, apply, and validate a generalized coherence framework capable of quantifying input contributions in multi-input systems regardless of input correlation. First, …

From Manifolds To Shorelines: Probabilistic Localization For Autonomous Surface Vessels In Littoral Environments, Derek Royce Benham

Theses and Dissertations

Autonomous surface vessels (ASVs) are increasingly deployed for marine monitoring, surveying, and defense missions where human operation is costly or hazardous. Yet, achieving robust autonomy in coastal environments remains challenging due to limited communication bandwidth, partial sensor observability, and unreliable GPS. This dissertation investigates new methods for localization and mapping that address these constraints through probabilistic modeling, Lie-group-based estimation, and domain-specific environmental constraints. First, a probabilistic signal-strength localization framework is developed for environments where two-way communication is infeasible, enabling one-way acoustic and LoRa-based positioning under severe bandwidth limitations. Second, the Invariant Extended Kalman Filter is extended to incorporate partial orientation …

Engineering, Processing, And Evaluation Of Alternative Solid-Phase Carbon Media For Passive Self-Regulatory Denitrification (Psrd), Chinedu James Chiama

LSU Doctoral Dissertations

Biological denitrification is an effective and cost-efficient approach for nitrate removal; however, conventional processes often rely on liquid carbon sources such as methanol or acetate that require precise dosing and monitoring. Solid-phase denitrification (SPD) using polyhydroxybutyrate (PHB) provides a self-regulating alternative, but its high cost limits widespread application. This dissertation investigated strategies to develop lower-cost solid carbon media and simplify SPD operation for recirculating aquaculture systems (RAS). PHB/cellulose (PHBC) blends containing 20–40% cellulose were first evaluated against pure PHB based on nitrate conversion, carbon release, substrate consumption, and denitrification cost. PHBC60:40 and PHBC70:30 achieved the highest apparent peak nitrate conversion …

Willingness To Pilot Under Varying Weather And Tower System Conditions: Mediating Effects Of Risk, Nathan Royal Schultz

Doctoral Dissertations and Master's Theses

The implementation of Remote Tower Systems (RTS) within the National Airspace System (NAS) offers potential improvements in operational efficiency, cost-effectiveness, and scalability; however, its success depends on pilots' willingness to operate in such environments. This study examined the effects of tower system type (RTS vs. Traditional Tower Systems [TTS]) and weather conditions (visual meteorological conditions [VMC], marginal visual meteorological conditions [MVMC], and instrument meteorological conditions [IMC]) on pilots’ willingness to pilot (WTP), while also evaluating the mediating role of perceived risk (PR). Grounded in Paul Slovic’s Risk Perception Theory (RPT), this research employed a quantitative experimental design using a factorial …

Ai-Driven Biomarker Discovery & Progression Modeling For Precision Diagnosis Of Glaucoma, Cheng Huang

Computer Science and Engineering Theses and Dissertations

This dissertation presents a comprehensive study on the integration of artificial intelligence (AI) for glaucoma diagnosis and retinal image analysis. Leveraging multimodal imaging data including fundus photography, Optical Coherence Tomography Optical Coherence Tomography (OCT) and Optical Coherence Tomography Angiography (OCTA), the research develops a suite of deep learning frameworks designed to detect early glaucomatous changes with high precision, robustness, and interpretability. A series of novel architectures are introduced, spanning vessel segmentation networks, biomarker discovery pipelines, and multimodal fusion models, all designed to enhance diagnostic accuracy and generalizability across diverse populations. To facilitate reproducible and scalable ophthalmic AI research, this work …