Engineering Commons^™

Enhancing Stem Education With Modeling, Simulation, And Ai Technologies: From Virtual Laboratories To Intelligent Teaching Assistants, Yiyang Li

Electrical & Computer Engineering Theses & Dissertations

Rapid advancements in modeling and simulation (M&S) and artificial intelligence (AI) present new opportunities to enhance various aspects of STEM education, from virtual laboratories that simulate physical lab environments in software to intelligent teaching assistants that provide on-demand, curriculum-aligned instructional support. Virtual laboratories offer a potential solution to the access and scalability challenges of laboratory courses by allowing students to conduct experiments without physical equipment or geographical constraints. AI-powered teaching assistants, particularly those grounded in course-specific materials, can help mitigate the instructional support gap that arises when students work independently in digital learning environments. This dissertation presents three-phase research into …

A Causal Inference Protocol For Root-Cause Diagnosis In Non-Stationary Industrial Time Series, Cansu Yalim

Engineering Management & Systems Engineering Theses & Dissertations

Industrial fault diagnosis increasingly relies on data-driven methods, yet most approaches assume process stationarity and treat association-based rankings as sufficient evidence for root-cause identification. Neither assumption holds when operating phases and fault progression create distinct behavioral regimes with shifting relationships among variables, and neither answers which feasible corrective action would alter a fault trajectory. The absence of a procedure addressing non-stationarity, causal identifiability, and decision-relevant effect estimation constitutes the gap this dissertation targets. In this context, a regime is a time period in which the process operates under a relatively consistent setting, so the relationships among variables are approximately stable …

Drones In Wildfire Airspace Management: Developing A Scalable Framework For Mid-Sized Cities, Victoria Denise Tanner Williamson

Engineering Management & Systems Engineering Theses & Dissertations

Wildfires are becoming increasingly frequent and severe, creating growing risks for mid-sized communities with limited emergency response resources. The January 2025 Los Angeles wildfires—which burned more than 57,000 acres and destroyed over 18,000 structures—underscore the urgent need to strengthen wildfire response strategies through the integration of unmanned aerial systems (UAS) (Hardy, 2025).

This study develops a scalable framework for drone-assisted wildfire response in resource-constrained environments. Using the city of Waynesboro, Virginia, as a case study, the research examines how mid-sized jurisdictions can integrate unmanned aerial vehicles (UAVs) to improve preparedness, response, and recovery. A three-round, mixed-methods Delphi study engages emergency …

Physics-Guided Deep Learning For Predictive Modeling Of Spatiotemporal Dynamical Systems, Niharika Deshpande

Engineering Management & Systems Engineering Theses & Dissertations

Many physical and networked systems evolve under continuously changing spatial and temporal conditions. Transportation networks respond to fluctuating demand, atmospheric fields reorganize as storms intensify, and coastal response depends on localized forcing pathways. Modeling such systems requires learning formulations that adapt to evolving structure, operate on irregular geometries, and provide interpretable measures of predictive uncertainty. This dissertation develops a physics-guided spatiotemporal learning framework designed for structured dynamical systems whose governing interactions are neither static nor Euclidean. The central premise is that spatial relationships in these systems are dynamic and geometry-dependent. To represent this behavior, system states are modeled on time-varying …

Residual Stress Informed Reconstruction And Failure Analysis Of Manufacturing Induced Composite Meso-Structure, Mohammad Nazmus Saquib

Mechanical & Aerospace Engineering Theses & Dissertations

A physics informed, AI-augmented framework is developed to enable digital twins of molded composite materials by linking manufacturing induced residual stresses to a local meso-structure. By reconstructing and explicitly modeling these architectures, the framework reveals how processing driven meso-structural variability governs stiffness, damage evolution, and failure. The work focuses on two technologically important systems: prepreg platelet molded composites (PPMC), characterized by inherently stochastic platelet architectures, and 2/2 twill glass fiber/PA6 organosheets, whose periodic but locally variable weave geometry influences mechanical response. For PPMC, the Residual Stress Informed Microstructure Reconstruction (ResIMiR) framework is introduced, combining thermoelastic strain fields with deep learning …

Computational And Ai Tools For Understanding Telomere-Associated Cancer Mechanisms, Eleni Adam

Computer Science Theses & Dissertations

Telomeres are the protective caps of the human chromosomes and are critical for genome stability. Dysfunctional telomeres caused by their erosion with age and cell proliferation as well as by defects in their maintenance is a major early event leading to genome changes and cancer. Subtelomeres possess the critical role of regulating adjacent telomeres. Due to their complex repeat structure and high variance from one person to another, these areas have not been analyzed in detail. We present a set of computational and machine learning tools to aid in the understanding of subtelomere structure and its rearrangements in cancer.

Initially, …

Effect Of Rheology Modification On Fiber Orientation And Dispersion In 3d-Printed Ultra-High-Performance Concrete, Haodao Li, Alfred Addai-Nimoh, Seongho Han, Kamal H. Khayat

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

The extrusion process in 3D concrete printing (3DCP) facilitates horizontal alignment of steel fibers along the printing direction, thus enhancing the load-bearing capacity of printed elements. However, such shear-induced fiber alignment is highly sensitive to rheological properties. This study investigates how variations in dynamic yield stress (τd) and plastic viscosity (μ), influence the extrudability, fiber orientation and dispersion, and anisotropic mechanical behavior of ultra-high-performance concrete (UHPC). Five viscosity-modifying agent (VMA) types were incorporated at two content levels to modify the rheology of printable UHPC. Results showed that moderate VMA additions improved printability, whereas excessive contents markedly increased τd and μ; …

Reframing Soil Freezing As An Unsaturated Process, Antai Dong, Xiong Zhang

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Soil freezing and frost heave are inherently unsaturated soil phenomena. However, most existing numerical models are based on saturated soil mechanics or assume full saturation. This simplification introduces conceptual inconsistencies, requires modifications that violate fundamentals in soil mechanics and fluid mechanics, and often leads to the use of self-conflicting soil properties. To overcome these limitations, this study develops a physically consistent, fully coupled thermohydraulic model for soil freezing grounded in modern unsaturated soil mechanics. A soil freezing characteristic surface (SFCS) is introduced to represent unfrozen water content in partially frozen soils as a function of both suction and temperature. Recognizing …

High-Throughput Characterization Of Creep In Additively Manufactured 316l Stainless Steel, Raushan Kumar Singh

All Graduate Theses and Dissertations, Fall 2023 to Present

Advanced materials are widely used in industries such as nuclear energy, aerospace, and automotive engineering, where components are exposed to extreme temperatures and stresses over long periods of time. As new materials continue to emerge, researchers need efficient ways to evaluate their mechanical performance so they can be used safely and effectively. Among several mechanical challenges, creep is a major concern in these conditions. Creep is a type of mechanical failure in which materials gradually deform when exposed to high temperatures and constant load. Conventional methods for evaluating creep typically involve testing a single specimen at a time, which can …

Thermal Rating And Prediction Of Roadway-Embedded Power Electronics For Dynamic Wireless Power Transfer, Forrest D. Nichols

All Graduate Theses and Dissertations, Fall 2023 to Present

Electric vehicles can be charged while driving through wireless charging coils buried in the road surface. To avoid running expensive cables from roadside equipment to each charging pad, the electronics that control the power transfer can also be buried in the road. However, burying these circuit boards removes the ability to cool them with fans or flowing air, so the heat generated during operation must escape naturally into the surrounding road material. If the boards get too hot, components fail—a problem that has already been observed in prototype systems.

Predicting how hot each component on a circuit board will get …

Sensitivity Analysis Of A Low-Power Wireless Capacitive Charging System To Inform Thermal Limitations And Battery Size Reduction Potential For Electric Passenger Vehicles, Karmen Teuscher

All Graduate Theses and Dissertations, Fall 2023 to Present

The purpose of using electric vehicles instead of internal combustion engine vehicles that burn gas is to reduce pollutants in the air and potential environmental impacts such as climate change. EVs produce much less air pollutants than ICEVs but manufacturing the EV batteries and the repeated recharging still contributes to the overall air pollution.

Capacitive power transfer systems can wirelessly charge vehicles through the road as they drive along highways or stop at traffic lights. If vehicles charge as they drive, an opportunity opens to reduce the size of the battery while maintaining the same driving range. Reducing the size …

Cadmium Biosorption By Fusarium Venenatum And Its Application In Functional Permeable Materials For Metal Removal, Bradley Lawson

All Graduate Theses and Dissertations, Fall 2023 to Present

Heavy metals are pollutants of increasing concern as continued industrialization and urbanization have escalated the discharge of these toxins into aquatic environments. Cadmium (Cd) is a metal of particular concern due to its acute toxicity and high mobility in aquatic ecosystems. Given these characteristics Cd poses significant health risks to both humans and aquatic ecosystems. The continued development of sustainable, low-cost remediation technology is imperative to manage metal pollution.

This research explores the use of fungal-based remediation systems to remove Cd from contaminated water. Living biomass of the filamentous fungus Fusarium venenatum was evaluated as a biosorbent material for Cd …

Modeling And Generating Crash Avoidance Behaviors In Safety-Critical Vehicle–Pedestrian Interactions Using Deep Reinforcement Learning, Qingwen Pu

Civil & Environmental Engineering Theses & Dissertations

Traffic crashes between vehicles and pedestrians arise from complex, split-second interactions in which both parties make rapid evasive decisions. Four fundamental gaps persist in existing research. Surrogate safety measures assume linear trajectories, failing to capture the curved movements of turning vehicles and crossing pedestrians at intersections. Single-agent modeling treats one party as a fixed obstacle, ignoring the joint decision-making that governs near-miss outcomes. The effect of vehicle type on pedestrian avoidance behavior—whether pedestrians respond differently to automated vehicles (AVs) than to human-driven vehicles (HDVs)—remains poorly understood. Finally, automated driving system development is hampered by a severe scarcity of large-scale, behaviorally …

Time-Frequency Analysis Of Arterial Pulse Signals Of Cardiovascular Disease Patients Measured By A Microfluidic-Based Tactile Sensor, Md Mahfuzur Rahman

Mechanical & Aerospace Engineering Theses & Dissertations

This dissertation presents a single-degree-of-freedom (SDOF) based time–frequency analysis framework that can simultaneously extract a comprehensive set of cardiovascular autonomic indices from arterial pulse wave recordings obtained at rest and post-exercise, supporting non-invasive monitoring of autonomic recovery during cardiac rehabilitation. The framework rests on three technical contributions.

First, an SDOF analytical model of motion artefacts quantifies two physically distinct distortion mechanisms: additive baseline drift and Time-Varying System Parameter (TVSP) generated distortion of the Tissue-Contact-Sensor (TCS) stack. Baseline drift is slowly varying and removable by filtering; TVSP distortion rides on all harmonics of the true pulse signal and cannot be removed …

Deep Multimodal Sensor Fusion For Autonomous Driving: A Real-World Deployment On Little Blue, Raphael T. Pamie-George

Electrical & Computer Engineering Theses & Dissertations

Accurate perception and control systems are essential for autonomous vehicles to safely interpret and navigate complex environments. Individual sensing modalities such as cameras, LiDAR, and inertial measurement units (IMUs) provide valuable environmental and vehicle state information; however, each sensor exhibits inherent limitations when used independently. Camera performance can degrade under varying lighting conditions, LiDAR measurements may be sparse or affected by environmental noise, and IMU measurements are susceptible to drift over time. Little Blue, a research autonomous vehicle platform from ODU (Old Dominion University), previously relied primarily on camera-based data for neural network training, limiting the system’s ability to exploit …

Id-More Vision: Real-Data Machine-Learning Assessment For A Digital-Twin-Inspired, Xr-Ready Rehabilitation Prototype, Rickey L. Clark

Master's Theses

Rehabilitation assessment often relies on periodic observation, while many XR prototypes show scripted rather than recorded-motion evidence. iD-MORE Vision is an offline pipeline trained on KIMORE and IRDS and linked through JSON packets to a two-mode Unity desktop prototype. Both datasets include controls and rehabilitation participants with neurologic, musculoskeletal, or mobility impairments. This improves relevance but does not clinically validate the system.

Under fixed subject-wise splits, the primary five-seed Random Forest predicted KIMORE clinician scores with MAE 6.087 ± 0.044 cTS and R² 0.568 ± 0.006; the subject-level R² interval crossed zero. The primary IRDS five-run CUDA GRU averaged 0.877 …

Prompt-Driven Tabletop Robotic Manipulation With A Structured Llm Interface And Visual Verification, Tomas Franco

Master's Theses

Creating a tabletop robotic manipulation system that connects language goals to robot actions is a challenging problem. Large language models can interpret mission objectives and reason through actions, but when placed directly in control of hardware they can produce hallucinated commands that result in unsafe behavior without the proper safeguards.

This thesis presents a constrained LLM-guided manipulation system built around the Quanser Qarm, a four degree of freedom manipulator with a mounted Realsense RGB-D camera and a gripper with readable current. Every decision made by the LLM planner is routed through a gated command interface that restricts the model to …

Hardware-In-The-Loop Evaluation Of Sensor-Source Selection For Prosthetic Locomotion Intent Recognition, Victoria Asencio-Clemens

Master's Theses

Active lower-limb prostheses use intent-recognition systems to identify a user’s locomotion mode and select an appropriate control strategy, but sensor configurations that perform well offline may be unsuitable for resource-constrained embedded hardware. Existing sensor-selection methods generally prioritize classification accuracy without directly accounting for processing latency, memory usage, or other hardware-dependent requirements. To address this limitation, this thesis develops a hardware-in-the-loop source-selection framework for embedded classification of level walking, ramp ascent, ramp descent, stair ascent, and stair descent using multimodal biomechanical data from transtibial amputee participants. Subject-specific linear support vector machine classifiers were evaluated using trial-held-out validation, and candidate configurations from …

Predicting Student Belonging In Computing Education: A Multimodal Machine Learning Approach Using Eeg And Survey Data, Hannah Moshtaghi

Master's Theses

Measuring students’ sense of belonging, characterized by feelings of acceptance, inclusion, and encouragement from teachers, remains a significant challenge in computing education. Prior research has associated this multidimensional construct with positive academic outcomes and has identified instructors’ growth- and fixed-mindset messaging as a potential influence. However, belonging is a complex and deeply personal experience that is difficult to capture through direct observation alone. Current measurement methods rely on self-report surveys, which may not capture every aspect of an experience that can also involve emotional and cognitive responses.

This thesis investigates whether combining EEG data recorded during a belonging questionnaire with …

Expected Structural Damage, Residual Capacity, And Repairability Of Light-Frame Timber Houses, Mikayla Caruthers

Master's Theses

Earthquake damage in light-frame timber structures is commonly evaluated using peak inter-story drift. However, drift alone does not fully represent the remaining structural capacity of a building or its ability to be repaired following a seismic event. Although expected structural damage, residual capacity, and repairability have each been studied extensively, these concepts are often considered independently, leaving limited guidance that links them within a unified post-earthquake assessment methodology.

This thesis establishes an integrated framework that relates expected structural damage, residual capacity, and repairability for light-frame timber residential structures. Existing literature was synthesized to develop drift-based damage-state classifications, identify methods for …

Synthesis And Characterization Of Carbon Quantum Dots And Gold Nanoparticles For Norovirus Biosensing Applications In Water Systems, Breanne Evans

Master's Theses

Rapid, reliable detection of viral pathogens remains a significant challenge across water-treatment and environmental monitoring systems, including drinking-water, wastewater, water reuse, and environmental surveillance applications. Waterborne viral contamination can pose substantial public-health risks, making early detection essential for protecting water quality and responding quickly to treatment failures or contamination events. Direct potable reuse (DPR) is one particularly demanding example because it requires continuous verification of treatment performance and the broader need for rapid virus monitoring extends across many water-treatment and environmental surveillance applications. Norovirus is a priority target because of its widespread occurrence in wastewater, environmental persistence, and exceptionally low …

A Technoeconomic And Lifecycle Analysis Of Catalytic Non-Thermal Plasma Steam Methane Reforming For Renewable Hydrogen Production, Gustav M. King

Master's Theses

When produced with sufficiently low life-cycle emissions, hydrogen may support low-carbon, dispatchable electricity generation to realize statewide renewable energy regulatory objectives. This thesis develops a screening-level electrothermochemical process model of catalytic non-thermal plasma steam methane reforming (CNTP-SMR) and integrates it with techno-economic and life-cycle assessments. Biogas and natural gas fed CNTP-SMR scenarios are compared with conventional steam methane reforming to evaluate hydrogen production cost, global warming potential, and the effects of key operating parameters. Under the baseline assumptions, CNTP-SMR generated hydrogen at a higher levelized cost (baseline of $3.86/kg H₂ and a range of $3.68 to $4.11) when compared …

An Integrated Model For Post-Hurricane Displacement, Shelter Demand And Shelter Allocation, Nirmal Adhikari

All Theses

This thesis develops an integrated tract-level framework for estimating post-hurricane displacement, short-term shelter demand, long-term shelter demand, and shelter allocation under hurricane wind hazards. The framework combines parametric wind-field modeling based on HURDAT2 and EBTRK hurricane data with HAZUS-based fragility and loss functions, uninhabitability relationships, demographic factors, and an insurance-sensitive recovery model. Tract-level insurance adequacy is estimated using American Community Survey data, National Association of Insurance Commissioners premium data, and the National Risk Index, using five scenario-based models; the combined home-value and hazard-risk model is adopted for final analyses. To evaluate post-disaster housing capacity, the study estimates the number of …

Extended Adaptive Oscillator Framework For Gait Phase Estimation With Adaptive Coupling And Transition Detection Across Locomotion Tasks, Nikhila Radha Krishnan

All Theses

Gait phase is a human-inspired physical variable that describes the instantaneous position of a person within a gait cycle. Adaptive oscillators have been widely used for gait phase estimation due to their ability to synchronize with periodic and pseudo-periodic biomechanical signals and generate monotonically increasing cyclic phase values. Typically, the performance of adaptive oscillators is strongly influenced by coupling strength, a parameter that bridges a trade-off between convergence speed and steady-state variability of the estimated stride frequency. In gait assistive applications, stride frequency estimation must be sufficiently fast to enable phase-based assistance while achieving a stable stride frequency estimate. The …

The Aggregation Of Microplastics By Enhancing Extracellular Polymeric Substance Production In Pseudoalteromonas Sp. Ncimb 2021 To Improve Removal Efficiencies In Environmental Matrices, Janelle L. Mercer

All Theses

Microplastics (MP) are ubiquitous in the natural environment and are a growing threat due to their small size and durability. Plastics are released into the environment through improper waste management, wastewater treatment outfalls, industrial spills, agricultural runoff, and landfills. These particles breakdown into secondary MP through degradation pathways. MP, less than 5 mm, require intricate removal techniques from water systems. Filtration techniques, though viable and effective, have implementation constraints due to high cost, maintenance demands, and filter fouling. By integrating coagulation and flocculation processes prior to filtration, MP removal efficiencies can increase, while minimizing operational challenges during filtration. Extracellular polymeric …

Evaluation Of Ostomy Pouching Change Practices Among Hospital-Based And Community-Based Nurses, Hannah Gerlach

All Theses

An estimated 725,000 to 1 million Americans are living with an ostomy and depend on ostomy pouching systems as part of their daily care. Effective ostomy management requires regular pouch changes and consistent skin care to prevent peristomal skin complications. Many individuals living with an ostomy face long-term challenges in managing their ostomy care, which can negatively affect their health-related quality of life. There is a need to understand how professional experience across different care environments, such as hospital-based and community-based settings, influences ostomy nursing care practices.

This study evaluates how nurses working in hospital-based settings and community-based settings perform …

Developing A Rapid Urban Forest Assessment System For Sustainable City Greenification, Daniel Gonzalez

Master's Theses

This thesis presents the Rapid Urban Forest Assessment (RUFA) system, a web-based platform that integrates urban tree inventories and aerial tree detection to assess forest health across California’s census-designated places. RUFA combines inventoried tree records with coordinates detected from high-resolution multispectral imagery using convolutional neural networks, then computes a composite RUFA Score from four metrics: canopy cover percentage, trees per capita, tree diversity (TD-50), and tree evenness. The thesis addresses two engineering challenges in building the dashboard: querying and aggregating over seven million tree records in real time, and rendering spatial summaries at multiple zoom levels without recomputing cluster assignments …

Probabilistic Modeling Of Hurricane Hazards And Structural Reliability Of Offshore Wind Turbines Under Climate Change, Susmita Bhowmik

All Dissertations

Hurricanes are among the most destructive natural hazards in the United States, especially along the Atlantic and Gulf coasts. Climate change is expected to affect hurricane activity by changing important environmental conditions. At the same time, offshore wind energy is expanding, creating a need to understand hurricane risks to offshore wind turbines.

This dissertation develops a stochastic hurricane simulation framework to estimate hurricane wind hazards for coastal and offshore regions along the U.S. East Coast and Gulf Coast. The framework generates synthetic hurricane tracks using updated storm-frequency data and is validated against historical records from HURDAT2, NOAA buoy wind observations, …

Optimal Management Of Electric Vehicle Fast Charging Stations Via Lyapunov Optimization And Reinforcement Learning, Mohammad Hossein Abbasi

All Dissertations

The transportation sector is responsible for 28% of global energy-related emissions, with road transport accounting for most of these emissions. While electric vehicles (EVs) are essential for decarbonizing transportation, widespread adoption depends on fast, efficient charging. Fast charging reduces charging time but accelerates battery degradation, whereas slow charging increases range anxiety. In addition, fast charging stations (FCSs) impose significant stress on distribution grids, making their operation a critical challenge. Optimizing FCS operation can conflict with EV fast-charging objectives, yet existing research largely treats these problems independently despite their strong interdependence.

Current fast-charging methods focus on individual cells or small battery …

A Surface-Bound Detection Architecture For Label-Free Evanescent-Wave Sensing Of Cobalt In Complex Fluids, Jeremiah W. Carpenter

All Dissertations

Cobalt exposure is a clinical concern in orthopedic implant surveillance, where cobalt-chromium wear debris can release ions detectable in blood and urine, and an environmental concern in mining-affected and industrial water systems. Reference laboratory methods, including inductively coupled plasma mass spectrometry, provide sensitive quantification but require centralized instrumentation, trained personnel, and controlled sample handling, which limits their availability for routine screening in decentralized clinical and environmental contexts. This dissertation develops a surface-bound detection architecture for label-free evanescent-wave sensing of cobalt in complex fluids. The architecture rests on a physical necessity argument grounded in interfacial optics: at physiologically and environmentally relevant …