Buckling Analysis Of Auxetic Composite Laminates And Optimal Design Using Lamination Parameters And Machine Learning, Hans Bendon Maria Tamil Selvan

Mechanical and Aerospace Engineering Theses

Composite materials are widely used as structural panels in aerospace, automotive, and civil engineering applications, where buckling is often a critical failure mode. This thesis focuses on the analysis and design of composite laminates that maximize buckling performance under prescribed stiffness and thickness constraints.

The first part of the study investigates the buckling behavior of auxetic laminates, which exhibit a negative Poisson's ratio. While previous studies suggest that auxetic laminates can achieve higher critical buckling loads than non-auxetic laminates under simply supported boundary conditions with lateral restraint, the influence of other boundary conditions and plate aspect ratios has not been …

Flood Damage And Social Vulnerability In Coastal New Hampshire, Mitchell S. Berry

Honors Theses and Capstones

This study investigates the relationship between flood-induced building damage and social vulnerability in coastal New Hampshire, with a focus on communities increasingly affected by sea-level rise, storm surge, and high tide events. Using a dataset of 2,528 single-family homes, the analysis integrates flood depth maps (coastal, pluvial, and fluvial), building-level damage estimates, and a housing-burden-based metric to assess how physical and social factors interact to shape flood impacts. Results show that flood depth is the primary driver of building damage, with the most severe impacts concentrated in coastal areas experiencing deeper inundation. However, when buildings are grouped by vulnerability, higher …

Sewer Pipe Condition Assessment Using An Ensemble Machine Learning Framework For Infrastructure Decision Support, Mahnaz Rouhi

Civil Engineering Dissertations

Aging wastewater infrastructure presents significant challenges for municipalities across the United States, with many sewer networks approaching or exceeding their design life. Conventional inspection methods, such as closed-circuit television (CCTV), are limited by subjectivity, cost, and inefficiency. To address these challenges, this study develops an ensemble machine learning framework for assessing the structural condition of sewer pipelines using inspection records enriched with geospatial attributes.

The primary objective of this research is to enhance predictive accuracy, interpretability, and decision-support for risk-based asset management. The scope of the study encompasses 4,802 CCTV inspection records from Dallas, TX, and Tampa, FL, integrating physical, …

Videoscoop: A Non-Traditional, Domain-Independent Framework For Video Analysis, Umme Hafsa Billah

Computer Science and Engineering Dissertations

Due to the proliferation of cameras in handheld devices and the widespread use of CCTV, images and videos have become a preferred alternative for capturing and disseminating information. Automated analysis for understanding image or video contents (e.g., objects, activities, backgrounds, situations of interest, etc.) is critical for many applications such as Civic Monitoring, Surveillance (in general), monitoring activities in Assisted Living environments, and many more. Image and Video Analysis (IVA) research has been ongoing for several decades, resulting in numerous techniques for algorithmically analyzing and understanding image and video contents.

Image Analysis (IA) has advanced in several areas, including object …

Deep Learning For Wireless Communications, Swarada Ajit Kulkarni

Electrical Engineering Dissertations

The rapid evolution of wireless communication imposes stringent requirements for ultra-reliable, low-latency transmission in dynamic, interference-prone environments. Traditional model-driven signal processing struggles to adapt to nonlinear hardware effects, time-varying channels, and complex interference patterns. Deep learning (DL) offers a transformative, data-driven alternative, enabling end-to-end optimization and robust adaptation under uncertain propagation conditions.

This dissertation investigates deep learning architectures for intelligent and resilient wireless communication through three complementary contributions. The first introduces a Vision Transformer (ViT)-based modulation classification framework that leverages self-attention to capture local and global dependencies in spectrogram representations of Quadrature Amplitude Modulation (QAM) signals. The ViT achieves superior …

6 Degrees Of Freedom Robotic Arm, Vansh Garg , ‘26, Eric Chen , ‘26, Kaw Moo , ‘26

Senior Theses, Projects, and Awards

This project involved the design, fabrication, and testing of a 6 degree of freedom robotic arm. The goal was to demonstrate that a low-cost, 3D-printed system could achieve useful strength, modularity, and basic manipulation for simple pick-and-place tasks. Potential applications include education, prototyping, hobbyist robotics, and low-precision automation.

The mechanical system uses 3D-printed arm links, cycloidal gearboxes, belt-driven transmission, bearings, and a modular end effector. These components were selected to balance cost, manufacturability, and performance, with gear reduction used to increase available joint torque. The electrical system provides motor actuation, power distribution, and controller integration, while the software enables command-based …

Assessing Water Quality In Drinking Water Distribution Systems: Rural Infrastructure Challenges, Hydrodynamic Effects On Biofilms, And Biofilm Contribution To Disinfection By-Products Formation, Vinila Vasam

Graduate Theses, Dissertations, and Problem Reports (ETD)

Access to clean and safe drinking water remains one of the most persistent public health and environmental challenges in the United States. Maintaining water quality after leaving the treatment plant in drinking water distribution systems (DWDS) is a complicated and often overlooked challenge. Most research focuses on water treatment and source water quality, but not on the miles of pipe that follow. Aging infrastructure, complex flow patterns in the DWDS, and limited resources make water quality management especially difficult. This dissertation includes three core studies: 1) A system-level analysis of small and rural utilities in the geographically complex region of …

Elucidating Structure–Reactivity Relationships In Ni-Catalyzed Co2 Methanation, Majed Alam Abir

Graduate Theses, Dissertations, and Problem Reports (ETD)

The catalytic hydrogenation of carbon dioxide (CO₂) to methane represents a promising strategy for carbon utilization and renewable energy storage within power-to-gas systems. When coupled with hydrogen derived from renewable electricity, CO₂ methanation enables the conversion of intermittent energy sources into storable and transportable chemical fuels compatible with existing natural gas infrastructure. Nickel-based catalysts have emerged as leading candidates for this reaction due to their high activity towards CO₂ methanation, abundance, and cost. However, the performance and long-term stability of Ni catalysts are strongly influenced by catalyst support properties, Ni nanoparticle size, and promoter effect, and …

Real-Time Lidar-Based Vehicle Detection Using Pointpillars For Connected And Automated Vehicle Applications, Jared Townsend Behr

Graduate Theses, Dissertations, and Problem Reports (ETD)

This work explores the implementation of a real-time LiDAR processing model for autonomous vehicle design. Automotive perception systems are becoming increasingly important as Advanced Driver Assistance Systems (ADAS) and Connected and Automated Vehicle (CAV) technologies continue to progress toward higher levels of autonomy. Reliable perception is paramount for autonomous features, such as adaptive cruise control (ACC), where identifying and tracking a lead vehicle is a safety critical task.

Many production ADAS perception systems primarily rely on radar and camera sensors for object detection and sensor fusion. These sensors work well to achieve classification and accurate distance detections; however, they are …

Development And Validation Of A Multi-Output Neural Network-Based Virtual Temperature Sensor For Electric Vehicle Thermal Management, Dalton Michael Wiggins

Graduate Theses, Dissertations, and Problem Reports (ETD)

Battery electric vehicles (BEVs) rely on accurate thermal management to ensure component performance, efficiency, safety, and long-term durability. Critical propulsion system components, including electric motors and high-voltage battery packs, are commonly monitored using physical temperature sensors. However, these sensors increase system cost, introduce additional hardware complexity, and may be impractical for directly measuring temperatures at critical internal locations. Virtual temperature sensors (VTSs) provide a software-based alternative by estimating component temperatures using readily available vehicle operating data.

This research presents the development and validation of a long short-term memory (LSTM) neural network-based virtual temperature sensor capable of simultaneously estimating the motor …

Smartbot V3: A Scalable Educational And Research Robotics Platform And Decentralized Construction Framework, Robert Tyler Cook

Graduate Theses, Dissertations, and Problem Reports (ETD)

Autonomous robotic systems are increasingly used in both engineering education and robotics research, creating a need for systems capable of supporting both within a common platform. This thesis presents SMARTbot V3, a scalable robotics platform developed to support undergraduate robotics education and multi-robot research.

SMARTbot V3 is a differential-drive mobile manipulator incorporating a 3-degree-of-freedom manipulator, LiDAR, RGB cameras, onboard computation, and Robot Operating System 2 (ROS2) software. The platform was designed to support scalable deployment through standardized hardware, modular construction, and common software. A fleet of twenty robots was manufactured and deployed for both educational and research activities. Educational validation …

Assessment Of Emissions Factors For Produced Water And Other Atmospheric Liquid Storage Tanks On Natural Gas Sites, David Glenn Childs

Graduate Theses, Dissertations, and Problem Reports (ETD)

As the US natural gas (NG) sector continues to grow, concerns have increased regarding the effects and increasing volume of greenhouse gases emitted into the atmosphere. While NG is a cleaner burning fuel than diesel and gasoline, unburned methane (CH₄) has a global warming potential (GWP) 27-30 times that of carbon dioxide (CO₂). To better quantify CH₄ emissions on NG sites, the US Department of Energy (DOE) granted West Virginia University (WVU) funding to collect direct measurements at well sites and compressor stations.

In this work, a total of 18 sites, including controlled and uncontrolled …

Cell-To-Pack Modeling Of Lithium-Ion Batteries: From Bayesian Parameterization To Pack-Level Optimization, Derek Slack

Graduate Theses, Dissertations, and Problem Reports (ETD)

One of the major hurdles for electric or hybrid aviation is the comparative energy density between lithium-ion batteries and jet fuel. To help obtain maximal power-to-weight ratio in electric or hybrid powertrains the battery pack design should be optimized to be as light as possible while meeting thermal safety and power requirements. The proposed solution is an optimization routine beginning with a cell-level parameter estimation of lithium-ion battery cells, where data driven Bayesian Gaussian Processes replace empirically or analytically derived parameters in a first principles electrochemical model in PyBaMM, as functions of the transient state of the cell. The resulting …

Fairness Without Demographic Attributes In Medical Vision–Language Models, Ahsan Habib Akash

Graduate Theses, Dissertations, and Problem Reports (ETD)

Vision–language models (VLMs) and the embedding models that underlie them have become the default representation layer for multimodal artificial intelligence. Trained by contrastive alignment over enormous, loosely curated image–text corpora, they inherit the demographic skew of that data, and they encode it in the geometry of the shared embedding space itself. The consequence is a model that performs unevenly across demographic groups even when no protected attribute is ever supplied as an input. In consumer applications this is an equity problem; in medicine it is a safety problem, because an embedding that is systematically less discriminative for one subpopulation translates …

Evaluation Of Engineering Controls In Mitigation Of Fecal And Chloride Contamination To An Urban Stream, Gabriel J. Zenny

Graduate Theses, Dissertations, and Problem Reports (ETD)

Fecal coliform contamination is a major contributor to surface water pollution in the United States’ (U.S.) waterways, whether from combined sewer overflows (CSOs) (point source pollution), runoff from precipitation and snowmelt (nonpoint source pollution), or exfiltration from aging and failing infrastructure. In addition to fecal bacteria, chloride contamination is also a major, prevalent surface water contaminant impacting U.S. waterways. Chloride contamination is predominantly released into U.S. waterways as nonpoint source pollution, endemic to northern areas that use industrial brine and salt as a form of mitigation for ice accumulation on roadways. The purpose of this research was to investigate impairment …

Multi-Timescale Monitoring And Modeling For Resilient Smart Grids: Pmu Anomaly Detection And Battery Digital Twins, Muhammad Imran Hossain

Graduate Theses, Dissertations, and Problem Reports (ETD)

Modern power systems face failures at very different timescales. Cyber-physical disturbances may emerge within seconds, while battery degradation develops over hundreds of operating cycles. Both monitoring problems share the same underlying difficulty: power systems produce measurement data in abundance, but reliably labeled examples of abnormal or degraded operation are scarce. Rare grid events are difficult to label, and battery degradation data are heterogeneous across cells, cycling protocols, and chemistries. This thesis addresses these challenges through two complementary domain-informed learning frameworks that constrain representation learning using information specific to each physical problem.

First, at the system level, T-BiGAN, a Transformer-augmented bidirectional …

Analysis Of Battery Degradation Effects On Optimized Torque Splitting In Dual-Motor Electric Vehicles, Homer E. Butcher

Graduate Theses, Dissertations, and Problem Reports (ETD)

Battery electric vehicle performance depends on both powertrain efficiency and battery-health. In dual-motor all-wheel-drive battery electric vehicles, driver-requested torque can be distributed between front and rear electric drive units, creating an opportunity to reduce electrical energy demand through torque allocation. However, lithium-ion battery aging changes the electrical behavior of the energy storage system through capacity fade and internal resistance growth. Capacity fade reduces the usable energy and vehicle range, while resistance growth increases voltage drop, current-related losses, and battery electrical loading. This thesis evaluates how these degradation effects influence the energy consumption, simulated range, and battery electrical behavior of optimized …

Data Augmentation And The Reliability Of Conformal Prediction For Uncertainty Quantification In Medical Imaging, Rizwan Ahamed

Graduate Theses, Dissertations, and Problem Reports (ETD)

The safe clinical deployment of deep learning models for high-stakes medical imaging tasks requires more than high average accuracy; it requires demonstrable, per-case reliability. Uncertainty quantification (UQ) provides the missing signal that tells a clinician when a model prediction can be trusted and when a case should be escalated for expert review. Among UQ approaches, conformal prediction (CP) is especially attractive because it produces prediction sets that are guaranteed, under the assumption of exchangeability, to contain the true label with a user chosen probability, and it does so without assumptions about the model or the data distribution. This report first …

Student Support In Civil And Environmental Engineering, Heather Marie Rice

Graduate Theses, Dissertations, and Problem Reports (ETD)

Many student support services target first-year engineering students to help improve their transition from high school to college and to reach first-year retention goals. These opportunities are communicated to students through a variety of ways. The objectives of this work are to evaluate student perspectives of student services support factors in a civil and environmental engineering program and investigate how student support services and opportunities are communicated to students in a civil and environmental engineering program. The media identified for student support service outreach were the fundamentals of engineering program newsletters, academic advising newsletters, Statler eNews newsletters, and the bulletin …

Dielectrophoretic Biomarkers For Cancer Detection And Cell Analysis: Integrating Microfluidics And Ai, Raphael Olumide Oladokun

Graduate Theses, Dissertations, and Problem Reports (ETD)

Pancreatic ductal adenocarcinoma (PDAC) carries a five-year survival rate of 13%, driven largely by late-stage diagnosis and the absence of sensitive noninvasive screening tools. Current diagnostic methods lack the sensitivity to detect disease-associated systemic changes at early and precancerous stages, representing a critical clinical gap. This dissertation addresses the central hypothesis that PDAC and its pathological subtypes induce measurable, disease-associated electrophysiological changes in circulating PBMCs that can serve as correlative liquid-biopsy biomarkers. To test this hypothesis, this work asks: can dielectrophoresis (DEP), impedance and zeta potential analysis with AI-assisted classification distinguish benign pancreatic conditions (non-malignant control), precancerous lesions (primarily IPMNs), …

Assessing Mobility And Upper Extremity Function Beyond Laboratory Settings In Manual Wheelchair Users With Spinal Cord Injury Using Inertial Measurement Units, Kathylee Pinnock Branford

Graduate Theses, Dissertations, and Problem Reports (ETD)

Manual wheelchair users with spinal cord injury (SCI) face chronic, repetitive shoulder demands that far exceed those of able-bodied daily life, placing them at high risk for rotator cuff pathology and long-term upper extremity dysfunction. Despite this burden, existing research has relied predominantly on brief laboratory assessments that capture only a narrow part of real-world mechanical demands, leaving critical gaps in the identification of true injury risk factors. This dissertation developed and applied inertial measurement unit (IMU)-based methods and novel algorithms to characterize arm use, mobility, and environmental context during a full week of free living behavior in 25 manual …

Experimental Evaluation Of 100 Ft X 10 Ft Frp Truss Pedestrian Bridge, Ashish Dhital

Graduate Theses, Dissertations, and Problem Reports (ETD)

ABSTRACT

Experimental Evaluation of 100 ft x 10 ft FRP Truss Pedestrian Bridge

Ashish Dhital

FRP truss bridges are now increasingly used in pedestrian bridge applications due to their high strength-to-weight ratio, corrosion resistance, better impact performance compared with conventional materials, and ease of assembly. These advantages make FRP systems attractive for accelerated construction, remote-site installation, and environments where steel or reinforced concrete bridges may experience corrosion-related deterioration. Due to insufficient data on both strength and serviceability (i.e deflection, frequency) performances. Full-scale testing of FRP pedestrian bridges of longer spans (50’-100’) is needed to better understand the dynamic behavior, long-term …

Application Of Passive Samplers For Exploring Remedial Progress In The Torch Lake Aoc And Interlake Variability Of Pcbs, Cailin B. Bishop

Dissertations, Master's Theses and Master's Reports

This study evaluates changes in dissolved polychlorinated biphenyl (PCB) concentrations in Torch Lake, Michigan, an Area of Concern shaped by decades of legacy contamination and evolving restoration policy. Passive samplers deployed across sites and seasons (2024–2025) show total PCB concentrations ranging from below detection to 110 pg/L (mean = 16.8 pg/L), representing an approximate 90% decline since 2005. Comparisons with regional reference lakes indicate no statistically significant difference (p = 0.84), suggesting concentrations may approach background atmospheric levels despite continued variability. Congener profiles indicate a shift toward lower-chlorinated PCBs, though interpretation of higher-chlorinated congeners is limited by slow sorption kinetics. …

Performance Comparison Of A Low Mass Vibratory Lunar Surface Compactor In Vacuum Versus Atmosphere, Robin D. Austerberry

Dissertations, Master's Theses and Master's Reports

As space agencies prepare to return to the moon, an emphasis is being placed on establishing a sustained human presence that requires permanent structures and supporting infrastructure, making site preparation a critical factor. Michigan Technological University’s Planetary Surface Technology Development Lab has developed a novel low-mass surface compaction tool for use on a site preparation vehicle in collaboration with Colorado School of Mines. Testing in vacuum is necessary to simulate a relevant environment, which is required to increase the technology readiness level of this tool to TRL 5. Testing concluded significant interactions between the presence of atmosphere and other factors. …

Microgravity-Induced Alterations In Left Atrial Hemodynamics And Thrombogenic Risk: Insights From Healthy And Atrial Fibrillation Models, Grace M. Hoeppner

Dissertations, Master's Theses and Master's Reports

Background: Microgravity exposure alters cardiovascular loading, yet its impact on left atrial flow dynamics and thrombotic risk remains poorly understood. This study investigates how spaceflight-relevant microgravity-induced changes in cardiac outflow affect left atrial hemodynamics in healthy individuals and patients with atrial fibrillation.

Methods: Patient-specific left atrial models were generated for three healthy individuals and three AF patients. Computational fluid dynamics (CFD) simulations were performed using each patient’s baseline mitral outflow waveform and two modified waveforms representing short- and long-duration post-flight cardiac loading changes derived from echocardiographic observations. Hemodynamic metrics included left atrial velocity, time averaged wall shear stress, oscillatory shear …

System-Level Assessment Of Non-Ideal Phase Change Material Behavior In Low Earth Orbit Spacecraft Thermal Control Models, Nathan S. Bruursema

Dissertations, Master's Theses and Master's Reports

Phase change materials (PCMs) are of interest in spacecraft thermal control because their latent heat capacity can provide passive thermal buffering during transient or cyclic heat loads. PCM behavior is often treated using idealized assumptions such as repeatable phase transition temperatures, consistent thermal accessibility across cycles, and full latent recovery. However, practical PCM behavior may be affected by non-ideal phenomena such as supercooling, interfacial resistance, and degradation of internal transport accessibility. This thesis examines the system-level relevance of these effects for low Earth orbit (LEO) spacecraft thermal control and identifies the operating conditions under which non-ideal PCM behavior becomes design-relevant. …

Development And Calibration Of A 2-D Diesel Oxidation Catalyst Filter (Docf) Model With Spatially Varying Washcoats Using Spacims And Engine Loading Data, Thomas K. Price

Dissertations, Master's Theses and Master's Reports

Diesel engine exhaust contains regulated species, including carbon monoxide, hydrocarbons, nitrogen oxides, and particulate matter (PM). Meeting increasingly stringent emission standards typically requires multiple aftertreatment components, motivating the development of multifunctional devices that reduce system size, cost, and catalyst usage. Computational models are essential for guiding this design process; however, existing models primarily focus on single-function devices and rarely capture the behavior of multifunctional systems with multiple catalyst washcoats. This work presents a physics-based model of a wall-flow diesel oxidation catalyst filter (DOCF), a multifunctional device that integrates the roles of a diesel oxidation catalyst and a diesel particulate filter …

On The Vibrational Dynamics Of Wind Turbine Blades: The Oscillatory Response To Gust Pulses, And The Physical Mechanisms Behind Them, North A. Yates

Dissertations, Master's Theses and Master's Reports

An easily noticed trend in the utility-scale wind turbine industry is that the size of the machines has continued to increase over time. While this may have benefits in terms of increasing the power generation for a single turbine, a major drawback is the rate with which the weight of the turbine blades grow. To ensure these larger machines can be utilized, efforts are being put forth to create lighter blades. This may fix the weight issue, but brings on a new one; these lighter blades can also be more flexible than previously studied ones. It is, therefore, vitally important …

Engineering Plga Nanoparticle Size To Modulate Immune Responses After Spinal Cord Injury, Daniel J. Kolpek

University of Kentucky Doctoral Dissertations

Spinal cord injury is a severe and debilitating condition that often results in lifelong complications, including paralysis. Many of these chronic outcomes are driven by a sustained inflammatory response at the injury site, which limits tissue regeneration and functional recovery. As a result, therapeutic strategies that modulate this immune response have gained significant interest. Polymer based nanoparticle therapies have emerged as a promising approach due to their ability to interact with and influence immune cell behavior. Importantly, the physicochemical properties of nanoparticles can be precisely tuned to optimize these effects. Among these properties, size has been shown to influence key …

Generative Imaging For Computational Pathology, Md Jillur Rahman Saurav

Computer Science and Engineering Dissertations

Hematoxylin and eosin (H&E) staining remains central to cancer diagnosis, providing morphological information essential for pathological assessment. Immunohistochemistry (IHC) and newer multiplexed imaging technologies complement H&E by revealing molecular information critical for accurate tumor subtyping and treatment decisions. In practice, however, H&E and IHC are obtained from different consecutive sections that are not spatially aligned, comprehensive multiplexed panels are expensive and tissue-consumptive, and not all stains are available at every clinical site, limiting comprehensive molecular profiling and the full diagnostic potential of these technologies in clinical practice. This dissertation addresses these gaps through three complementary generative deep learning studies in …