Engineering Commons^™

A System And Method For Measuring Spatially Varying Surface Appearances With A Study Of Feathers, Jessica Baron-Lis

All Dissertations

Real-world materials, particularly biological structures such as feathers exhibit complex appearances that vary spatially across their surfaces. The field of computer graphics provides a means of understanding such surfaces through material modeling which uses both analytical models and data acquired from light-surface interactions. There are many efforts within the past decade in measuring materials for graphics, but common limitations in these works include not accounting for spatially varying properties and reliance on neural networks and synthetic datasets.

Feathers from modern birds present diverse appearances due to how light interacts with their unique hierarchical microstructures. Variations in those structures lead to …

Enhancing Photovoltaic Inverter Reliability Through Advanced Hardware Protection And Simulation Techniques, Buck Brown

All Dissertations

Power electronics converter reliability is an issue in today’s grid, and it is an issue that will only become more prevalent as the nation and world move toward greater renewable energy penetration. While a significant amount of research has been conducted pertaining to power electronics converter reliability, (1) there lacks a universal way to protect the most critical component in a power electronics converter—the power device—from the two most common failure modes—short- and open-circuit faults; and (2) there does not exist a tool that considers both the component- and system-levels of a photovoltaic (PV) inverter for the purposes of lifetime …

Design And Characterization Of Lignin-Based, Thermoresponsive Soft Composites With Improved Mechanical And Transport Properties, Missoury D. Wolff

All Dissertations

In an attempt to reduce reliance on petroleum-based polymers, lignin – an abundant biopolymer – has gained popularity as a sustainable alternative. However, research on lignin-containing soft composites – i.e., hydrogel (bio)composites – has largely been heuristic, providing limited insight into the fundamental structure-processing-property relationships that govern performance improvements in this emerging class of ‘green’ soft composites. As such, this dissertation presents a systematic investigation of how lignin molecular weight (MW), composite composition, and the concentrations of crosslinker and accelerator impact the mechanical and transport characteristics of soft composites composed of lignin, poly(N-isopropylacrylamide) (PNIPAm), and poly(vinyl alcohol) (PVA).

In the …

Integrating Artificial Intelligence For Transportation Cyber-Physical Systems: From Detection To Cyber Resilience, Reek Majumder

All Dissertations

This dissertation investigates different methods for methane detection using unmanned aerial vehicles (UAVs). The author addresses the fundamental problem of methane emissions, a potent greenhouse gas responsible for global warming. The first part of the dissertation aims to create a cost-effective system for real-time methane detection and intensity prediction using ensemble learning models trained on meteorological parameters. The ensemble learning-based classification models show a high accuracy for methane detection.

The second part of the dissertation investigates cyberattack detection for UAVs using a graph-based intrusion detection system (IDS) for controller area networks (CAN). This lightweight, protocol-independent IDS uses graph-based machine learning …

Understanding Conversion Of Long Chain Fatty Acids In Anaerobic Digestion Systems, Julia Ann Funk

All Dissertations

Anaerobic co-digestion with fats, oils, and grease (FOG) waste can increase energy production due to the high methane potential of lipids. However, adding FOG can lead to operational issues caused by accumulating saturated long-chain fatty acids (LCFA). My research explored why saturated LCFAs are often the primary intermediate that accumulates and the microbial sensitives of the populations responsible for their degradation. In each batch or semi-continuous experiment, all intermediates of FOG degradation, including LCFAs, volatile fatty acids (VFAs), Hydrogen gas (H₂), and endpoint methane production, were paired with temporal quantitative polymerase chain reaction (qPCR) of the Syntrophomonas genus …

User Acceptance Of Shared Autonomous Vehicles, Haotian Su

All Dissertations

A dissertation is proposed to explore user acceptance of shared autonomous vehicles (SAVs). SAVs are facing limited user acceptance. To systematically tackle the user acceptance barriers of SAVs, the main problem can be disintegrated into two sub-problems of user acceptance of autonomous vehicles (AVs) and ridesharing. The comfort of the ride experience in AVs is a determinant of user acceptance. Understanding the influential factors and developing methodologies to quantify human comfort in AVs are essential to facilitating future research to improve human comfort in AVs. The current pooled rideshare (PR) service closely resembles the anticipated future of SAVs. Understanding why …

Changes In The Western Flank Of The North Atlantic Subtropical High Since 1140 Ce: Extremes, Drivers, And Hydroclimatic Patterns, Joshua C. Bregy, Justin T. Maxwell, Scott M. Robeson, Grant L. Harley, Valerie Trouet

Publications

Summer circulation and moisture patterns in the Southeast United States are controlled by the position of the North Atlantic subtropical high. In a warming climate, the subtropical high is projected to strengthen and expand west, but there remains uncertainty regarding its variability and linkages to natural drivers. Here, we use a tree-ring network across the Southeast United States to reconstruct the relative intensity of the pressure gradient across the subtropical high’s western flank over the past 870 years. Variations in the flank’s position and the pressure gradient have been a major driver of the hydroclimate—including creating a Southeast-Caribbean moisture dipole—since …

Principles Of Advanced Manufacturing For Engineers, Xin Zhao, Walid Asad, Subha Majumder, Chenyang Zhu

Manufacturing

No abstract provided.

Foundational Robotics, Akshit Lunia, Ananya Nagabhushana Rao, Yue Wang

Robotics

This textbook is a product of Co-DREAM OER (Collaborative Development of Robotics, Mechatronics, and Advanced Manufacturing Open Educational Resources), a US Department of Education-funded initiative to develop Open Educational Resource textbooks on robotics, mechatronics, and advanced manufacturing processes. It has been created by a diverse team of scholars and graduate students from across the country and is intended for higher-level robotics courses offered by 4-year undergraduate programs.

Microwave Flow Cytometer For Single Cell Detection, Differentiation, And Drug Effect Study, Neelima Dahal

All Dissertations

New methods to rapidly detect and identify pathogens in patients’ blood are needed for timely disease treatment. In this work, a tunable microwave interferometer was used to measure single Candida cells of C. albicans, C. tropicalis, C. parapsilosis, and C. krusei at multiple frequencies between 0.265 GHz and 7.76 GHz. A Quadratic Discriminate Analysis was used to classify Candida species with an accuracy of 0.875. Likewise, a microwave device was used to measure single Escherichia coli cells of B and K-12 strains at multiple frequencies between 500 MHz and 8 GHz. A LightGBM model was developed to …

Electrochemical Techniques For The Treatment Of Source-Separated Urine, Philip Arve

All Dissertations

Urine makes up approximately 1% of the total volume of municipal wastewater, but it contributes up to 75% of the nitrogen and 50% of the phosphorus received by publicly owned treatment works (POTWs). These elements are essential nutrients for plant growth and trigger algal blooms when released into natural bodies of water, resulting in rapid ecological degradation. Removing these nutrients from municipal wastewater is energy intensive and often operationally sensitive. The past few decades have seen an increase in focus on the source-separation and side-stream treatment of urine.

Urine characteristics differ greatly from those of municipal wastewater, presenting an opportunity …

Learning To Represent Temporal Dynamics And Generative Factors For Intelligent Visual Navigation, Sahand Khoshdel

All Theses

Visual navigation systems are crucial in various applications, including autonomous driving, unmanned aerial systems (UAS), and industrial automation. For these systems to operate efficiently in dynamic environments, they must not only interpret complex surroundings but also anticipate changes over time. Temporal prediction—forecasting environmental changes like moving obstacles or shifting lighting conditions—enables navigation systems to act proactively, enhancing both safety and performance. This dissertation investigates representation learning methods both as a backbone feature extractor for RL agents as well as a proxy for systems oriented for Explainable AI (XAI). Two main projects are presented as case studies to achieve the aforementioned …

Striking A Balance: Market Shock & Responses In Automotive Components Manufacturing, Emma Lane Mcgahey

All Theses

This thesis examines the effects of extreme market shocks on supply chain dynamics within the automotive industry. Through an analysis of demand data from an automotive manufacturer to its component suppliers (January 2018 to May 2024), the study investigates the relationship between market shocks and supply chain responses, providing insights into how auto components inventory management handles downstream responses to market shocks. With supporting public data—from FRED, BLS, and the U.S. Census Bureau resources—we explore two primary relationships: the impact of market shocks on the Average Standard Deviation of Demand (SDO) and the effect of demand variability on expedited pricing …

Interpreting Strain Caused By Transient Well Testing, Soheil Roudini

All Dissertations

Understanding reservoir properties and structure is essential to managing subsurface operations, such as geologic storage of CO₂ or production of water, hydrocarbons or heat. Previous work demonstrated the potential of analyzing strain data during transient well tests by estimating hydraulic diffusivity using a type-curve-like approach. The following dissertation aims to pursue this potential by developing and evaluating methods for interpreting strain tensor data to improve subsurface characterization. The research advances the classic, intuitive method of using type-curves to interpret well tests, but it also brings together modern computational methods from machine learning, proxy modeling and Bayesian inversion, and it …

Investigating Challenges Of Converting Cad Models To Game Ready Assets, Vathsa Pawar

All Theses

This thesis explores the challenges associated with converting detailed CAD models into game-ready assets optimized for use in virtual reality (VR) environments using game engines, focusing on enhancing using mechanical engineering models. The primary goal is to establish a toolchain that allows the integration of CAD models into game engines for immersive applications, enabling engineers and stakeholders to interact with 3D models in a synthetic environment. The study employs several test cases ranging from simple door models to complex automotive vehicle prototypes, elaborating the process of exporting CAD models through intermediate formats (such as STEP, STL, GLB) using tools like …

Assessing The Potential For Photosynthetic Degradation Of Per- And Polyfluoroalkyl Substances, Marlow Thomas

All Theses

PFAS is a prevalent groundwater contaminant. It has been known to cause many health issues for humans and animals including cancer and several diseases. A main problem faced with PFAS is contamination in groundwater. Remediation strategies have been and continue to be researched to try to mitigate this issue. Current treatment strategies to mitigate PFAS include the use of granular activated carbon, ion exchange, chemical oxidation, and many hybrid treatments. There has not been one treatment technology to date that has prevailed as the best due to monetary and time constraints.

The main intention behind this research is to examine …

Influence Of Hygrothermal Conditions Of The Bistability Of Asymmetric Carbon Fiber Laminate Composites, Celia Hill

All Theses

Carbon fiber-reinforced polymer (CFRP) laminates have widespread use in many industries because of their exceptional strength-to-weight ratio. Carbon fiber laminates following an asymmetric layup orientation can exhibit bistability meaning the laminate can exist at two stable geometric configurations. The morphing characteristics of bistable CRFP has a growing level of interest because of its potential in various applications including space aircraft structures for easy repair, automotive structures for energy dissipation and ergonomics, robotics for flexible motion and energy harvesting. Existing research shows that both moisture and temperature affect the material properties and behavior of CFRP laminates, however, the influence of moisture …

Toward Electrochemical Detection Of Salmonella Enterica Serovar Enteritidis On Hydroponically Grown Green Onions (Allium Fistulosum L.), Lisseth Casso-Hartmann

All Theses

The Food and Drug Administration (FDA) established standards during the growing, harvesting, packing, and holding of produce for human consumption as part of implementing the Food Safety Modernization Act (FSMA). One of the main requirements for farmers is to detect environmental pathogens such as Salmonella enterica species in water and sprout samples. S. enterica is a bacterium of significant concern due to its pathogenicity and ability to survive and persist in diverse environmental conditions. S. enterica has been associated with recalls in ready-to-eat foods. Traditional detection methods include Enzyme-Linked Immunosorbent Assay (ELISA), Polymerase Chain Reaction (PCR), and plate counting, which …

Surgical Suturing Skill Assessment Using Estimated Hand Roll Angle From A Deep-Learning Computer Vision Algorithm, Jianxin Gao, Amir Mehdi Shayan, Simar P. Singh, Joe Bible, Ravikiran Singapogu, Richard E. Groff

Publications

This paper proposes a deep-learning computer vision algorithm to estimate hand roll angles for metric-based assessment of surgical suturing skills. The number of rolls metric, previously calculated directly from IMU data, counts the number of hand roll reversals during a single suture. To calculate this metric using computer vision, we apply a deep-learning algorithm that can reliably estimate hand roll angles after training on suturing videos collected on the SutureCoach simulator. Results show that the estimation accuracy of the deep-learning algorithm is robust to different video backgrounds. The number of rolls metrics were used to analyze suturing performance in the …

Basic Safety Message Generation Through A Video-Based Analytics For Potential Safety Application, Abyad Enan

All Theses

With the advancement of modern artificial intelligence techniques, computer vision can play a vital role in enhancing roadway safety by reducing the risk of imminent collisions. To do so, a vision-based safety application is required, where a roadside camera can monitor the roadway traffic and predict potential risks of crashes in real-time. If any risky situation or behavior is observed that may lead to a crash, then a safety application can send warnings to the vehicles at risk. For vision-based safety applications on a roadway section, it is important to accurately monitor each vehicle’s location, speed, acceleration, heading direction, etc. …

Pressureless Sintering Of Sic - Oxide Multiphase Ceramics For Protective Coating Applications, Reilly Boros

All Theses

For hydrogen-fueled combustion, there exists a demand to improve coating materials that are capable of protecting SiC_f/SiC CMC turbine material. Promising coating materials must be able to shield from harsh oxidation while working at extremely high temperatures. The work presented in this thesis aims to expand the understanding of two promising material systems for integrated environmental barrier coating (EBC) – thermal barrier coatings (TBC) by fabricating bulk composite ceramic samples and performing characterization to further understand their sintering behaviors. In this study, a processing procedure to consistently produce dense composite ceramics of PDC SiC – Y₂Si …

Collision Hazard Prevention And Notification For Construction Worker Safety Using Audio Surveillance, Kehinde Elelu

All Dissertations

The construction industry faces significant safety challenges, with collision hazards ranking as the second highest cause of annual fatalities and injuries in the United States, as reported by the Occupational Safety and Health Administration (OSHA). Current collision detection methods predominantly rely on proximity technologies, which necessitate costly and complex installations on each construction equipment piece. Furthermore, auditory situational awareness declines among workers due to hearing loss and intricate construction noises, which further heightens collision risks. This research introduces an innovative, low-cost, audio-based collision prevention technology aimed at enhancing auditory situational awareness for construction workers exposed to high noise levels. The …

Sustainable And User-Driven Scope Development Framework For Engineering Design Services Of Transportation Infrastructure Projects, Ahmad Zaki Ghafari

All Dissertations

Rapid economic growth has led to a significant increase in transportation demands, exerting unprecedented pressure on infrastructure systems in the United States. State transportation agencies play a vital role in maintaining and developing transportation infrastructure networks within their regions. State transportation agencies face immense pressure from federal and state governments, elected officials, and the public to deliver projects efficiently and within budget. State transportation agencies rely on professional consultants for engineering design services. Engineering design services for transportation infrastructure projects are delayed due to incomplete inaccurate scope. For state Department of Transportation (DOTs), a streamlined scope development process is essential …

Magnetic Resonance Imaging Trackable Pathology-Triggered Polymersomes Toward Enzyme Replacement Theranostics For Gm1 Gangliosidosis, Dorian Foster

All Dissertations

This dissertation investigates the development and optimization of pathology-responsive polymersomes for simultaneous enhanced magnetic resonance imaging (MRI) and enzyme replacement therapy (ERT) in the treatment of GM1 gangliosidosis (GM1). While therapeutic strategies exist for similar, non-neuropathic lysosomal storage disorders, implementation towards GM1 faces significant challenges due to the blood-brain barrier.

Herein, we developed and characterized a range of low molecular weight hyaluronic acid-b-polylactic acid (HA-PLA) polymersomes (PSs) capable of encapsulating therapeutic enzymes in their hydrophilic core. These polymersomes exhibit pathophysiology-triggered responsiveness, degrading in the presence of acidic conditions, which is characteristic of lysosomes, and enzymes such as hexosaminidase A, which …

Nlp-Based Quantitative Methods For Measuring Highway Project Similarity To Support Project Clustering And Bundling, Quan Do

All Dissertations

State highway agencies (SHAs) often need to classify similar projects into distinct work type clusters, enabling them to correlate new projects with historical data on cost, schedule, pay item production rates, and project complexity. This classification also facilitates the identification of similar projects for project bundling. However, the conventional method for classifying projects into work types is inefficient, relying heavily on subjective judgment and manual review of project scope. This inefficiency hinders SHAs’ ability to effectively apply knowledge gained from historical projects to future projects. Moreover, the subjective nature of project classification is time-consuming and can result in inconsistencies and …

Space Operations Education Research: Studying Undergraduate Experiences As Predictors Of Early Career Performance For Military Space Operations Officers, Keith Balts

All Dissertations

Undergraduate students who go on to operate space systems, e.g., satellites, launch systems, and ground-based systems, come from a diverse set of demographics and undergraduate experiences. The United States Space Force (USSF), and United States Air Force (USAF) before them, like many professions, have a demonstrated interest in who enters their ranks, but have had limited research available to them to inform their recruiting, selection, training, and early career development policies and processes.

This Profession-Based Education Research study, a term introduced here in contrast to Discipline-Based Education Research, focused on the military space operations profession. This study analyzed newly commissioned …

Regulating Cox Conversion Through Catalyst Design And Reaction Energy Input, Ewa Chukwu

All Dissertations

Carbon dioxide (CO₂) emissions, primarily from fossil fuel use in energy and chemical production, are the leading driver of global warming. The chemical industry is the third-largest source of these emissions, so reducing its carbon footprint—and ultimately achieving “CO₂ emissions-free” chemical manufacturing—is critical to combating global warming. Thermal catalysis is the workhorse of industrial chemical manufacturing, generating CO₂ emissions from two main sources: the actual chemical transformations of fossil feedstocks and burning of fossil fuels to provide the process heat. Therefore, developing and implementing technologies to mitigate the carbon emissions associated with these emissions sources is essential for decarbonizing the …

Modeling Instrument Design Risks In Medical Device Reprocessing, Manuel Andres Gutierrez

All Dissertations

Medical device reprocessing is an essential practice in healthcare delivery. While FDA regulations require device manufacturers to develop and validate reprocessing procedures, the increasing complexity of medical device designs and their use environments can increase the risks of inadequate reprocessing and associated device malfunctions and potential patient injury. While some design features present known difficulties for reprocessing, critical information needed to define relative risks or feature-specific parameters that increase or decrease risks of inadequate reprocessing is lacking. There is an urgent need for tools to quantify and predict reprocessing risks associated with design features used in surgical instruments.

The broad …

Deformation Mechanism In Gold Nanoparticles Under Compressive Loading: Insights From Atomistic Modelling And Unsupervised Machine Learning, Tanuj Gupta

All Dissertations

Gold nanoparticles (AuNPs) offer exciting possibilities due to their inertness, malleability, and tunable structures, making them valuable for applications ranging from nanomedicine to electronics. Their optical, mechanical, and other properties can be tailored by modifying shape and structure, underscoring the importance of understanding their deformation behaviour at the nanoscale. This study used classical molecular dynamics simulations with LAMMPS to investigate the deformation mechanisms of gold nanospheres (AuNS) under uniaxial compression. Employing the embedded atom method (EAM) potential to model atomic interactions, AuNS with 20 nm in diameter were compressed along the z-direction using planar indenters moving at a constant …

Neural Operator And Physics-Informed Deep Learning Approaches For Inverse Design Of Composites And Manufacturing Processes, Minglei Lu

All Dissertations

In this dissertation, artificial intelligence (AI) models are designed and used to accelerate inverse design of composites and manufacturing processes. The critical bottlenecks in machine learning (ML) including data availability, data quality, model generalization and adaptation, interpretability, physical consistency, and the ’black box’ nature of models for the inverse design are addressed. And the proposed AI models are tested under different engineering scenarios. Firstly, a fast deep neural operator (DNO) structure was developed to significantly reduce training time. This model was tested in the context of additive manufacturing, a transformative industrial technology that allows for the creation of materials with …