Digital Commons Network^™

Hydrodynamics Of Perforated Heave Plates, Muhammad Usman

All Dissertations

Ocean waves are a clean and renewable energy source that can help reduce dependence on fossil fuels and combat climate change. To capture this energy, researchers have developed devices known as wave energy converters (WECs). One common type, called a two-body point absorber WEC, uses a buoy floating on the ocean surface connected to a submerged reaction plate, known as the heave plate, which lies underwater. The relative up-and-down motion between the buoy and the heave plate, driven by ocean waves, generates usable power via a power take-off (PTO) system. Traditionally, these submerged heave plates are solid structures. However, this …

Opposed-Piston Two Stroke Engine As A High Power Density Solution In Heavy Duty Applications: An Experimental Evaluation With Diesel And Ethanol, Ankur Bhatt

All Dissertations

With an increasing demand to reduce greenhouse gas (GHG) emissions, the conventional powertrain technology is at a saturation point. There is reinvigorated research interest in alternative powertrain designs that offer potentially higher efficiencies and lower engine-out emissions compared to conventional powertrains. The opposed piston two-stroke (OP2S) engine is one such alternative engine architecture that has demonstrated a reduction in engine-out emissions and increased efficiency compared to conventional four-stroke diesel engines. Like any two-stroke engine, the scavenging process and the composition of the internal residuals are predominantly governed by the pressure differential between the intake and the exhaust ports. Without dedicated …

Thermal Management Of Power Electronic Converters In Electric Motor Drives Using Active Thermal Control And Active Cooling, S M Imrat Rahman

All Dissertations

The application of power electronic converters (PEC) in electric vehicles (EVs) has significantly increased due to their enhanced controllability and flexibility. Additionally, Permanent Magnet Synchronous Machines (PMSMs) are favored in EVs for their higher torque, efficiency, performance, and heat dissipation capabilities compared to asynchronous machines. The reliable operation of power converters in PMSM drives is crucial for EV operation, and this is driving interest in developing innovative and sustainable technologies that ensure the safe and reliable functioning of PECs. One of the main challenges in achieving reliable PECs is designing effective thermal management systems to control junction temperature and reduce …

Machine Learning-Enabled Safety-Critical Model Predictive Control For Uncertain Dynamical Systems, Hossein Nejatbakhsh Esfahani

All Dissertations

This dissertation explores the interactions between Model Predictive Control (MPC), Safety-critical Control, and Artificial Intelligence (AI)/Machine Learning (ML) methods, with a particular focus on Reinforcement Learning (RL) and Bayesian Optimization (BO). We then leverage AI/ML to address several challenges in the control design and safe operation of uncertain dynamical systems. In many applications, ranging from autonomous vehicles and robotics to energy systems and industrial processes, ensuring safety is as essential as satisfying control objectives. The use of Control Barrier Functions (CBFs) within the MPC framework recently has emerged as a powerful tool to guarantee safety by enforcing constraints in optimal …

Reverse (Bio)Engineering: A Machine Learning Approach To Optimize Baseball Pitcher Health And Performance, Robert C. Moore

All Dissertations

Ball tracking systems are becoming ubiquitous in sport, creating an unprecedented opportunity for big data applications to optimize human health and performance. These applications are especially common in baseball, a sport known for analyzing ball flight data to quantify performance. Analysts routinely use ball flight data to identify the attributes of top performing pitchers, finding that the best pitchers throw with optimal combinations of release speed and spin to precise locations. However, for certain pitchers, the throwing motion required to produce optimal ball flight places exceedingly high biomechanical load on the elbow, and consequently injury rates continue to rise. This …

Legitimacy, Learning, And Launch: Exploring Relationships, Community, And Connection In An Undergraduate Research Experience, Randi J. Sims

All Dissertations

Undergraduate research experiences (UREs) are critically important methods for integrating undergraduate students into legitimate scientific practices. While widely celebrated for producing positive outcomes such as increased self-efficacy, research skills, and STEM retention, less is known about the processes through which undergraduate mentees become integrated members of their research groups and the broader scientific community. This dissertation presents findings from both a systematic literature review and a quantitative ethnographic study of a biological sciences URE at a southeastern R1 predominantly white institution (PWI). Grounded in communities of practice and legitimate peripheral participation frameworks, this study explores how undergraduate researchers build relationships, …

Contributions To Statistical Modeling And Estimation Of Rainfall Intensity–Duration–Frequency Curves, Jiyun Huang

All Dissertations

Extreme rainfall can cause flooding, damage infrastructure, and create serious risks for communities. Engineers use Intensity-Duration-Frequency (IDF) curves to estimate precipitation extremes over different lengths of time, such as one hour or one day, and the average time one would expect wait for one of these events to occur. Several approaches exist for estimating IDF curves, but no single approach is known to be best in all cases. In this dissertation, I study statistical methods that aim to improve IDF curve estimation. I use the Canadian Regional Climate Model (CanRCM4) Large Ensemble, which contains 35 independent climate simulations. These simulations …

Hybrid Learning For Rough Terrain Navigation Of Actively Articulated Wheeled Vehicles, Dhruv Mehta

All Dissertations

Conventional wheeled ground vehicles have been used for rough terrain navigation in the recent years. They consist of a chassis connected to wheels through passive, semi-active, or active suspension systems. However, their fixed configurations limit mobility and maneuverability, constraining their ability to autonomously navigate diverse and rough terrains. Autonomous Ground Vehicles (AGVs) face significant challenges in this regard, including varying terrain roughness, soil hardness, and obstacle crossing.

To address these limitations, Actively Articulated Wheeled Vehicle (AAWV) architectures have recently emerged, offering real-time geometric adaptability. AAWVs have chassis and wheels connected via articulated serial or parallel linkages. However, increased articulation introduces …

Data-Driven Discovery Of Finite-Dimensional Koopman Operator For Modeling And Control Of Uncrewed Ground Vehicles, Ajinkya Joglekar

All Dissertations

This dissertation advances data-driven modeling and adaptive control techniques for Uncrewed Ground Vehicles (UGVs), with a focus on autonomy in mission-critical and safety sensitive environments. UGVs are deployed across a wide spectrum of domains, from structured manufacturing shop floors to unstructured off-road terrains, including planetary exploration, precision agriculture, and disaster response. These platforms, operating in dull, dirty, and dangerous conditions, demand autonomy that is both adaptable and robust. While traditional model-based control methods offer interpretability and robustness, they struggle with unmodeled dynamics, parameter variations, and integration of high-dimensional sensing. Conversely, modern machine learning approaches can directly exploit sensory data but …

Digital Reflections: Evaluating Body Dissatisfaction In Xr Through Eye- And Body-Tracked Virtual Humans, Deyrel Diaz

All Dissertations

In an era where digital and physical realities increasingly intertwine, the perception of body image is undergoing a significant transformation. Traditional understandings of body dissatisfaction, long studied in relation to psychological distress and eating disorders, are now being reshaped by technologies such as Virtual Reality (VR), Augmented Reality (AR), and Artificially Intelligent (AI)- generated media. These technologies have introduced novel ways of experiencing and interacting with the human form, raising critical questions about their impact on self-perception and internalization of beauty standards.

As virtual representations become more prevalent in entertainment, social media, and interactive platforms, it is becoming more crucial …

Atomic-Scale Engineering Of Dilute Pd–Cu Alloys For Selective Electrocatalytic Cox Reduction, Zehua Jin

All Dissertations

The excessive release of carbon dioxide (CO2) into the atmosphere has become a major cause of global warming and ocean acidification, threatening the sustainability of human life on Earth. To address this challenge, scientists are exploring ways to convert CO2 into useful fuels and chemicals instead of simply capturing and storing it. One promising approach is electrocatalysis, which uses electricity—potentially from renewable sources—to drive chemical reactions that transform CO2 under mild, environmentally friendly conditions.

This research aims to understand how the arrangement of atoms in metallic catalysts affects the conversion of CO2 and carbon monoxide (CO) into valuable products such …

Integrating Dft And Machine Learning To Predict Structural Properties In High Entropy Alloys, Nathan Linton

All Dissertations

In the past decade, a paradigm shift in the design of metal alloys has been observed. These new alloys are commonly referred to as high entropy alloys (HEAs), multi-principal element alloys (MPEAs), or complex, concentrated alloys (CCAs). In contrast to conventional alloys, which consist of one main element (for example 80%) with other elements in small amounts, HEAs are made of four or more main elements ranging from 5 to 35% each element. Due to the large presence of multiple elements, HEAs have shown substantial material property improvements over conventional alloys such as steel. For example, they have high ductility …

Cosmic Duets: A Search For Binary Supermassive Black Holes In Merging Galaxies, Sagar Adhikari

All Dissertations

Galaxies are vast cosmic islands of stars, dust, and gas. They come in various shapes and sizes. They might look static for the timescales we are used to, but they are dynamic and collisional systems that can merge with other galaxies to make bigger galaxies. Most galaxies, including the Milky Way, host a central supermassive black hole (SMBH) with a mass greater than a million (sometimes a billion) times the mass of the Sun. When galaxies merge, their SMBHs form a binary system before ultimately merging. These cosmic duets are of great interest to astronomers and astrophysicists as they are …

Closing The Achievement Gap: School Counselors’ Role In Enhancing College And Career Access For First-Generation Students, Conswyla J. Decoteau

All Dissertations

Professional school counselors play a vital role in supporting each student's academic, experiential, and personal growth, especially in preparing them for success in post-secondary education. Due to social, academic, and financial disadvantages, first-generation students face significant obstacles. Given that inequities persist despite efforts to improve access to higher education, this problem is important to address. To close the academic gap that first-generation students face, effective counseling programs that are sensitive to cultural differences are necessary. In order to better understand how school counselors in rural high schools may help first-generation students close the gap in access to college and careers, …

Navigating Safety: A Mixed-Methods Examination Of Supportive Workplace Practices In Maritime Contexts, Rebecca N. Pool

All Dissertations

Maritime Sailors operate in high-demand and high-risk environments that require sustained adherence to strict safety standards. Using the Conservation of Resources theory (COR), this dissertation examines how supportive workplace practices impact job stress and foster increased safety compliance among U.S. Navy personnel. Using a mixed-methods design, two studies were conducted with data from the Afloat Safety Climate Assessment Survey (ASCAS). Study 1 analyzed quantitative survey responses from active-duty Sailors (N = 15,517) nested in 1,033 departments nested within 122 ships to test a multilevel moderated mediation model linking social support, job stress, psychological safety, and safety compliance. Results indicated …

Interfaces To Enhance Performance In Human-Ai Teams Conducting Safety-Critical Military Operations: A Route Reconnaissance Use Case, Sarvesh Sawant

All Dissertations

Military teams frequently operate in hazardous and dynamic environments where they must recognize threats, act swiftly, and maintain awareness of their surroundings. To assist soldiers in identifying threats, analyzing data, and creating safer routes, Artificial Intelligence (AI) systems are being integrated into these teams. But only when humans comprehend what AI is doing, why it is doing it, and how to collaborate with it can AI be helpful in these high-stakes missions. To enhance human-AI collaboration during military route reconnaissance missions, this dissertation explores ways to improve human-AI communication. In a route reconnaissance mission, teams of soldiers must navigate through …

First Principles Calculation Of Electron-Phonon Coupling In Nonequilibrium Quantum Materials, Chendi Xie

All Dissertations

This dissertation combines first-principles computation and light-induced nonequilibrium analysis to understand and control electron–phonon coupling (EPC) and emergent many-body phenomena in quantum materials, in both equilibrium and nonequilibrium states.

Chapters 1 and 2 build the theoretical and computational foundation, beginning with electron and phonon self-energies, linewidths, and perturbation theory for EPC, followed by density functional theory (DFT) and density functional perturbation theory (DFPT), which serve as the first-principles workhorses used throughout. Chapter 3 reviews Bardeen-Cooper-Schrieffer (BCS) and Migdal-Eliashberg theory, including the BCS gap - transition temperature (T_c) relation and the strong-coupling generalization, and delineates the practical validity bound …

Particle Migration In Non-Newtonian Fluid Flows Through Curved Microchannels, Sanskruti Ramesh Raut

All Dissertations

Innovations in microfabrication over the past three decades have enabled the development of microfluidic devices with intricate channel geometry. Microfluidic platforms offer controlled manipulation of fluids and particles by leveraging the internally induced and/or externally imposed force field(s). The demand for compact microchannel geometry has turned the attention toward curved microchannels with significantly reduced footprints. However, most of the previous studies in curved microchannels have been limited to particle migration in Newtonian fluids. The influence of fluid rheology has remained largely unexplored.

In the first part of this dissertation, we present a systematic experimental study on the influences of fluid …

Accident Data Analytics And Ai-Based Auditory Enhancement For Highway Construction Safety, Thinh Nguyen

All Dissertations

This research develops data-driven and AI-enhanced approaches to improve worker safety in highway construction environments. The study integrates advanced analytics and auditory signal enhancement to identify high-risk worker behaviors and improve real-time safety warnings. The work consists of three core studies. The first study applies Sequential Pattern Mining and Social Network Analysis to more than 1,000 construction accident reports to identify high-risk worker actions and their hidden sequential relationships with accident types and consequences. These insights reveal sector-specific risk patterns, supporting the creation of targeted, data-informed safety interventions. The second study introduces an AI-based auditory enhancement model built on a …

Universal Systems Simulation Via Constraint Hypergraphs With Applications To Digital Twins, John Morris

All Dissertations

The characterization of systems encompasses a variety of modeling frameworks designed to capture specific behaviors and components of various system domains. Whatever the framework, the core elements of a system representation are the information of the system and a description of how that information is related. The relations in deterministic systems are functions, which, when composed to form executable processes, can be used to simulate system data. A declarative modeling framework is one that encodes mechanisms for preparing these simulations within the model structure, allowing an external agent to form the execution processes required for a given context. To date, …

Purifying Circular Rna Therapeutics, Karen Guillen-Cuevas

All Dissertations

Circular RNA (circRNA) has emerged as a promising therapeutic modality due to its enhanced stability and resistance to exonuclease degradation compared with linear mRNA. However, its stability and functionality depend strongly on achieving high purity, and current methods such as size-exclusion chromatography suffer from peak overlap, low yields, and poor scalability. This dissertation addresses these limitations by developing ultrafiltration-based strategies to purify circRNA directly from in vitro transcription (IVT) and self-splicing (circularization) reactions. First, the feasibility of ultrafiltration was demonstrated using polyethersulfone membranes, where sieving coefficients and critical flux values of circRNA, precursor RNA, and nicked RNA were measured to …

Exploring Glycosomes As Therapeutic Targets For Trypanosoma Brucei, Sabrina Sutton Pizarro

All Dissertations

Trypanosoma brucei is a protozoan parasite which causes human African trypanosomiasis and the livestock wasting disease, nagana. These parasites have highly specialized peroxisomes, called glycosomes, which house a variety of essential metabolic pathways, including glycolysis. Glycolysis is the sole means of energy production in the infective life stage of T. brucei making glycosomes and the glycolytic pathway promising targets for therapeutic strategies. In this work, we have studied the glycosome as a therapeutic target from multiple perspectives. The first portion of this work addresses drug trafficking. The efficacy of small-molecule inhibitors of glycosomal enzymes is restricted by the rate of …

End-To-End Direct Current For Standalone Power Network, Eyad Ahmad Aldarsi

All Dissertations

The primary issue that faces the humanity is climate change and because of that greenhouse gases (GHGs) emissions are rising. The consequences of this issue have emphasized the necessity for replacing the dominant method of electricity generation, which mostly utilizes fossil fuels, to be centered on access to all, green, low-cost, and renewable sources of energy. Currently, photovoltaics (PV) and wind turbines are the two technologies so far that can convert the source of renewable energy, which is produced by sun irradiance and wind respectively, into large-scale electric power that can be distributed into the electricity grid. The work in …

Developing American Indian/Alaska Native Children As Leaders In The Climate Movement, Joseph Burns, Alessandra Angelino, Danielle Heims-Waldron, Allison Empey, Jason Deen

Journal of Youth Development

American Indian/Alaska Native (AI/AN) voices are critical in the climate movement, as numerous social drivers have rendered these communities particularly vulnerable to the consequences of environmental change. In recent years, specific events, including the Dakota Access Pipeline, have galvanized AI/AN youth, who have been increasingly involved as leaders in the climate movement both in the United States and internationally. This yields a significant opportunity to promote leadership development for Indigenous youth, both through local, national, and international organizing and through curricular development to spark interests in environmental science. This review aims to discuss the role of AI/AN youth leadership in …

Diabetes-Induced Mitral Valve Degeneration: Tissue-Engineered Solutions And Antioxidant Therapy, Samantha Hahn

All Theses

Mitral valve (MV) fibrosis is a progressive pathological condition characterized by leaflet thickening and stiffening, ultimately compromising valve function. This process is accelerated in diabetes, where chronic hyperglycemia elevates reactive oxygen species (ROS) and alters the mechanics of the extracellular matrix (ECM), collectively promoting the activation of valvular interstitial cells (VICs). Under healthy conditions, VICs maintain a quiescent, fibroblast-like phenotype responsible for sustaining ECM homeostasis. However, pathological biochemical cues or mechanical stress drive VICs toward a myofibroblast phenotype. While this transformation is essential for short-term repair, its persistence contributes to maladaptive MV remodeling and fibrosis. Diabetic stressors may be mitigated …

Fall 2025 - Volume 35, Number 2

CompassPoint

No abstract provided.

Spatially Mapped Statewide Estimated Potential Evapotranspiration Using An Efficient Surface Interpolation Method: A Case Study Of South Carolina, Sudhanshu S. Panda, Devendra M. Amatya, Ka Kit Liu, Augustine Muwamba, Timothy J. Callahan

Journal of South Carolina Water Resources

Potential evapotranspiration (PET) exhibits substantial spatial and temporal variability across large landscapes, necessitating site-specific estimation for accurate environmental and water resource assessments. However, obtaining PET or ET data for specific locations across an entire state remains challenging due to the limited number of weather stations and associated environmental datasets. This study aimed to develop an automated geospatial modeling framework to map PET distribution across South Carolina, USA, using PET estimated by the temperature-based Hargreaves–Samani (H–S) method with daily weather data from 59 NOAA stations. Because the accuracy of spatial interpolation depends on both the target variable and the desired spatial …

Multiscale 3d Whole Joint Cellular And Molecular Mapping Reveals Disease-Specific Neurovascular Plasticity Underlying The Structure-Pain Relationship, Peng Chen, Jiaxin Chai, Abirami Soundararajan, R. Glenn Hepfer, Benjamin Kheyfets, Jiaxin Hu, Ishraq Alshanqiti, Swarnalakshmi Raman, Ikue Tosa, Jun Tae Huh, Matthew Yee, Brooke J. Damon, Shangping Wang, Yu Shin Kim, Man-Kyo Chung, Mildred C. Embree, Janice S. Lee, Tong Ye, Hai Yao

Publications

Understanding musculoskeletal joints from a 3D multiscale perspective, from molecular to anatomical levels, is essential for resolving the confounding relationships between structure and pain, elucidating mechanisms regulating joint health and diseases, and developing new treatment strategies. Here, a musculoskeletal joint immunostaining and clearing (MUSIC) method specifically developed to overcome key challenges of immunostaining and optical clearing of intact joints are introduced. Coupled with large-field light sheet microscopy, this approach achieves 3D high-resolution, microscale neurovascular mapping within the context of whole-joint anatomy without the need for image coregistration across various joints, including temporomandibular joints, knees, and spines, and multiple species, including …

Truck Drivers And Autonomous Trucks: A Topic Modeling Analysis Of Truck Driver Posts, Noah Britt, Amy M. Schuster, Shubham Agrawal, Chu-Hsiang Chang, Jenna A. Van Fossen, Elizabeth A. Mack, Sheila R. Cotten

Publications

Social media provides a rich, alternative data source to interviews or survey-based research to study hard-to-reach populations (e.g., truck drivers, because of their transient work structure and unique subculture). This study uses public social media posts from the largest trucking forum in the United States to examine truck drivers’ views on autonomous trucks (ATs), which are poised to transform the trucking industry. We expand on traditional qualitative strategies of analyzing social media data by combining newer methods, including BERT-based topic modeling, sentiment analysis, stance detection, emotion analysis, topic similarity, and location analysis through a social interaction network, to analyze a …

Detection And Classification Of Invasive Callery Pear From Multisource Satellite Imageries In Google Earth Engine, Kavi Raj Awasthi, Nilesh Timilsina, Denita Hadziabdic, Federico Iuricich, William E. Klingeman, Marcin Nowicki, Brook T. Russell, Jessica A. Hartshorn

Publications

Assessing the spatial distribution of invasive species is a critical component for establishing baselines to examine the rate of spread, documenting key areas where negative impacts on ecosystems can be mitigated, and developing sustainable management strategies. Callery pear (Pyrus calleryana Decne.; PC) is a rapidly spreading invasive woody plant species in the eastern United States (U.S.). The incursion of these wild-type trees into urban, peri-urban, and rural landscapes, which have escaped from transplanted clonal cultivars, poses complex management challenges for land managers and hampers ecosystem function by competing with native plant species and altering the forest environment. We integrated …