Digital Commons Network^™

Reevaluating The Van’T Hoff And Arrhenius Equations: How Temperature And Pressure Affect Chemical Reaction Thermodynamics, Equilibrium, And Kinetics, Jianmin Wang

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

The van’t Hoff equation, which is used to calculate the effect of temperature on equilibrium constants, was derived from the Gibbs – Helmholtz equation that relates the molar Gibbs free energy to the molar enthalpy of a chemical reaction. However, the Gibbs – Helmholtz equation was developed for systems that do not consider contributions of Gibbs free energy from chemical species. Consequently, the van’t Hoff equation and the Arrhenius equation derived from it are technically incomplete.

By employing Hess’s law and the appropriate Gibbs free energy equation for chemical reaction systems, this investigation develops theoretical equations to calculate the effects …

Resilient Power System Load Frequency Control, Ghadeer Ahmed Almahri

Theses

Standard frequency and voltage levels need to be maintained when the electric power system is running in order to keep it in a satisfactory state of operation. Between AC power generation and use, there should be a balance between active and reactive power. However, due to variations in active and reactive power requirements, the frequency and voltage provided may fluctuate from their rated values. Any unwelcome change in frequency or voltage can have an immediate effect on how the power system operates and may even cause harm to linked devices. These parts are intended to operate at certain rated frequencies …

Conversion Of Orange Waste To Chemically Modified Activated Carbon Adsorbent Materials For Aqueous Phase Phosphate Removal, Sierra Mugan

Electronic Theses and Dissertations 2020 - Present

Phosphorus pollution in surface waters drives harmful algal blooms, creating ecological, public health, and economic risks. This study examined citrus processing waste as a sustainable, low-cost precursor for producing chemically modified adsorbents for phosphorus removal. Orange waste was pyrolyzed, resulting in a carbon-rich material with low ash content, as confirmed by thermogravimetric analysis. The material was modified using lanthanum chloride, iron (III) chloride, and calcium chloride at varying mass ratios and screened under standard conditions (1 mg P/L, 1 g/L dosage, 24-hour contact time). Lanthanum- and iron-modified samples demonstrated the best removal efficiencies and underwent further evaluation. The lanthanum-modified sample …

Beneficent Artificial Intelligence In The Age Of The Thing: A Case Study Of The Palm Beach County Library System, Philip J. Smith

Electronic Theses and Dissertations 2020 - Present

With this thesis, I explore how Palm Beach County Library System administration and the broader county government are managing the advance of artificial intelligence and seeking actionable resolutions to the artificial intelligence dilemma. Due to power differentials, triangulation required me to adopt a humanist, perspectival approach. I collected data from participant observations, reflective fieldnotes, literature review, and transcription of an interview, all of which informed my interpretations. Albeit colored by past experiences, I relate my professional familiarity in a customer service training role and express the importance of engaging patron experience that is service-oriented, ongoing training intended to recenter the …

Examining The Relationships Among Land Surface Temperature, Surface Urban Heat Islands, Land Cover, And Societal Impacts In The Miami Metropolitan Statistical Area, Alanna D. Shapiro

Electronic Theses and Dissertations 2020 - Present

Surface Urban Heat Islands (SUHI) and Land Surface Temperature (LST) are important to study because they can have large impacts on human and environmental health and well-being. The research described in this dissertation includes three separate but related studies of SUHI and LST. The first study evaluates historic LST trends in a multiscalar view and examines the impact of environmental and socioeconomic explanatory variables on LST. Results show that NDVI and impervious surfaces are significant explanatory variables for the dependent variable LST. The rate of change (RoC) of each of the regression models ranges between 0.29oC/decade and 1.56oC/decade. The second …

Materia Non Medica: Reading Disability And Medical Narratives In The Daughter Of Doctor Moreau, Jessica Elizabeth Young

Electronic Theses and Dissertations 2020 - Present

This thesis presents a close reading of The Daughter of Doctor Moreau by Silvia Moreno-Garcia, engaging Indigenous studies and disability studies to illuminate how the novel interrogates embodiment, medical authority, and human difference. By situating the text within historical frameworks of medicine and corporeality in Mexico, and alongside speculative modes that seek to recuperate non-Western epistemologies, the analysis reveals how Moreno-Garcia reimagines the body as mutable, relational, and politically charged. The narrative’s hybrid characters and transgressive identities offer a generative lens through which to explore bodily variance, not as deviation, but as a site of possibility. Ultimately, this thesis argues …

Exploring The Role Of Online Discussion Forums In Endorsing Egyptian Undergraduates’ Efl Learning, Wesam Khairy Morsi

English Language and Literature

eLearning Management systems (eLMS) are software applications used in universities worldwide to implement specific educational goals. eLearning platforms have several features that support traditional Face to Face (FTF) teaching and provide valuable opportunities for independent, self-paced learning. One of these features is the Online Discussion Forums (ODFs). This research paper investigates the role of ODFs in endorsing English as a Foreign Language (EFL) learning by examining students' perceptions of its accessibility, peer/instructor interaction, assessment criteria, and discussion topics. The paper also investigates the influence of gender on students' perceptions of the role of ODFs. This is a non-experimental research design, …

Predicting Bus Ridership In Dubai Using Advanced Machine Learning Models, Fatma Almheiri

Theses

In rapidly urbanizing cities, the public transport systems have to be efficient and reliable with proper demand forecasting to guarantee customer satisfaction. This paper explores how evidence-based machine learning tools can be used to forecast weekly bus ridership in Dubai, using a dataset of more than 10 million trip-level boarding observations between June 2013 and July 2014. It was aggregated to 25,195 route-week observations, and preprocessed with temporal feature engineering, lag variables and rolling statistics. Three predictive models have been tested: Linear Regression (as a baseline), Random Forest and XGBoost (as an ensemble method). Mean Absolute Error (MAE), Root Mean …

On High-Speed Breakup Of Water Droplets Behind High Mach Number Shocks, Sydney M. Briggs

Graduate Thesis and Dissertation post-2024

Water droplet breakup in high-speed flow is a relatively popular experimental study to analyze breakup mechanisms. There is a plethora of experiments performed at low Mach number and low Weber number, but studies with higher speed flows and higher Weber numbers are less common. In this study, water droplet breakup is assessed using high-speed shock waves (Mach 2.3-above Mach 5) in a shock tube. Multiple methods are used to introduce droplets, and multiple different water purity levels are considered. An assessment was made into whether cavitation played a role in the breakup process physically, as this has been a budding …

Mechanistic Insights Into The Antimicrobial Action Of Fungus-Derived Xanthoquinodins Against Clostridioides Difficile, Erika A. Serravalle

Graduate Thesis and Dissertation post-2024

The bacterial pathogen Clostridioides difficile is the leading cause of antibiotic- and healthcare-associated diarrhea, imposing significant clinical and economic impacts. The emergence of hypervirulent strains, such as PCR ribotype 027 (RT027), has exacerbated disease severity, recurrence rates, antibiotic resistance, and epidemiological spread. Expanding resistance profiles among C. difficile strains continue to limit the effectiveness of current IDSA-SHEA recommended therapies, which are already compromised by high recurrence rates due to antibiotic-induced disruption of the gut microbiota. These challenges highlight the urgent clinical need to identify and characterize antimicrobial compounds targeting alternative pathways in C. difficile physiology. We report the discovery and …

Development Of Generalizable Data-Driven Traffic State Prediction Solutions: A Comprehensive Approach, Md Mobasshir Rashid

Graduate Thesis and Dissertation post-2024

Increased urbanization and population growth lead to more traffic in the transportation system, causing severe congestion. Particularly during disruptive events such as hurricanes or traffic incidents, the traffic flow in the network worsens significantly. As a result, there is a need for data-driven traffic prediction models to reduce congestion in real-time, and the prediction model should be generalizable to be applicable across different dynamic scenarios. Additionally, a robust and adaptable traffic prediction model can help traffic managers to take proactive actions to optimize traffic flow. However, the majority of data-driven traffic prediction models suffer from limited applicability as they are …

Towards Supporting Undergraduate Students To Become Lifelong Learners: A Multimethod, Multimodal, And Multigranular Analysis Of Motivation And Self-Regulated Learning In Context, Sierra Outerbridge

Graduate Thesis and Dissertation post-2024

This publication-based dissertation includes three manuscripts with distinct statistical methods to investigate self-reported motivation, self-reported self-regulated learning (SRL), and enacted SRL processes in undergraduate student contexts towards understanding how students learn how they learn.

The first manuscript focused on 1248 undergraduate statistics students, utilized self-reported motivation, and interpreted logfile data of time spent within an online textbook through the lens of SRL using hierarchical cluster analysis followed by k-means cluster analysis to identify four distinct motivation clusters. Results from a repeated measures ANOVA suggest that students did not spend time differently within the textbook, whereas there were differences between motivation …

Deep Reinforcement Learning-Based Optimal Takeoff Trajectory Design Of An Evtol Drone, Nathan M. Roberts, Bingling Huang, Xiaosong Du

Mechanical and Aerospace Engineering Faculty Research & Creative Works

The continuing development of electric vertical take-off and landing (eVTOL) aircraft presents promising opportunities to alleviate transportation congestion. However, designing and executing takeoff trajectories that optimally balance energy usage, passenger comfort, and aircraft constraints remains challenging. Conventional design optimization provides a solution for pre-defined flight conditions and environments but is not ideal in real-world applications. In contrast, deep reinforcement learning (DRL) implements optimal policy making real-time decisions with no assumption of mathematical models. Seeing the lack of literature on DRL-based takeoff trajectory design of eVTOL aircraft, we implement and conduct DRL-based optimal takeoff trajectory designs for the Airbus³ Vahana …

Industry 5.0, Human–Machine Interface, And Smart Manufacturing In Additive Manufacturing—A Recent Trend, Atiqur Rahman, Md Hazrat Ali, Muhammad Arif Mahmood, Frank Liou

Mechanical and Aerospace Engineering Faculty Research & Creative Works

The emergence and importance of Industry 5.0 are transforming production by integrating smart technology with human creativity and intelligence, especially in advanced additive manufacturing. This critical review precisely analyzes the function of human–machine interfaces (HMIs) in enhancing additive processes, emphasizing their incorporation into smart manufacturing systems and hybrid manufacturing methods, including material extrusion (MEX), laser powder bed fusion (LPBF), and directed energy deposition (DED). It also evaluates artificial intelligence (AI), the Internet of Things (IoT), and cybersecurity, which enhance HMIs in process monitoring, operation, and system adaptability. This study aims to provide a critical analysis and future research direction on …

Large Language Models And Networks: Edge Proposal, Synthetic Corpora, And Adaptive Node Generation, Nathan Gonzalez

Graduate Thesis and Dissertation post-2024

Natural Language Processing (NLP) and Artificial Intelligence (AI) have evolved from brittle rule-based engines through data-driven statistical models to today’s transformer architectures whose multi-head attention enables rich contextual reasoning. Against this backdrop, this dissertation unifies three complementary investigations that deepen our understanding of how large language models (LLMs) can reason over, generate, and strategically adapt language within networked settings. First, instruction-tuned LLMs are recast as latent-relationship detectors: by prompting models to hypothesize links between text-described entities, we recover edge sets that reconstruct social, thematic, and citation graphs with high precision, revealing how attention distributions encode topological cues. Recognizing the difficulty …

Modeling Frameworks To Understand And Predict Land Use Type And Land Value Patterns In Florida, Lauren Hoover

Graduate Thesis and Dissertation post-2024

Florida’s population has been rapidly growing, with a 14.6% growth in population from 2010 to 2020. This growth in population has led to an associated increase in demand for housing and commercial establishments, which have resulted in changes in land use patterns across the state. For this dissertation, we focus on methods to qualitatively and quantitatively examine how land use patterns are likely to evolve under the expected scenario of population growth in Florida while explicitly allowing for interactions between demographics, transportation and land use patterns. In our first objective we build a simulation framework to predict land use evolution …

Printability And Phase Transformation Of Selected Alloys Additively Manufactured By Laser Powder Bed Fusion, Thinh Huynh

Graduate Thesis and Dissertation post-2024

The integration of laser powder bed fusion (LPBF) to produce critical engineering components, aimed at achieving reduced weight and enhanced efficiency, has sparked significant interest in the field of additive manufacturing (AM). LPBF is highly desirable due to its rapid production capabilities, minimized material waste, and its ability to facilitate intricate engineering designs. The ongoing challenges associated with processing metals free of cracks while attaining high relative density remain central to advancing AM technology. This has led to a continued interest in alloy development for LPBF given the limited selection of alloys currently available. This study seeks to evaluate the …

Analysis Of An Aero-Engine Using Ammonia As A Fuel Carrier, Kangana Patel

Graduate Thesis and Dissertation post-2024

Numerous studies in the literature have explored the decarbonization of aviation. Some opt for sustainable aviation fuels (SAF), while others propose Hydrogen(H₂). Recent studies have also investigated Ammonia (NH₃) as a potential hydrogen fuel carrier. This study of NH₃ as a viable alternative fuel could help reduce overall emissions and overcome the challenges of H_2, which is highly flammable and difficult to store. This study aims to develop a core-engine model in a system simulation software called Simcenter Amesim. Results show a reasonable similarity between jet-A fuel and NH₃ cracked H₂ within …

A Unified Thermodynamic Framework For Regime Discovery, Entropy-Aware Optimization, And Emergent Leadership In Flocking Systems, Victor Nkwocha

Graduate Thesis and Dissertation post-2024

This thesis presents a unified framework for modeling, optimizing, and analyzing collective behavior in flocking systems through a thermodynamic and statistical lens. In the first study, we employ entropy-regularized Gaussian Mixture Models (GMM) to identify distinct thermodynamic regimes—ordered, transitional, and disordered—based on the energy and entropy profiles of simulated agent-based flocks. The second study introduces the Organic Adaptive Flocking Algorithm (OAFA), a biologically inspired, entropy-aware extension of the Boids model. OAFA dynamically adjusts rule weights based on local entropy signals and is optimized via a multi-objective NSGAII framework to balance cohesion, separation, energy efficiency, and disorder. Results show that entropy …

Critical State-Based Study On Deformations Due To Construction Activities And Blast Densification, Jorge Enrique Orozco-Herrera

Graduate Thesis and Dissertation post-2024

The behavior of geo-structures and foundation systems in densely populated urban areas relies on the successful performance of the supporting soils when subjected to static (e.g., the weight of the structure or service loads) or dynamic (e.g., earthquake-induced ground motions, construction-induced vibrations, wind loads, or traffic) loading scenarios. Construction-related activities and ground improvement operations can also be responsible to alter the stress-strain-strength behavior of supporting soils by causing vibration-induced ground deformations, excessive vibrations, or mobilizing soil shear strength in relation to in situ or as-built conditions. Construction-related activities and ground improvement operations such as blast densification trigger complex dynamic input …

Computational Methods For Population Genetic Inference Using Identity By Descent And Local Ancestry, Yuan Wei

Graduate Thesis and Dissertation post-2024

Identity by descent (IBD) and local ancestry are essential for population genetic inference, such as understanding genealogical relationships and demographic history through genomic data. With the availability of large and high-resolution datasets, new opportunities and computational challenges are brought for efficient and accurate methods to infer IBD segments and local ancestry. This dissertation presents three computational methods designed to assist in population genetic inference. First, RaPID-Query is introduced to efficiently query IBD segments for individual haplotypes over a large genotype dataset. This method is based on the positional Burrows-Wheeler transform (PBWT) algorithm and utilizes a random projection approach. RaPID-Query is …

Carleman Linearization Of Dynamical Systems, And Graph Inverse And Wiener Filtering, Cong Zheng

Graduate Thesis and Dissertation post-2024

Carleman linearization is a mainstream approach for transforming finite-dimensional nonlinear dynamical systems into infinite-dimensional linear systems. It provides accurate approximations of the original nonlinear system over larger regions around the equilibrium for longer time horizons, surpassing the capabilities of conventional first-order linearization. In Chapter 1, we derive explicit error bounds for the finite-section approximation, demonstrating its exponential convergence concerning the finite-section order. We illustrate that for a specific class of nonlinear systems, exponential convergence can be achieved across the entire time horizon, extending to infinity. These results hold significant practical utility, as the proposed error bounds can be used to …

Characterization, Imaging, And Modeling Of Thermal Dynamics And Failure Mechanisms Of Quantum Cascade Lasers, Alejandro M. Villalobos Meza

Graduate Thesis and Dissertation post-2024

As advancements in Quantum Cascade Laser (QCL) technology continue to push the upper limits of continuous-wave performance, effective thermal management remains at the forefront of design considerations. The compact and highly tunable active region that has made QCL technology so attractive also imposes challenges to heat dissipation during continuous wave operation. To address this ongoing challenge, this work demonstrates a set of characterization and modeling techniques which can be used to interrogate different aspects of the thermal and structural properties of QCLs. Emphasis is placed on a suite of electron microscopy techniques and their role in providing a window into …

Anisotropic Third-Harmonic Vortex Beam Generation With Ultrathin Germanium Arsenide Fork Gratings, Jayanta Deka, Jie Gao, Xiaodong Yang

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Optical vortices have the tremendous potential to increase data capacity by leveraging the extra degree of freedom of orbital angular momentum. On the other hand, anisotropic 2D materials are promising building blocks for future integrated polarization-sensitive photonic and optoelectronic devices. Here, highly anisotropic third-harmonic optical vortex beam generation is demonstrated with fork holograms patterned on ultrathin 2D germanium arsenide flakes. It is shown that the anisotropic nonlinear vortex beam generation can be achieved independent of the fork grating orientation with respect to the crystallographic orientation. Furthermore, 2D fork hologram is designed to generate multiple optical vortices having different topological charges …

Integration Of System Dynamics And Agent-Based Simulation To Emulate Cyberattacks In An Iot-Based Smart Grid, Francisco Valdez

Graduate Thesis and Dissertation post-2024

The electric power grid is a cyber-physical system (CPS) that plays a fundamental role in modern society. With the integration of renewable energy sources and advanced communication technologies, Smart Grids (SGs) can enhance both the profitability and reliability of the electric power system. The communication network that interconnects numerous remotely distributed generators, devices, and controllers plays a vital role in grid control, and current trends favor the widespread adoption of Internet of Things (IoT) devices. However, this network is inherently vulnerable to cyberattacks. This dissertation presents a hybrid methodology to model and analyze the dynamic behavior of an electrical Smart …

Holographic Optical Elements For Complex Beam Transformations, Shaghayegh Yaraghi

Graduate Thesis and Dissertation post-2024

In this thesis, we explore the design, fabrication, and application of volume holographic phase elements in photo-thermo-refractive (PTR) glass for two key purposes: expanding the eye-box in augmented reality (AR) displays and controlling optical angular momentum (OAM) modes in laser cavities.

Encoding complex phase structures in PTR glass enables efficient beam shaping, multiplexing, and wavefront engineering, offering strong potential in AR displays, optical communications, and structured light. Holographic optical elements (HOEs) recorded in PTR glass exhibit high diffraction efficiency (over 99%), thermal stability, and chemical durability. Combined with low absorption and scattering in the visible and near-IR, these features make …

Shock Tube Droplet Breakup Experiments Facilitated By Acoustic Levitation, Anthony J. Aguilera

Graduate Thesis and Dissertation post-2024

Droplet introduction methodology in a shock tube differs based on the experimental conditions. For experiments in which the objective is to image droplet breakup, acoustic levitation allows for a consistent droplet shape and for diagnostic equipment to be aligned to a droplet prior to an experiment. A levitator was designed and used in the University of Central Florida’s shock tube facility. Polystyrene doped droplets were levitated to increase the likelihood of cavitation occurring. Multiple droplets were impacted by a shock wave, and the breakup regime was captured using a high-speed camera.

Thermo-Rheological And Tribological Properties Of Low- And High-Oleic Vegetable Oils As Sustainable Bio-Based Lubricants, Abiodun Saka, Tobechukwu K. Abor, Anthony C. Okafor, Monday U. Okoronkwo

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Vegetable oil-based lubricants have attracted increased research attention in recent decades as sustainable alternatives to conventional petroleum-based lubricants in metal machining. However, more studies are required to fully elucidate the thermo-rheological and tribological properties. This study presents an investigation of the thermo-rheological and tribological properties of different vegetable oils, including low- and high-oleic soybean oil, high-oleic sunflower, safflower, and canola oils. The lubricity, and evolution of viscosity and thermodynamic properties as a function of temperature were investigated to obtain important parameters including the viscosity index, flow behavior index, flow activation energy, specific heat capacity, thermal conductivity, coefficient of friction, contact …

Examining Information Flows Within Transformer Models Using Transfer Entropy, Clayton Barham

Graduate Thesis and Dissertation post-2024

The rapid growth of artificial intelligence, in terms of both power and prevalence, motivates the need for new ways to study explainability in deep neural networks. This is especially true for transformer architectures and large language models, which are the driving force behind the current surge in artificial intelligence. The complexity of transformer architecture foils many pre-existing methods for studying explainability in deep neural networks. To address this gap in knowledge, this dissertation proposes a new method of studying explainability in transformer architectures that leverages insights from neuroscience, employing transfer entropy to map information flows between components of the transformer …

High-Efficiency Dual Active Bridge Converter With Stacked Secondary Phase For Next-Generation Ai Data Center Power Delivery, Anirudh Ashok Pise

Graduate Thesis and Dissertation post-2024

The rapid electrification of hyperscale AI data centers is accelerating a shift from legacy 48 V distribution ladders to ±400 V high-voltage DC backbones, concentrating residual loss and dynamic stress on a single isolated bidirectional interface. This work presents a high-density Dual Active Bridge with Stacked Secondary Phasing (DAB-SSP) architecture as a scalable GaN-based solution for 48 V–800 V rack-level power conversion. By stacking 400 V secondaries, the topology leverages 650 V GaN devices while satisfying 800 V system requirements, reducing clearance and creepage distances, minimizing magnetic path lengths, and embedding leakage inductance necessary for wide-range zero-voltage switching.

A rigorous …