Engineering Commons^™

Advances, Limitations, And Future Perspectives In 3d Printing Of Porous Glasses: A Technical Note, Hamed Bakhtiari, Mostafa Omidi Bidgoli, Mohammad Hosseini

Research outputs 2022 to 2026

In this study, the latest developments in 3D printing of porous glasses are discussed. Current challenges in 3D printing of porous-based microfluidic devices mostly include the printing resolution which is correlated with the processing time, post treating, and developing tailored materials for porous glasses. Although the latter issue has been resolved to some extent recently, the former has remained a challenge. Currently, the smallest 3D printed feature in a microfluidic structure is 200µm while higher resolutions are required in some applications. On the other hand, previous reports have shown intensive printing time for higher resolutions. To achieve an optimal compromise, …

Sensitivity Analysis Of Reservoir Characteristics And Flue Gas Composition For Enhanced Oil Recovery In Heterogeneous Reservoir, Mehdi Nassabeh, Zhenjiang You, Alireza Keshavarz, Stefan Iglauer

Research outputs 2022 to 2026

The success of enhanced oil recovery depends on optimizing various reservoir factors. While CO2 and flue gas injections are common methods, they encounter challenges that require a deep understanding of reservoir characteristics and thorough analysis of pertinent parameters for effective mitigation. This study aimed to explore the synergistic relationship between flue gas compositions, reservoir characteristics, and injection rates for optimal oil recovery. Unlike prior studies that primarily examined the isolated effects of CO2 or flue gas, this research uniquely investigates the combined impact of real-world flue gas compositions from industrial sources under heterogeneous reservoir conditions. Through extensive sensitivity analysis and …

Recent Progress In Underground Hydrogen Storage, Muhammad Ali, Abubakar Isah, Nurudeen Yekeen, Aliakbar Hassanpouryouzband, Mohammad Sarmadivaleh, Esuru Rita Okoroafor, Mohammed Al Kobaisi, Mohamed Mahmoud, Volker Vahrenkamp, Hussein Hoteit

Research outputs 2022 to 2026

With the global population anticipated to reach 9.9 billion by 2050 and rapid industrialization and economic growth, global energy demand is projected to increase by nearly 50%. Fossil fuels meet 80% of this demand, resulting in considerable greenhouse gas emissions and environmental challenges. Hydrogen (H2) offers a promising alternative due to its potential for clean combustion and integration into renewable energy systems. Underground H2 storage (UHS) enables long-term, large-scale storage to achieve equilibrium between seasonal supply and demand. This review synthesizes recent advancements in UHS, highlighting progress and persistent challenges. The review explores the complex mechanisms of H2 trapping and …

Ecu-Pmu-Fdi/Tsa, Taylah Griffiths, Mohiuddin Ahmed, Chadni Islam

Research Datasets

Cyberattacks are now targeting the electrical grid due to its inclusion of smart devices, e.g., smart meters, phasor measurement units. The need to understand and review the impacts of attacks is vital. ECU-PMU-FDI/TSA encompasses communications between a phasor measurement unit and a phasor data concentrator, using the IEEE C37.118 protocol. Benign traffic was captured as control, and for attacks false data injection and time synchronization attack traffic were captured.

Fast-Sparse-Spanner: A Practical Algorithm For Constructing Low-Stretch Sparse Geometric Graphs, Fnu Shariful

UNF Graduate Theses and Dissertations

When constructing geometric graphs (vertices are points and edges are line segments connecting point pairs) on pointsets, stretch-factor (worst-case detour between any point pair) is often considered a quality metric. A low stretch-factor (a quantity that is usually > 1) guarantees short paths between all vertex pairs. A geometric graph having a stretch-factor of t is known as a t-spanner. Creating low stretch-factor geometric graphs for large pointsets with a low number of edges is an open problem in computational geometry.

In this work, we have designed and engineered a new simple and practical (fast and memory-efficient) algorithm named Fast-Sparse-Spanner algorithm …

Traffic Safety In Tacoma: A Dual Study On Community Perceptions Of Vision Zero And The Application Of The Safe System Framework, Janeroza W. Matyenyi

UNF Graduate Theses and Dissertations

The city of Tacoma adopted Vision Zero in 2020 and is planning to achieve zero traffic deaths and severe injuries by 2035. As part of its outreach plan to engage the local community, the city of Tacoma’s Vision Zero team surveyed the critical issues affecting traffic safety as perceived by road users. One of the Vision Zero strategies is to implement safer speeds across streets by reducing speed limits that are too high. This study aims to analyze the factors influencing the perceptions of speeding and high-speed limits as safety concerns, analyze narratives from respondents on issues affecting traffic safety, …

Analysis Of Port Traffic Growth For Optimization Of Traffic Flow: A Microscopic Traffic Simulation Study Of Jaxport's Blount Island Marine Terminal, Amy A. Aida

UNF Graduate Theses and Dissertations

To accommodate increasing cargo volumes and remain competitive, ports worldwide are facing growing pressure to expand and modernize their facilities. However, these expansions can place additional strain on land transportation networks, leading to congestion, delays and operational inefficiencies. This study used VISSIM, a microscopic traffic simulation tool, to model and analyze the complex traffic dynamics at the Blount Island Marine Terminal in Jacksonville, Florida, which is currently undergoing expansion.

To account for future traffic conditions, time series analysis was employed to project growth in traffic demand, taking into consideration anticipated expansions in tenant yard facilities, as well as increases in …

Design, Fabrication, & Laboratory Testing Of A Strain Gage Instrumentation System For Marine Applications, Salem C. Homrighausen

UNF Graduate Theses and Dissertations

A strain gage-based instrumentation system was designed and fabricated to measure the moment present at the base of a mock, diesel-engine snorkel for a submerged vehicle designed to operate in the surf zone. Afterwards, a lab experiment was designed and executed to determine the accuracy of the instrument and a 2-dimensional, matrix-vector equation was formulated to relate pairs of voltages, Vx and Vy, to moments, Mx and My for the experiment. Three versions of this model were built. The first model was created using traditional statics equations governing strain, stress, moment, force. The second and third models were built directly …

Assessment And Optimization Of Electric Vehicles Charging Infrastructure: Addressing Accessibility Disparities In Urban And Rural Areas, Dennis B. Bwire

UNF Graduate Theses and Dissertations

The widespread adoption of electric vehicles (EVs) is essential for advancing sustainable transportation systems; however, disparities in the spatial distribution of electric vehicle charging stations (EVCS) present significant challenges for equitable access. This thesis investigates both the inequities in EVCS accessibility and offers a data driven approach for optimizing the siting of future charging infrastructure.

The first part of the study investigates the accessibility of EVCS in rural and urban areas, focusing on how socio-demographic factors influence accessibility metrics. Using geographic information systems (GIS), network analysis, and binary logistic regression, spatial data on EVCS locations and socio-demographic attributes such as …

Understanding Fare Capping In Public Transit: Socioeconomic Predictors And Ridership Outcomes, Maige Majuto

UNF Graduate Theses and Dissertations

Fare capping is a transit policy that limits how much a rider pays within a certain period, after which all rides are free for the rest of that period. Fare capping has become a potential strategy to reverse the trend of declining transit ridership, which has been caused by factors like fare increases, service reductions, and shifts in travel behavior. While demographic and socioeconomic characteristics are known to influence ridership, their role in fare capping adoption remains underexplored. This study examines how factors like age, income, race, education, and car ownership affect fare capping adoption at the neighborhood level and …

Rodcast Interaction: A Novel Technique For Dense Virtual Reality Environments, Nevzat U. Demirseren

UNF Graduate Theses and Dissertations

Virtual Reality (VR) technologies continue to grow in popularity and application versatility, yet effective interaction within complex dense environments remains as a critical challenge. In particular, users with low level of VR experience often face decreased accuracy and dissatisfaction selecting occluded objects. A variety of interaction techniques to select and manipulate objects exist, but there is a research gap in understanding what kinds of techniques support users in dense environments. This study evaluates the user performance and preference in such environments. Three interaction techniques are examined in this study: Go-Go Hand, Flower Cone, and a proposed technique called RodCast Interaction. …

Continuing Development Of An Unmanned Vehicle For Conducting Scientific And Engineering Operations In The Littoral Zone, Peter S. Bohn

UNF Graduate Theses and Dissertations

The beach and near shore are among the most economically and environmentally important regions on earth, yet they remain poorly understood due to the challenges of surveying the surf zone and obtaining other important data during high-energy events. Traditional methods such as wading surveys, small watercraft, and specialized vehicles like the coastal research amphibious buggy (CRAB) are limited by safety risks, high mobilization costs, and restricted operating windows. The work conducted in this effort addresses these limitations by continuing development of a remotely operated vehicle (ROV) intended to be operational in harsh surf conditions to collect high-resolution bathymetric and hydrodynamic …

Solar Energy Prediction Using Advanced Hybrid Machine Learning Models, Jelawi A. Alqhtani

UNF Graduate Theses and Dissertations

Accurate short-term forecasting of solar power generation is critical for the reliable and cost-effective operation of renewable-based microgrids, where sudden weather-induced variability can compromise grid stability, battery scheduling, and energy trading decisions. Traditional physical and statistical models struggle to capture the complex non-linear relationships and localized weather effects, while individual deep learning architectures often exhibit systematic biases such as chronic under-prediction of peak generation. This thesis proposes a novel Cross-Feedback Ensemble framework that combines the complementary strengths of Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and one-dimensional Convolutional Neural Network (1D-CNN) models through an iterative cross-feedback mechanism and a …

Frustrated Quantum Magnetism: The Interplay Of Isotropic And Anisotropic Interactions With Application To Α-Rucl3, Evan M. Wilson

UNF Graduate Theses and Dissertations

We investigate how anisotropic spin interactions, including Dzyaloshinskii–Moriya and Kitaev terms, manifest across quantum spin systems ranging from a single S = 1/2 dimer to molecular spin clusters and layered magnetic materials. Beginning with an exact analysis of the spin dimer, we demonstrate how singlet–triplet mixing induced by Dzyaloshinskii–Moriya interaction directly influences both thermodynamic observables and inelastic neutron scattering spectra. These microscopic fingerprints are then extended to trimer, tetramer, and tetrahedron geometries, where field-induced phase transitions and heat capacity anomalies reveal the interplay between isotropic Heisenberg and anisotropic Kitaev exchanges. In the frustrated zigzag honeycomb lattice, we show that a …

Intelligent Tutoring Systems In The Age Of Llm-Based Agentic Frameworks - Adapting Small On-Device Language Models For Fact-Checking And Student Compliance Detection, Evan Vahid Naderi

Honors Undergraduate Theses

As large language models (LLMs) demonstrate increasingly sophisticated language understanding capabilities, they offer transformative potential for educational technology, particularly in developing more responsive intelligent tutoring systems (ITS). To develop these systems, a synthesis that balances theoretical frameworks with practical, cutting-edge, and deployable technology would be useful. This thesis aims to advance the field of ITSs theoretically by viewing the modern advancements in natural language processing within the context of the foundational frameworks important to the fields of self-regulated learning, ITSs, and cognitive agents. Then, building on prior research on the ITS MetaTutor \citep{Azevedo2022}, this research focuses on how functions of …

Identification Of Fiducial Points In Seismocardiographic Cycles Using Manual And Automated Annotation Methods, Jasmine-Vy T. Truong

Honors Undergraduate Theses

There is currently a need for complementary methods for non-invasive cardiac monitoring. Seismocardiography (SCG), the measurement of cardiac-induced vibrations at the chest surface, has shown potential clinical utility. Improving the reliability of detecting fiducial points of electrocardiography (ECG) and SCG, which collectively capture the electro-mechanical cardiac activities, could expand ECG/SCG utility as a low-cost, accessible tool for clinical assessment. This study identifies commonly accepted criteria for fiducial point detection in SCG and ECG through an extensive literature review and signal processing techniques. The previous criteria were evaluated to identify their strengths and weaknesses. Based on the findings, an improved set …

Quantum-Resilient Architectures For Enterprise And Cloud Information Systems, Implications Of Quantum Computing For Enterprise Cybersecurity And Data Integrity, Manikantha Varaprasad Inakollu

Computer Science and Engineering Faculty Publications

The emergence of quantum computing presents unprecedented challenges to contemporary enterprise cybersecurity frameworks. Current cryptographic systems that protect sensitive data and secure communications will become vulnerable to quantum attacks within the next decade. This research examines the implications of quantum computing advancement for enterprise and cloud information systems, proposing quantum-resilient architectural frameworks that can withstand both classical and quantum threats. We analyze the timeline of quantum computing development, assess vulnerabilities in existing enterprise security infrastructures, and evaluate post-quantum cryptographic approaches suitable for organizational implementation. Through comparative analysis of quantum-resistant algorithms and architectural patterns, this study demonstrates that enterprises must begin …

Blockchain-Enabled Trust Frameworks For Enterprise Information Systems, Establishing Verifiable Trust In Distributed Organizational Environments, Manikantha Varaprasad Inakollu

Computer Science and Engineering Faculty Publications

Enterprise information systems increasingly operate in distributed environments where traditional trust mechanisms based on centralized authority prove insufficient. This research develops a comprehensive blockchain-enabled trust framework that establishes verifiable, decentralized trust mechanisms for enterprise systems operating across organizational boundaries. The study addresses critical gaps in current enterprise architectures where trust depends on centralized intermediaries, creating single points of failure and limiting inter-organizational collaboration. Through examination of existing trust models and blockchain capabilities, we propose an integrated framework that combines cryptographic verification, distributed consensus, and smart contract automation to establish trust without centralized control. Our framework enables organizations to verify data …

Advanced Nanocomposite-Based Electrochemical Sensor For Ultra-Sensitive Dopamine Detection In Physiological Fluids, Megha Shinde, Gymama Slaughter

Center for Bioelectronics Publications

This study presents a novel point-of-care electrochemical sensor for dopamine (DA) detection, featuring a flexible laser-induced graphene (LIG) modified with a unique nanocomposite comprising Nb₄C₃T_x MXene, polypyrrole (PPy), and iron nanoparticles (FeNPs). The LIG-Nb₄C₃T_x MXene-PPy-FeNPs is characterized by scanning electron microscopy to confirm the successful surface modification. The electrochemical performance of the fabricated sensor via cyclic voltammetry showed significant electrochemical activity upon Nb₄C₃T_x MXene-PPy-FeNPs nanocomposite modification of the LIG surface with an increased peak anodic current (Ipa) from 43 μA to 104 μA. The sensor …

Landslide Prediction Using Time-Series Decomposition, Reinforcement Learning-Based Feature Selection And Ml Models, Mohith Sai Venkat Ankem

Master's Projects

Landslides pose significant risks to human life, the community, and the environment, yet their prediction remains a complex and unexplored challenge. Existing prediction models often rely on surface measurements and satellite images, neglecting the critical role, in providing deeper insights into landslide analysis. The literature review highlights a lack of research in time series decomposition techniques, despite their potential to improve prediction accuracy. Similarly, feature selection methods that enhance model robustness and precision have not been adequately addressed. This study presents a novel approach to predicting landslide displacement by combining feature selection through reinforcement learning techniques with advanced time-series machine …

Digital Twins For Flexible Manufacturing, Drew Brandon Sander

Theses and Dissertations

With the establishment of Digital Twins as an enabling technology for Industry 4.0, it is time to transition from the previous foundations to works that implement and highlight the capabilities Digital Twins present. The Industry 4.0 paradigm has recentered the focus on customizability, leading to reemerging goals of flexibility within manufacturing. Empowered through new cyber-physical systems, new enabling technologies are driving the revolution. To identify how Digital Twins as an enabling technology contribute to flexibility within manufacturing, a comprehensive investigation is conducted along with a detailed case study. A systematic literature review is conducted to analyze quality Digital Twin implementations …

Novel Redox Oxygen Active Materials For Solid Oxide Cells And Thermochemical Hydrogen Production, Jiaxin Lu

Theses and Dissertations

This dissertation investigates novel materials designed to significantly enhance the performance and durability of oxygen electrodes for solid oxide cells and redox active materials for thermochemical hydrogen production. The first part of this work evaluates Ta-doped BaCoO₃₋δ (BCT) and its structural analog SrCoO₃₋δ (SCT), focusing on their catalytic performance in oxygen reduction and evolution reactions. Among BCT compositions (x = 0.1, 0.3, 0.5), the BCT10 (x = 0.1) composition exhibited the highest oxygen vacancy concentration, electronic conductivity, and lowest polarization resistance. However, SCT10 surpassed BCT10 in these critical performance parameters and also demonstrated greater stability over extended operational periods. Notably, …

Analyzing The Safety Effects Of Edge Lane Roads For Motor Vehicle Users, John Yang

Master's Theses

This thesis builds upon a prior study that analyzed the safety effects of Edge Lane Roads (ELRs) within the U.S. context, addressing gaps related to collision, traffic volume, and speed data. An ELR is a roadway configuration that accommodates two-way automobile traffic within a single center lane while providing edge lanes for vulnerable road users (VRUs), i.e., bicyclists or pedestrians. Although the concept of a single shared lane for opposing traffic often raises safety concerns among the public, ELRs have demonstrated potential to control speeds, optimize roadway space, and improve traffic operations on low-volume roads.

To evaluate safety outcomes, this …

Biomedical Mxene-Polymer Nanocomposites: Advancing Photothermal Therapy, Antibacterial Action, And Smart Drug Delivery: A Review, Ali Mohammad Amani, Lobat Tayebi, Ehsan Vafa, Mohammad Javad Azizli, Milad Abbasi, Ahmad Vaez, Hesam Kamyab, Daniel Simancas-Racines, Shreeshivadasan Chelliapan

Electrical & Computer Engineering Faculty Publications

MXenes are hydrophilic, conductive, tunable, and biocompatible two-dimensional ceramic materials prepared by etching the 'A' layer from their precursor MAX phases. Although MXenes show exceptional promise in photothermal therapy, biosensing, and regenerative medicine, they face challenges such as oxidative instability in physiological environments, limited drug-loading capacity, and unpredictable immune responses. To address these limitations, MXene/polymer nanocomposites incorporating both synthetic polymers (e.g., polyethylene glycol (PEG), polyvinyl alcohol (PVA), polyvinylpyrrolidone (PVP), and polylactic-co-glycolic acid (PLGA)) and natural biopolymers (e.g., cellulose nanofiber, gelatin, chitosan, hyaluronic acid, and soybean phospholipids) have been developed. These composites enhance functionality for biomedical applications such as photothermal cancer …

Flame Boundary Effects Of Hydrogen-Air Premixing, Alecson L. De Lima Junior

Honors Undergraduate Theses

The objective of this research was to investigate the reaction of hydrogen and heated air premixing when injected into a combusting ethylene-air crossflow, and to study the flame stabilization location with varying premixing levels. The main parameter of this investigation was the flame stabilization diagnosed through chemiluminescence, based on recorded equivalence ratio, temperature, and flame boundaries, and maintaining a constant air temperature, hydrogen and air mass flow, and momentum flux ratios. Testing was conducted at different ratios of hydrogen and air premixing achieved through alternating the distance between the point where hydrogen and air are mixed and the combusting crossflow. …

Integrated Qfd-Triz Optimization Method For Satellite Solar Array Design In Cost-Sensitive Environment, Hongyi Zhang, Liang Su

International Journal of Aviation, Aeronautics, and Aerospace

With the rapid evolution of commercial space markets in the new space era, satellite design philosophy is transitioning from "performance supremacy" toward "cost-effectiveness priority." This research concentrates on solar arrays, a critical component representing 15%-20% of satellite costs, addressing limitations in traditional design methodologies that inadequately coordinate user requirements and lack systematic frameworks for cost-performance collaborative optimization. We propose a solar array optimization methodology predicated on the integration of Quality Function Deployment (QFD) and the Theory of Inventive Problem Solving (TRIZ). This methodology incorporates cost dimensions through an extended QFD matrix, employs TRIZ to resolve technical contradictions, and develops a …

Suas Agricultural Aerial Application Operational Field Test, David Thirtyacre, Joseph Cerreta, Scott S. Burgess

International Journal of Aviation, Aeronautics, and Aerospace

One of the most promising uses of aerial applications by a sUAS is on small farms where traditional crewed aerial applicators were not practical due to the limited size of the operations. This controlled field test aimed to assess the feasibility and cost-effectiveness of using a sUAS spreading system compared to the traditional manual application of weed killer and fertilizer on cranberry bogs in Western Washington that were less than 10 acres. The aerial application took place over two separate days as scheduled by the farmer for maximum product efficiency. A total of sixty-three flights were necessary to apply the …

Bibliometric Analysis With R Biblioshiny On Safety Behavior In Aviation, Büşra Yıldırım, İnan Eryılmaz, Ahmet Karacan, Nusret Erceylan

International Journal of Aviation, Aeronautics, and Aerospace

Safety behaviors in aviation are not limited to technical knowledge and skills in ensuring the safety of flight operations, but also include the attitudes, decision-making processes and collaborations of individuals and teams. In this context, in this study, a bibliometric analysis of publication and citation trends, key concepts and interactions of studies in the field was conducted to identify current and potential trends in aviation and safety behavior-based research, and to explore the intersections between safety behavior and aviation studies and the areas waiting to be explored. The bibliometric analysis using the RStudio-based Biblioshiny program was conducted on 1065 articles …

Mitigating Information Overload In Aviation Safety: Ai-Driven Hierarchical Tagging And Summarization Of Notam For Pre-Flight Information Bulletin, Rutong Gu, Yefeng Qu, Dongling Chen, Yu Tang, Ailin Zhou

International Journal of Aviation, Aeronautics, and Aerospace

To address the challenges of aviation safety information overload in Pre-flight Information Bulletin (PIB) systems, this study proposes an intelligent classification framework (ERNIE-DPCNN) that integrates knowledge-enhanced semantic representation with a Deep Pyramid Convolutional Network. Traditional systems relying on rule-based filtering mechanisms suffer from inefficiencies in critical information identification and high risks of human misjudgment. The proposed framework achieves breakthroughs through three technical innovations: (1) An aviation domain-adapted ERNIE model is constructed, leveraging phrase-level masking strategies to enhance semantic representation of compound identifiers; (2) A Deep Pyramid Convolutional Network (DPCNN) is designed to extract multi-granularity features via hierarchical convolution-pooling architecture, optimized …

Innovative Bird Strike Mitigation Strategies: Integrating Drones And Cutting-Edge Technologies To Enhance Airport Safety, Abdellah Hanine, Abdellah Elbarkany

International Journal of Aviation, Aeronautics, and Aerospace

Notwithstanding significant efforts to reduce the risk of bird strikes at and around airports, as well as advancements in technology, aviation safety continues to be threatened by this hazard. Our study of recent data shows a clear historical increase in accidents, therefore underscoring the flaws in present technologies. Although among the technologies in common use are radar, drones, cameras, and acoustic approaches, they are not always able to completely meet the challenging needs of bird strike risk mitigation. This approach creatively blends these four fundamental technologies by means of enhanced real-time data processing and targeted drone deployment. While providing more …