Engineering Commons^™

Development Of Hydrogen Emissions Quantification Systems To Expand Understanding Of Leaks And Losses Associated With The Burgeoning Hydrogen Transportation Sector, Christopher Loomis

Graduate Theses, Dissertations, and Problem Reports (ETD)

To combat global warming, alternative fuels are being investigated. Hydrogen is at the forefront of this movement, advertised as having zero emissions due to the products of the energy reaction being only water. However, studies over recent decades indicate that hydrogen in the atmosphere acts as a form of greenhouse gas (GHG) by increasing the lifespan of methane in the atmosphere. Models are attempting to estimate the possible effects of a transition to a hydrogen-fueled economy but lack empirical data to provide confidence to these estimated values. There is little data that quantifies hydrogen from anthropogenic sources.

To address this …

Effect Of Graphene Oxide On The Upconversion Photoluminescence Behavior Of Er/Yb Co-Doped Pvdf-Go Composite Nanofibers, Saptasree Bose, Jack Ryan Summers, Bhupendra B. Srivastava, Karen Lozano, Victoria Padilla-Gainza

Mechanical Engineering Faculty Publications

Upconversion photoluminescence (UCPL) materials, particularly rare-earth (RE) doped nanoparticles, have garnered significant attention due to their ability to convert near-infrared (NIR) excitation into visible emission, offering benefits such as high photostability, long lifetimes, low autofluorescence, and deep tissue penetration. Among various platforms, polymer-based one-dimensional (1D) nanofibers with in-situ lanthanide doping remain relatively unexplored, despite their superior mechanical flexibility, processability, and potential for improved luminescence performance. In this study, we report the fabrication and UCPL quenching behavior of Er3+/Yb3+ co-doped polyvinylidene difluoride (PVDF) nanofibers incorporated with graphene oxide (GO), synthesized for the first time using the scalable Forcespinning® technique. PVDF, a …

Wideband Acoustic Immittance: Suitable Quantities For Assessing Middle-Ear Status, Kren Monrad Nørgaard, Jingxin Jessica Feng, Susan E. Voss

Engineering: Faculty Publications

This paper investigates the physical significance of ear-canal wave quantities—such as absorbance—that are commonly measured in wideband-acoustic-immittance tests and evaluates whether these quantities uniquely characterize middle-ear function. This is explored using simulations of lumped-element and transmission-line ear canals, along with measurements in three-dimensional-printed uniform and anatomical ear canals of varying geometry, terminated by the same middle-ear simulator. The results demonstrate the following points: (1) Wave quantities computed using estimated or geometrical cross-sectional areas do not uniquely characterize the middle ear because they describe the wave interaction between ear canal and middle ear and are therefore confounded by variations in ear-canal …

Security-Oriented Voice Authentication Using Machine Learning, Ifeoluwa Stella Elegbe

College of Graduate Studies: Theses & Dissertations

This study develops and evaluates a machine learning and deep learning-based voice authentication system for secure identity verification. As traditional authentication methods such as passwords, PINs, and security tokens continue to face challenges, including identity theft, forgetting, and unauthorized access, voice biometrics offers a more secure, convenient, and user-friendly alternative, especially for remote, hands-free, and accessibility-focused applications. The study adopts a closed-set speaker identification framework, where the system determines the most likely speaker from a predefined group of enrolled users. A structured methodology is implemented, beginning with audio preprocessing and feature extraction. Key acoustic features, including Mel-Frequency Cepstral Coefficients (MFCCs), …

Feasibility Of Quantifying The Dosage Of Zycotherm In Its Modified Asphalt Binders, Susmita Acharjee

College of Graduate Studies: Theses & Dissertations

The quantification of low-percentage additives in asphalt binders is challenging due to their minimal concentration and the complex composition of the binder matrix. Zycotherm, a nano-organosilane anti-stripping additive, is typically used in very small dosages (0.05%–0.20%), making its detection and quantification particularly difficult. This study investigated the feasibility of estimating Zycotherm dosage in asphalt binders by examining chemical and rheological and moisture responses. Two asphalt binder grades, PG 64-22 and PG 76-22, were modified with Zycotherm at dosages of 0.05%, 0.10%, 0.15%, and 0.20% by weight of binder, along with corresponding base binders. Laboratory experiments were conducted using Fourier Transform …

Explainable Ai-Driven Predictive Maintenance Curriculum For Smart Manufacturing, Abdullah Al Mamun, Murat Kuzlu, Katherine Smith, Vukica Jovanovic, Dalya Ismael, Adel El-Shahat, Angela Sicaja, Md. Hedayetul Islam Chy

Engineering Technology Faculty Publications

Nowadays, Industry 4.0 has transformed manufacturing industries into a data-rich system driven by IoT, automation, and Artificial Intelligence (AI). Within this context, Predictive Maintenance (PdM) provides a proactive strategy that leverages heterogeneous sensor data such as vibration, acoustic, electrical, and visual signals along with historical performance and advanced analytics to forecast equipment failures before they occur. Usually, AI-driven PdM (AI-PdM) enhances this capability by integrating AI-based sensor analytics to automate fault prediction and optimize system reliability. However, traditional AI-PdM often functions as a “black box,” providing limited interpretability of its decision-making process and posing challenges for trust, validation, and human …

Data-Driven Prediction Of Compressive Strength In Pofa-Modified Concrete: A Comparative Study Of Lr, Nlr, And Ann Models, Shuaaib A. Mohammed, Hawdin Ismael Ibrahim, Diar Fatah Abdulrahman Askar, Hersh F Mahmood, Mehdi Khodaei, Soran Abdrahman Ahmad

Mansoura Engineering Journal

Production of concrete results in high CO₂ emissions, high energy demand, and consumption of various raw materials; however, it is one of the most widely used materials in construction to date. Therefore, researchers aim to minimize the impact of concrete production through various methods, such as introducing sustainable sources of materials that can be used in concrete. For instance, agricultural waste materials can be used as partial cement replacement. This study presents a comprehensive data-driven analysis of the effects of POFA on the properties of normal-strength concrete. By synthesizing a database of 196 experimental datasets from existing literature, three …

Recycling Of Plastic Into Fibers Using A Novel Machine Design And Analysis Of Fiber Characteristics, Mahmoud Khamees, Nasser Ayoub, Sabreen Addullah Abdelwahab, M. M. Maghawry

Mansoura Engineering Journal

This study presents a modified extrusion-based recycling system with an improved nozzle design and controlled fiber production capability. The machine was conceptualized and fabricated to efficiently process waste plastic and extrude it into fibers of varying diameters. The study focuses on evaluating how fiber diameter influences critical material properties. Microstructural analysis by scanning electron microscopy (SEM) was conducted to investigate the morphology and fiber diameters, while tensile testing provided insights into mechanical performance, including strength and elongation. Moisture absorption tests were also performed to assess durability and environmental resistance. The results demonstrate clear correlations between fiber diameter and the examined …

Federated And Explainable Spiking Neural Networks For Fair And Privacy-Preserving Nail Disease Diagnostics, Ch Pavani Reddy, Krishnanaik Vankdoth

Mansoura Engineering Journal

Automated nail disease diagnostics provide a non-invasive pathway for identifying underlying systemic health conditions; however, conventional centralized deep learning approaches often raise concerns related to privacy, fairness, and interpretability. Although the original NeuroNail-SNN framework demonstrated an energy-efficient and edge-ready diagnostic solution, its broader clinical adoption remained limited by unresolved trust, transparency, and ethical considerations. In this study, we propose the Federated and Explainable NeuroNail-SNN, which extends the original spiking neural architecture by integrating federated learning (FL), explainable artificial intelligence (XAI), fairness evaluation, and uncertainty quantification within a unified framework. Federated learning enables decentralized model training across hospitals and mobile clinics …

Event-Related Potential Variation In Response Accuracy: A Comparative Analysis Using Mne-Python, Akash Rajak, Sachin Umrao

Mansoura Engineering Journal

Event-Related Potentials (ERPs) are extensively employed in the examination of neural responses linked with cognitive processing and changes in brain activity. In this work, we conducted a comparative analysis of ERPs on a publicly available EEG dataset (122 subjects, alcoholic and control groups) with the help of the MNE-Python framework. The 64 electrodes for EEG were placed according to the international 10 - 20 system, and EEG was sampled at a 256 Hz sampling rate over 1-second epochs. The preprocessing pipeline consisted of 1 - 40 Hz bandpass filtering, noise reduction, spectral computation, and ERP waveform analysis. Temporal neural activity …

Optimisation Of Stepped Basin Solar Still With Response Surface Methodology And Machine Learning Methods, M. Balamurugan, V. Santhanam, B. Deepanraj, S. P Manikandan, M. Yuvaperiyasamy, N. Senthilkumar

Mansoura Engineering Journal

This research focuses on enhancing the distillate output of a stepped basin solar still by optimizing key operational variables using Response Surface Methodology (RSM) and advanced machine learning techniques. As water scarcity remains a critical global challenge, solar stills offer a viable, sustainable solution for desalination. These systems offer an energy-efficient approach to converting saline water intofreshwater, providing an alternative to conventional desalination methods. The primary objective was to investigate how variations in solar radiation, step height, and water inlet temperature influence the productivity of the stepped basin solar still. The solar radiation ranged from 600 to 1000 W/m², the …

Improving Efficiency In Noma Schemes Having Inter-User Interference Using Mechanism Design, Zory Marantz

Publications and Research

Modern wireless systems utilize non-orthogonal multiple access to increase their rate capacities; however, the efficiency of the individual utility defined in bits per Joule has yet to be considered. Multiple variations of non-orthogonal multiple access have the interference of the signal-to-interference-plus-noise ratio as a function of the received power from multiple other users due to code implementations that are non-orthogonal or non-ideal cancellation in successive-interference-cancellation methods. Game theoretic concepts are used to improve user bits-per-Joule performance. Previous solutions increment transmit power and are not based on closed form systematic methods. The mechanism design presented here led to a non-cooperative Nash …

Pafex: Compiler-Based Floating-Point Exception Detection For Gpu Kernels With Papispecific Software-Defined Events, Samin Islam, Shirley V. Moore, Christoph Q. Lauter

Graduate Student Papers (CS)

As high-performance computing becomes progressively heterogeneous, the dependence upon vendor specific tools for numerical correctness has become an impediment to portability. Although modern GPUs comply with the IEEE 754 standard, the lack of practical native hardware support to raise and handle exceptions (special values like ±∞ or NaN) is a well-known architectural limitation. To embed portable numerical correctness across heterogeneous systems, we propose an architecture agnostic prototype based on LLVM-compiler infrastructure. This framework detects floating-point exceptions in GPU kernels at the Intermediate Representation (IR) level, instrumenting both device code and host code, strictly complying with the 2019 IEEE 754 standard. …

Toward Neurosymbolic Reinforcement Learning Via Editable Specifications, Vedant Khandelwal, Hong Yung Yip, Amit Sheth

Publications

Reinforcement learning systems are commonly adapted to new settings by retraining or fine-tuning policies. This default is costly, difficult to audit, and poorly aligned with structured requirement changes such as revised safety rules, new operational constraints, or updated user preferences. We argue for an alternative abstraction: adaptation via edits to an external, human-readable specification that the agent consults at execution time. We propose conditioning decision-making on an editable knowledge graph encoding (i) rules capturing action applicability and high-level effects, (ii) hard constraints defining feasibility, and (iii) soft preferences shaping tradeoffs among feasible behaviors. Requirement changes become graph edits, not policy …

Estimating Sediment Properties Using A New Source Level Function For Wind-Driven Underwater Sound Derived From Long-Term Archival Data, S Bruce Martin, Martin Siderius

Electrical and Computer Engineering Faculty Publications and Presentations

Wind-driven breaking waves generate the background sound throughout the ocean. An accurate source level for wind-driven breaking waves is needed for estimating the ambient sound levels needed for sound exposure modeling, environmental assessments, and assessing the detection performance of sonars. Previous models applied a constant roll-off of sound levels at -16 dB/decade at all wind speeds, and these models' source levels were flat at frequencies below ∼1000 Hz due to a lack of measurements. Here, we analyzed 16 long-term archival datasets with limited anthropogenic sound sources to estimate the wind-driven source level down to 100 Hz. We estimated the site-specific …

Mobility Of Hydrophilic And Hydrophobic Nanoparticles In Carbonate Reservoirs: Application To Subsurface Projects, Zain Ul Abedin Arain, Sarmad Al-Anssari, Muhammad Ali, Faisal Ur Rahman Awan, Alireza Keshavarz, Jitendra Sangwai, Mohammad Sarmadivaleh, Stefan Iglauer

Research outputs 2022 to 2026

Nanoparticles (NPs) have been suggested for subsurface projects, including enhanced oil recovery (EOR), carbon capture and storage (CCS), and hydrogen storage, due to their small size, high surface energy, controlled surface properties, and significant effects on the underground formation properties. Silica is an excellent NP that efficiently modifies the surface properties of subsurface formations for incremental oil recovery and to derisk carbon and hydrogen leaks. However, the retention of injected NPs in a narrow area near the injection inlet can limit a project’s feasibility. In the present study, hydrophobic (hybrid) NPs were produced via silanization of silica NPs, and the …

A Review On Underwater Beamforming: Techniques, Challenges, And Future Directions, Ruba Zaheer, Quoc Viet Phung, Iftekhar Ahmad, Asma Aziz, Daryoush Habibi, Yue Rong, Walid K. Hasan

Research outputs 2022 to 2026

This paper comprehensively reviews recent advancements in Underwater Beamforming (UWB) systems, highlighting its pivotal role in underwater communication, sensing, and environmental monitoring. It explores the various beamforming applications, ranging from maritime surveillance to marine life monitoring, and indicates its significance in enhancing signal clarity, spatial resolution, and noise suppression in underwater acoustic environments. The unique challenges posed by the underwater environment that introduce complexities into the beamforming process such as non-stationary noise interference, severe signal attenuation, multipath propagation, and dynamic environmental variability are thoroughly discussed. The review systematically discusses and examines conventional, adaptive, and learning-based beamforming techniques, analyzing their strengths, …

Enhanced Strength And Corrosion Resistance Of Ti-13nb-12ta-10zr-4sn Alloy By Aging Treatment, Yuhua Li, Rong Zhao, Qian Zhang, Haojie Wang, Yujing Liu, Lai Chang Zhang

Research outputs 2022 to 2026

This work investigates the effect of aging treatment on the mechanical properties and corrosion resistance of Ti-13Nb-12Ta-10Zr-4Sn (TNTZS) alloy prepared by vacuum arc melting. The as-cast TNTZS alloy was solution-treated and aged at 450°C (HT450) and 550°C (HT550). Microstructural characterization revealed significant changes in the phase proportion (in vol%), which transformed from 64% β, 19% α, and 17% α″ in as-cast condition to 54% β, 13% α, and 33% α″ for HT450 and 55% β, 25% α, and 20% α″ for HT550, respectively. The tensile strength and yield strength increased from 608 and 424 MPa in as-cast condition to 1192 …

Performance Investigation Of Microchannel Heat Sink With Biomimetic Trefoil Cavities On Different Walls, Sadiq Ali, Numan Habib, Faraz Ahmad, Aamer Sharif, Ana Vafadar

Research outputs 2022 to 2026

The modern world is shifting towards digitalization and miniaturization, leading to higher flux densities in electronic components and machines. However, conventional cooling methods, such as air-cooled smooth channels, are proving inadequate for removing the huge amounts of heat generated, thereby compromising the reliability and operational lifespan of electronic systems. This necessitates urgently exploring and analyzing modern techniques like microchannel cooling to improve its efficiency. This work uses ANSYS to conduct numerical simulations and investigates the heat transfer and flow behavior in a microchannel heat sink. The smooth channel is used to investigate and validate the flow behavior with the available …

Towards Carbon Geosequestration: Comparing The Wettability Performance Of Western Australian Altered Basaltic Rock/Co2/Water Systems, Seyi Philemon Akanji, Rossen Sedev, Lionel Esteban, Ausama Giwelli, Trevor Beardsmore, Heather Howard, Joel Sarout, Alireza Keshavarz, Stefan Iglauer

Research outputs 2022 to 2026

Geosequestration of carbon dioxide in basaltic rock formations is considered to have the potential to safely and permanently store significant quantities of this greenhouse gas and thereby mitigate its potential global warming effect. The success of this storage method is primarily dependent on the wettability behaviour of the rock-water-CO2 system, which significantly affects fluid distribution, fluid transport, storage capacity and containment security. This study investigates the wettability performance of several Western Australian altered basaltic rocks, of similar geochemistry, porosity and inter-connection. The wettability behaviour of the basaltic materials is assessed using water containing ions that have been leached from the …

Covert Transmission For Active Ris-Aided Full-Duplex Uav Integrated Sensing, Communication, And Computation Systems, Qi Zhang, Wei Gao, Chuan Liu, Yu Yao, Shihao Yan, Feng Shu, Shi Jin

Research outputs 2022 to 2026

Next-generation wireless network should accomplish integrated sensing, communication, and computation (ISCC) capabilities. This paper proposes a novel covert transmission scheme based on active reconfigurable intelligent surface (RIS)-enabled full-duplex (FD) unmanned aerial vehicle (UAV)-ISCC framework, where the multi-functional UAV realizes simultaneous target sensing and uplink (UL) covert communication, as well as performing edge computing (EC) for users. To maximize the minimum covert transmission rate (CTR) among all UL users, UAV transmit beamforming and trajectory, RIS weights, power allocation and signal processing in a FD UL transmission system are jointly devised. To tackle the intractable non-convex problem, we leverage second order cone …

Integrating Environmental Awareness In Underwater Acoustic Networks: A Comprehensive Review, Sadaf Vahabli, Iftekhar Ahmad, Quoc Viet Phung, Daryoush Habibi, Walid K. Hasan, Ruba Zaheer

Research outputs 2022 to 2026

Underwater Acoustic Networks (UANs) are critical for enabling long-range underwater communication, supporting a wide range of applications, such as environmental monitoring, resource exploration, disaster prevention and marine security. Unfortunately, UANs operate within a limited acoustic spectrum, where these spectrums often overlap with those used by marine animals for communication, navigation and foraging. Additionally, anthropogenic noise from industrial activities contributes to acoustic pollution, intensifying this problem. This frequency overlap poses significant risks to marine life. Therefore, this review highlights the urgent need to develop environmentally aware UANs that minimize harmful acoustic interference with marine mammals, fish and invertebrates. Further, it focuses …

A Novel Deep Transfer Learning-Based Adaptive Cascade Pi Controller Enhanced By Reinforcement Learning Algorithm And Snake Optimization For Robust Speed Regulation Of Brushless Dc Motors, Seyyed Morteza Ghamari, Asma Aziz

Research outputs 2022 to 2026

Brushless DC (BLDC) are common in electric cars, industrial automation, and robotics because of their high efficiency, high torque control, and compact size. Nevertheless, strong speed and current regulation is not easily attained because of system variation, load variations and the shortcomings of traditional fixed-gain proportional-integral (PI) controllers. In this paper, a new snake optimization-assisted deep transfer learning-based reinforcement learning (SOA-DTL-RL)-based adaptive cascade PI controller is proposed that combines transfer learning with fast adaptation, Reinforcement learning with real-time optimization, and snake optimization with optimal initial gain selection to guarantee the robust speed and current regulation in BLDC motors. The proposed …

Gaze Transition Entropy And Automation Trust In Multitasking Workspace, Yusuke Yamani, Austin Jackson, Tetsuya Sato, Feyishola Ashimi, Michael S. Politowicz, Eric T. Chancey, Makoto Itoh

Psychology Faculty Publications

Safe flight operation requires visual scanning across multiple displays in a cockpit, which collectively represent the state of the aircraft and supporting automation. Trust is a crucial factor that drives human-automation interaction, and recent work has suggested a relationship between an operator's visual attention and automation trust. One index that captures predictability of eye movements between different areas of interest is gaze transition entropy. The current work reanalyzed data from Sato et al., which examined eye movement patterns and trust in automation associated with the system monitoring task of the Multi-Attribute Task Battery. Results showed credible positive correlations between the …

Multi-Objective Optimization Strategy For Component Sizing In Solar-Hydrogen Microgrids Using An Advanced Hybrid Genetic Algorithm, Dylan Jones

UNF Graduate Theses and Dissertations

This thesis presents the development of a genetic algorithm (GA) optimization framework for the design and component sizing of hybrid solar-hydrogen microgrids. The framework addresses a critical gap in research and existing commercial tools by unifying performance maximization and cost minimization objectives across both grid-tied and islanded configurations. Integrating solar photovoltaics, electrolyzers, hydrogen storage, fuel cells, and batteries, the GA employs adaptive weighting and dynamic boundary constraints to balance technical feasibility with economic efficiency. To ensure real-world viability, the algorithm relies on a novel Daylight Sun Factor (DSF) for localized solar assessment and was rigorously validated against multi-year, high-fidelity irradiance …

Regulation And Localization Of Urease In Sporosarcina Pasteurii: Implications For Coastal Protection, Amar Kosovac

UNF Graduate Theses and Dissertations

Coastal erosion is a persistent problem exacerbated by global warming. As the climate changes, the southeastern coast is likely to experience an increased frequency and intensity of storms, which can significantly damage the coastline. The coast is crucial as it serves as a habitat for numerous animals, supports tourism, and underpins infrastructure. Microbially induced calcite precipitation (MICP) is a novel method to enhance erosion resistance in sandy soils using the non-pathogenic bacterium Sporosarcina pasteurii. S. pasteurii produces urease to catalyze urea into bicarbonate, which drives the precipitation of calcium carbonate. Maximal expression of urease is a limiting factor for …

Development Of A Flexible In Vitro Model System For Studying Biomineralization In Humans And Marine Organisms, Reed J. Harper

UNF Graduate Theses and Dissertations

Biomineralization is a process where cells control the supersaturation of ions and spatiotemporal deposition of numerous proteins to guide biomineralization, resulting in hard mineralized tissues with complex structures and novel properties. The mechanisms of this process are not well understood but key components have been identified as critical for biomineralization to occur. The cellular expression of intrinsically disordered proteins (IDPs) and the subsequent post-translational modification (PTM) play a role in stabilization of mineral precursors, control of morphology and growth, phase/polymorph selection, and composition of mineral formed. Currently in vitro model systems use either synthetic polymers, native proteins extracted from mineralized …

Experimental Validation Of Optical Wireless Communication And Power Transfer For Uav Applications, Fnu Dhruv

UNF Graduate Theses and Dissertations

Unmanned Aerial Vehicles (UAVs) have revolutionized emergency response, disaster assessment, and search-and-rescue operations. However, their operational efficacy is fundamentally constrained by limited battery endurance and the susceptibility of traditional radio-frequency communication to disruption in adverse weather. To address these limitations, this thesis proposes and experimentally validates a novel architecture integrating Free-Space Optical (FSO) communication with Simultaneous Lightweight Information and Power Transfer (SLIPT). This system utilizes a split-beam configuration to concurrently enable high-bandwidth data transmission and optical energy harvesting to replenish the UAV's battery pack. The research was conducted in three progressive phases. Initially, system feasibility was established through rigorous optical …

The Effects Of Weathering On The Very High Cycle Fatigue Behavior Of Aluminum 6061-T6, Rama Albatesh

UNF Graduate Theses and Dissertations

Aluminum 6061-T6 is commonly used in structural and transportation applications due to its strength-to-weight ratio, corrosion resistance, and ease of manufacturing. In many practical situations, components made from this alloy experience cyclic loading while exposed to environmental conditions such as humidity, temperature changes, and ultraviolet radiation. These factors can affect surface integrity and fatigue performance, especially in the very high-cycle fatigue (VHCF) regime.

This study aims to explore how accelerated weathering impacts the ultrasonic fatigue behavior of Aluminum 6061-T6. First, assess the material through tensile testing to determine its mechanical properties. Then conducted microstructural analysis using optical microscopy, scanning electron …

Implications Of Quantum Computing For Enterprise Cybersecurity And Data Integrity, Manikantha Varaprasad Inakollu

Computer Science and Engineering Faculty Publications

Quantum computing represents a paradigm shift in computational capabilities that poses both unprecedented threats and opportunities for enterprise cybersecurity. This research examines the implications of quantum computing advancement on current cryptographic systems, data protection mechanisms, and organizational security frameworks. Through analysis of quantum computing developments from 2019-2024 and surveys of 280 cybersecurity professionals across various industries, this study identifies critical vulnerabilities in existing encryption standards and explores emerging quantum-resistant solutions. The findings reveal that approximately 78% of enterprises remain unprepared for quantum threats, with current RSA and ECC encryption systems facing potential compromise within the next 10-15 years. The research …