Engineering Commons^™

Synthesis And Characterization Of Composite Hydrogels For Tissue Engineering: An Investigation On Mechanical Properties And Biocompatibility, Ismael Lamas Jr.

Theses and Dissertations

This study investigates the fabrication and characterization of Polyvinyl Alcohol (PVA)/agar double-network (DN) hydrogels for biomedical applications, focusing on mechanical strength, biocompatibility, and tissue engineering potential. Techniques like swelling ratio analysis and Fourier-transform infrared spectroscopy (FTIR), alongside antibacterial and cytotoxicity assays, were employed to evaluate the hydrogels' properties. Results show that increasing agar content enhances mechanical and physical properties, with swelling ratios increasing by 300% when agar makes up 6% of the hydrogel, compared to 140% without agar. A positive correlation was observed between agar concentration and compressive and tensile moduli. Load-relaxation rates, essential for viscoelastic properties, also improved with …

Development And Tribological Characterization Of Uhmwpe-Tin Composite Coatings Deposited By Electrostatic Spraying, Jarrod Keith Perez

Theses and Dissertations

The increasing demand for inert, wear-resistant, cost-efficient, environmentally friendly, and low-friction coatings has driven extensive research into polymer-based solutions. Among these, ultra-high-molecular-weight polyethylene (UHMWPE) has emerged as a strong candidate due to its low density, anticorrosion properties, self-lubricating nature, affordability, and ease of processing. However, its low load-bearing capacity limits its widespread use in high-stress tribological applications. To overcome this limitation, this project investigates the development and characterization of UHMWPE composite coatings reinforced with titanium nitride (TiN) particles at varying concentrations (2.5, 5, and 10 wt%) to enhance their mechanical properties and wear resistance.

Virtual Makeup And Technology Integration, Vishwa Bhatt

Electronic Theses, Projects, and Dissertations

The Virtual Makeup Streamlit application presents an advanced approach to digital cosmetic try-on by allowing users to apply makeup to their facial images in real time. This project uses computer vision and web technologies to create an interactive and user-friendly platform that capitalizes on the increasing popularity of virtual try-on solutions in the cosmetics industry.

At its core, the system uses effective facial detection and semantic segmentation techniques to recognize and separate facial areas such as lips and hair. Techniques such as U-Net and Resnet, and Midepipe are used to create accurate segmentation masks, which are essential for accurate makeup …

Multistage Random Key Genetic Algortihm Optimization For Scheduling Flexible Flow Lines With Sequence Depenedent Setup Times, Aadithan Anbuvanan

All Theses

This thesis proposes a new variation to the Random Key Genetic Algorithm (RKGA) for scheduling optimization in flexible flow line manufacturing with sequence dependent setup times. The proposed RKGA representation decodes scheduling information independently at each stage, unlike the traditional RKGA, which is only sequenced based on the first stage, limiting flexibility. The proposed method's performance is compared to the traditional method with varying numbers of jobs and stages. It is compared regarding performance ratio and statistical significance of differences through the Wilcoxon Signed Rank Test. Results show that the proposed RKGA outperformed traditional RKGA in high complexity (8 Stage …

Impact Of Shear Flow On Marine Biofilms Using Hyperspectral Imaging, Shantanu Mahesh Kore

All Theses

Various microbial communities in marine biofilms cause biofouling on submerged surfaces, posing challenges to marine industries. Despite their ecological and economic importance, biofilms' biomechanical and biochemical responses to hydrodynamic shear stress are insufficiently understood, particularly in dynamic flow conditions. To fill this gap, our study uses an innovative fiber-optic hyperspectral imaging (HSI) system and a supercontinuum laser source to examine marine biofilms' structure, composition, and detachment behavior at different shear stress levels.

To detect spectral and spatial heterogeneity in live biofilms without labeling, we created a custom imaging pipeline that captures reflectance spectra in the 600-850 nm range, targeting microbial …

Reinforcement Learning For High-Dimensional Tradespace Exploration In Multi-Objective Optimization, Aaditya Kothavade

All Theses

Engineering design optimization often requires balancing multiple competing objectives while navigating complex, high-dimensional tradespaces. Despite significant advances in tradespace exploration techniques, current methods face critical challenges in efficiently navigating high-dimensional design spaces. As the number of design variables and competing objectives increases, traditional multi-criteria decision-making and optimization methods struggle to explore the vast solution space comprehensively. The curse of dimensionality exacerbates this issue, making it impractical to analyze all possible solutions and effectively identify trade-offs between objectives. Additionally, the computational complexity of high-dimensional spaces further complicates optimization, making exhaustive solution analysis infeasible. Traditional multi-objective optimization methods rely on static Pareto-front …

False Information Attack Detection In A Connected Vehicle Environment With Quantum Inspired Long Short-Term Memory, Jean Michel M. Tine

All Theses

Wireless communication Systems enabling Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) data exchange, supported by technologies such as Cellular-V2X (C-V2X), has introduced significant cybersecurity challenges, particularly the threat of false information attacks that can compromise traffic safety and efficiency. In this thesis, the author focuses on identifying false information cyber-attack on V2I, in which vehicles are sending Basic Safety Messages (BSMs) to a Roadside Unit (RSU) and RSUs are collecting, processing and communicating data back to Connected Vehicles (CVs) to support different CV applications. Despite advances in anomaly detection using Long Short-Term Memory (LSTM) networks, these models often struggle with computational efficiency …

Berm-Leveling Machine For Peach Orchards: Incorporation Of Tree-Sensing Feature And Profitability Study, Shubham Singh

All Theses

Root collar excavation extends the productive life of peach trees in Armillaria root rot-infested soil, but the process requires trees to be planted on berms. Berm-planted peach orchards restrict the mobility of workers and machinery and can lead to increased erosion in furrows on either side of the berms. The current inter-tree berm-leveling machine depends on the driver's command to dodge the peach trees. The objectives of this thesis were to (1) integrate the feeler, infrared, and LiDAR-based tree sensing systems in the berm-leveling machine to make the soil excavating head's movement independent, (2) measure the impact of finger weeder-based …

Lightlink: Visible Light Communication For Batteryless Devices With Variable Computational Load, Charles Phillips

All Theses

Visible Light Communication (VLC) devices have been experimentally proven to work as a suitable communication medium for batteryless devices. However, the effects of practical load have yet to be fully explored. To that end, we have developed LightLink, a new MAC and PHY layer protocol for VLC within batteryless devices, and have studied various ways that computational load can affect transmission accuracy in realistic scenarios. Our key findings point us towards an adaptive VLC reception system based on inferred environmental variables.

Developing Reduced Order Models For Gas Bubble Formation In Irradiated Metals Using Integrated Phase Field Modeling And Koopman Operator Theory, John M. Eggemeyer V

All Theses

Irradiation damage in materials is prevalent in nuclear components, posing significant risks in the safety and reliability of nuclear reactors. Phase field models offer a versatile framework for modeling irradiation damage in materials at mesoscales. Such high fidelity method has been used to model the formation of fission gas bubbles superlattice, a microstructure array occurs at certain irradiation conditions (dose, dose-rate, and temperature). To overcome the high computational cost of phase field modeling, Koopman operator theory is applied to create reduced order models, allowing for instantaneous simulations of fission gas bubble behaviors. These low fidelity models are integrated into machine …

Evaluating The Role Of Electrostatic Forces In The Adsorption Of Perfluoroalkyl Substances To Granular Activated Carbon, Thomas A. Mccall

All Theses

In response to new drinking water regulations announced by the EPA in 2024, many municipalities will need to monitor concentrations and implement new treatments to address PFAS, a class of anthropogenic organic contaminants. A leading technology for this application is GAC adsorption due to its familiarity and availability. The adsorption of four PFAS species (PFBA, PFBS, PFOA and PFOS) to Calgon Filtrasorb400 (F400) was evaluated for a range of pH and ionic strength conditions to investigate the role of electrostatic interactions in adsorption capacity. These PFAS are all strong acids, so pH was used as a control for GAC surface …

Graph Based Deep Reinforcement Learning Aided By Transformers For Multi-Agent Cooperation, Michael S. Elrod

All Theses

Mission planning for a fleet of cooperative autonomous drones in applications that involve serving distributed target points, such as disaster response, environmental monitoring, and surveil- lance, is challenging, especially under partial observability, limited communication range, and uncertain environments. Traditional path-planning algorithms struggle in these scenarios, particu- larly when prior information is not available. To address these challenges, I propose an innovative framework that integrates Graph Neural Networks (GNNs), Deep Reinforcement Learning (DRL), and transformer-based mechanisms for enhanced multi-agent coordination and collective task ex- ecution. My approach leverages GNNs to model agent-agent and agent-goal interactions through adaptive graph construction, enabling efficient …

Blockchain-Integrated Version Control For Secure And Transparent Software Supply Chains, Iwinosa W. Aideyan

All Theses

The software supply chain encompasses all stages of software development and delivery from initial coding and version control to integration and deployment. As development environments become increasingly distributed and reliant on external dependencies, ensuring the integrity, auditability, and consistency of code changes has become a pressing challenge. Traditional version control systems like Git, while effective for collaboration and tracking revisions, do not inherently provide tamper-evident commit histories. Features such as history rewriting (e.g., git rebase, git push --force) can be exploited to manipulate commit logs without detection, posing risks in security-sensitive domains. This thesis proposes a blockchain-integrated version control framework …

Gene Editing Combined With Apap Diet-Mediated Selection In A Ldlr-/- Mouse Model Of Familial Hypercholesterolemia, Pramita Suresh

All Theses

Cell-based gene therapy has garnered significant interest in treating familial hypercholesterolemia (FH), an autosomal co-dominant disorder characterized by elevated low-density lipoprotein cholesterol (LDL-C) levels. However, achieving a therapeutic threshold level of engraftment of gene-modified cells is a significant hurdle. In FH, as in most liver diseases, the transplantation of healthy gene-modified hepatocytes does not result in a selective advantage for the healthy hepatocytes over native hepatocytes for clonal expansion in the liver. In FH, as in most liver diseases, the transplantation of healthy gene-modified hepatocytes does not provide a selective advantage for the healthy hepatocytes over native hepatocytes regarding clonal …

Defining Fidelity For Tradespace Application, Aditya Agrawal

All Theses

This research proposes a definition of tradespace fidelity and presents a study on its effectiveness in the tradespace. Tradespace exploration helps evaluate various design options, allowing engineers to make informed decisions in early design stages. Fidelity generally refers to how closely a model approximates reality. However, the definition of fidelity has been inconsistently defined and interpreted in various contexts concerning particular problems. In some cases, it is a measure of accuracy; in others, information; in another, uncertainty; and in others, computational complexity. Fidelity is poorly and inconsistently defined in the literature. In general, higher fidelity models tend to be more …

A Parametric Study Of Compact Wind Borne Debris In Tornadoes, Akash Yadav

All Theses

Debris lofted and transported by tornadoes is a significant source of damage during these storms. Several approaches have been taken to model such debris flight, ranging in complexity from fine-scale CFD simulations to coupling the compact debris flight equations with simplified analytic models for the tornado vortex. Both approaches have their merits, though the latter comes with significantly lower computational costs. Despite the simplifications, this second approach has successfully captured details of debris flight events established in post-tornado forensic surveys. Herein, we take advantage of the low computational cost of the latter approach to undertake a detailed parametric study of …

Mechanistic Insights Into Polymer-Assisted Graphene Exfoliation: The Roles Of Velocity, Adhesion, Cohesion, Temperature, Peeling Mode, And Edge Defect Via Coarse-Grained Molecular Dynamics, Linjiale Dai

All Theses

Graphene exfoliation is a critical step in the fabrication of high-quality graphene

layers. However, the underlying fracture mechanisms remain poorly understood. In this

work, I employed coarse-grained (CG) molecular dynamics (MD) simulations to

investigate how factors such as interfacial binding energy, substrate cohesion, temperature,

peeling mode, and edge defects influence the outcome of the exfoliation process. To model

polymer-assisted mechanical exfoliation, I used a finite-size system in which multilayer

graphene (MLG) is sandwiched between two thin polymer films. Leveraging the

spatiotemporal efficiency of the CG model, I performed fifty simulation iterations per

parameter set and analyzed the results from a …

Development Of Aczel-Alsina Aggregation Operators In Neutrosophic Cubic Sets For Multi-Expert And Multi-Criteria Weighting: Optimizing Alternative Fuel Technology Selection, Majid Khan, Muhammad Gulistan, Aitazaz A. Farooque, Mohammed M. Al-Shamiri, Witold Pedrycz

Neutrosophic Systems with Applications

Managing vague and uncertain data has long been a challenge in decision-making (DM), particularly in scenarios where criteria and expert assessments play a critical role. This paper introduces operational laws based on Aczel-Alsina (AA) norms within Neutrosophic Cubic Sets (NCS) to more effectively handle uncertainty. Leveraging these operational laws, we propose two aggregation operators: the Neutrosophic Cubic Aczel-Alsina Weighted Averaging (NCAAWA) and the Neutrosophic Cubic Aczel-Alsina Weighted Geometric (NCAAWG) operators. These provide a comprehensive approach to data aggregation, preserving both additive and multiplicative influences on outcomes in complex systems. In DM, the importance of weights is paramount, and we introduce …

2025 Spring Graduate Recognition Program, Propulsion Research Center, Robert Frederick

PRC Graduate Recognition

This program includes the graduate recognition program for spring 2025. Includes photographs, upcoming events, recent publications, and student profiles.

Manipulating Martensitic Transformation And Residual Stress Development In Stress Superposed Incremental Forming Of Ss304, Elizabeth M. Mamros, Fabian Maaß, Thomas Gnaupel-Herold, A. Erman Tekkaya, Brad L. Kinsey, Jinjin Ha

Faculty Journal Articles

Stress superposition is one of the strategies used in metal deformation processes to increase the material formability, decrease the required forming forces, and create highly customized components. To investigate the effects of tensile and compressive stresses superposed to the single point incremental forming (SPIF) process, experiments and numerical simulations were conducted for a stainless steel 304 (SS304) truncated square pyramid geometry. Tensile stresses were superposed in-plane on the specimen blank by a custom hydraulic frame, and compressive stresses were incorporated via a polyurethane die. Identified parameters for a martensitic transformation kinetics model for SS304 were used in a two-step finite …

Observing Mesospheric Gravity Waves With Nasa's Awe Mission And Correlating To Gnss Tec Maps, Jaime Aguilar Guerrero, Björn Bergsson, Sehin Mesfin, Pavel Inchin, Matthew Zettergren, Ludger Scherliess, Yucheng Zhao, Dominique Pautet

Space Dynamics Laboratory Publications

The Atmosphere Waves Experiment (AWE) is a NASA mission launched on November 9, 2023, and installed on the International Space Station (ISS). Its primary goal is to detect and characterize atmospheric gravity waves (AGWs) by measuring Earth’s mesospheric hydroxyl (OH) airglow with its key instrument, the Advanced Mesospheric Temperature Mapper (AMTM). Since its deployment, AWE has been quantifying the seasonal and regional variability of AGWs, investigating their occurrence and potential sources, and enabling the assessment of their broader impact on the atmosphere by comparing measurements at different altitudes by other instruments. AWE has collected extensive imagery and temperature data capturing …

Groundwater Storage Dynamics In Abu Dhabi Emirate Using In-Situ And Grace Data, Tala Jalal Maksoud

Theses

Water scarcity presents a significant challenge to the sustainable development; especially in arid regions like Abu Dhabi Emirate. Addressing concerns over nonrenewable aquifer depletion, caused by agricultural expansion and lifestyle advancements, has, therefore, become crucial in such regions. This thesis investigates Groundwater Storage (GWS) dynamics in Abu Dhabi Emirate by integrating satellite data from the Gravity Recovery and Climate Experiment (GRACE) with in-situ data from 257 wells over two decades (2002-2022), employing GIS and RS technologies. The main aim of this study is to provide a comprehensive approach to evaluate GWS dynamics considering multiple perspectives including: dealing with missing datasets, …

Hierarchical Frameworks For Scaling-Up Multi-Agent Coordination, Minghong Geng

Research Collection School Of Computing and Information Systems

Multi-agent reinforcement learning has emerged as a powerful framework for developing collaborative behaviors in autonomous systems. However, existing MARL methods often struggle with scalability in terms of both the number of agents and decision-making horizons. My research focuses on developing hierarchicalapproaches to scale up MARL systems through two complementary directions: structural scaling by increasing the number of coordinated agents and temporal scaling by extending planning horizons. My initial work introduced HiSOMA, a hierarchical framework integrating self-organizing neural networks with MARL forlong-horizon planning, and MOSMAC, a benchmark for evaluating MARL methods on multi-objective MARL scenarios. Building on these foundations, my recent …

Networked Multi-Agent Deep Reinforcement Learning Framework For The Provision Of Ancillary Services In Hybrid Power Plants, Muhammad Ikram, Daryoush Habibi, Asma Aziz

Research outputs 2022 to 2026

Inverter-based resources (IBRs) are becoming more prominent due to the increasing penetration of renewable energy sources that reduce power system inertia, compromising power system stability and grid support services. At present, optimal coordination among generation technologies remains a significant challenge for frequency control services. This paper presents a novel networked multi-agent deep reinforcement learning (N—MADRL) scheme for optimal dispatch and frequency control services. First, we develop a model-free environment consisting of a photovoltaic (PV) plant, a wind plant (WP), and an energy storage system (ESS) plant. The proposed framework uses a combination of multi-agent actor-critic (MAAC) and soft actor-critic (SAC) …

Wide Lock-In Energy Harvesting From Vortexinduced Vibrations Of A Deformable Cylinder, Ahmed Raafat Mostafa

Theses

Energy harvesting from ambient sources has gained attention due to increasing energy demands. Despite VIV-based harvesters showing significant potential, their lock-in region, where significant power is generated, is narrow. Given the continuously varying ambient conditions of fluid currents, harvesters can easily fall into de-synchronization, yielding low energy output. Existing solutions like tunable masses or multiple degrees of freedom systems increase complexity and weight, limiting practical applications. This work introduces a novel variable diameter cylinder mechanism—a practical technique that actively tunes the cylinder’s geometry in real time to enhance energy harvesting efficiency from VIV. The mechanism employs an expanding pulley system …

Identifying Barriers, Challenges And Opportunities Of Implementing Retrofitting Strategies In Existing Buildings In The Uae, Ahmad Ghalib Masri

Theses

The built environment of the UAE faces sustainability challenges because of its high energy usage and greenhouse gas emissions which require successful retrofitting methods to enhance aging buildings' performance and efficiency. This research investigates the barriers and challenges and opportunities of retrofitting strategy implementation in the UAE to provide direction for policymakers and stakeholders regarding sustainable practices. The research employed a mixed-methods approach through literature reviews and stakeholder surveys and interviews. The study shows that high upfront costs (68% of respondents) and building owner awareness limitations (54%) and fragmented regulations with inconsistent thermal insulation standards across emirates represent major barriers. …

A Study Of The Impact Of Balancing, Geometric Transformation, Generative Networks, And Roi Techniques In Eye Diseases Classification, Sghaira Hareb Alnuaimi

Theses

Automatic detection of ocular diseases helps medical professionals efficiently identify eye disorders, reduce diagnostic errors, and accelerate diagnoses to prevent blindness. Deep learning has been successfully utilized in various fields, including medical image classification. However, in spite of these advancements, challenges remain in ocular disease classification.

The objective of this work is to address these challenges using data processing, data augmentation in combination with Region of Interest (ROI) techniques. Medical datasets often suffer from scarcity, imbalance, and low-quality images, leading to inaccurate classification. To mitigate these issues, we utilize the ODIR dataset, which contains 7,000 labelled training images for both …

Utilization Of Imidazolium Ionic Liquids For Enhanced Oil Recovery In Harsh Emirati Tight Carbonate Oil Reservoirs, Noran Hussein Mousa

Dissertations

In response to the increasing global demand for energy and the limitations of traditional chemical oil recovery methods, this study explores the potential of imidazolium-based ionic liquids (ILs) as enhanced oil recovery (EOR) agents for Emirati tight oil reservoirs. Four ILs—C10mimCl, C12mimCl, C12mimBF4, and C16mimBr—were evaluated for their effects on the interfacial tension (IFT), wettability, emulsification, and rheological properties under reservoir conditions. Experiments conducted at varying salinities, temperatures (up to 110°C), and IL concentrations (500–3000 ppm) demonstrated that longer alkyl chain ILs, particularly C16mimBr, effectively reduced IFT by >99% and improved wettability by lowering contact angles down to 15.37°. Statistical …

Tracing Wave Induced Flow Field Surrounding Reef Balls, Alexis Scheele

Theses and Dissertations

This study aims to explore the wave-induced flow dynamics around Reef Ball models using dye tracing techniques. Reef Balls are hemispherical artificial reefs with a hollow center and cavities throughout each face, they are designed in this manner to enhance coral reef restoration. Reef Balls rely on wave energy and current motion to facilitate water circulation and nutrient exchange within and surrounding their structure. To understand how wave action influences flow patterns around these artificial reefs, a scaled model experiment was designed to simulate real-world conditions. The experiments were conducted in the wave flume at Florida Institute of Technology’s Surf …

Effects Of Different Blue Light Conditions On Saos-2 Cell Viability, Differentiation, And Mineralization, Jamielyn Alcantara Jarvis

Theses and Dissertations

Photobiomodulation (PBM) is a low-intensity light therapy that uses non-ionizing forms of energy to induce a directed cellular response. Prior work has investigated the effects of blue light exposure at energy densities ranging from 1 J/cm2 to 10 J/cm2 on osteogenic differentiation of human gingival mesenchymal stem cells (hGMSCs), human dental pulp stem cells (hDPSCs), and stem cells from the apical papilla (SCAPs) and shown promising outcomes at 4 J/cm2 and then having a detrimental impact at higher energy densities. One key caveat in prior studies is that the blue light energy density was modulated by changing the light exposure …