Engineering Commons^™

Machine Learning Modeling Of In-Situ Effective Thermal Conductivities And Ablation Behaviors Of Ceramic Matrix Composites Under Hydrogen Combustion Environments For Gas Turbine Engines, Jayanta Bhusan Deb

Graduate Studies Theses and Dissertations 2026

Through the integration of experimental characterization, machine learning, deep learning, numerical modeling, and physics-informed artificial intelligence, this dissertation explores the thermal performance of polymer-derived ceramic matrix composites (CMCs) for hydrogen combustion environments. The polymer infiltration and pyrolysis (PIP) process was used to create Yttria-stabilized zirconia (YSZ)-fiber-reinforced ceramic matrix composites, which were then experimentally assessed under hydrogen torch and hydrogen combustion conditions typical of next-generation gas turbine and aerospace propulsion systems. Front- and back-surface temperature measurements were used to continually monitor thermal reactions, and post-test microstructural characterization and numerical simulations were carried out to evaluate material integrity and heat-transfer behavior. To …

De Novo Protein Binding To Zinc Oxide Through Biomineralization Pathways, Jean-Mark A. Francis

Theses and Dissertations

De novo proteins are structurally distinct from proteins found in nature and thus capable of having their amino acid sequence modified to accomplish tasks such as increasing protein-nanoparticle binding without unfolding or decomposing. Zinc Oxide nanoparticles are functionally distinct from their bulk counterparts and are widely used as semiconductors in a variety of fields such as medicine and agriculture. With demand for these nanoparticles increasing, environmentally sustainable methods of Zinc Oxide nanoparticle synthesis are being investigated as an eco-friendly alternative to currently utilized but environmentally hazardous chemical and physical techniques. This research investigates the binding characteristics between Zinc Oxide nanoparticles …

Integrated Corridor Management Framework For Severe Freeway Incidents, Sanjida Afroz Iqra

Graduate Studies Theses and Dissertations 2026

Traffic incidents are a major source of non-recurrent congestion on urban freeways, generating substantial mobility, safety, and economic impacts. Severe incidents that block multiple or all travel lanes are particularly disruptive because they degrade freeway operations and propagate congestion onto surrounding arterials. Effective Integrated Corridor Management (ICM) requires the ability to identify severe incidents, estimate their network-wide impacts, and anticipate the traffic conditions and driver behaviors that contribute to instability. This dissertation develops a data-driven ICM framework to address these challenges using real-world incident, crash, detector, and connected vehicle data from major Central Florida corridors, including I-4 and SR-417. The …

Minimizing Performance Overheads For Crash-Consistency In Disaggregated Persistent Memory, Khan Shaikhul Hadi

Graduate Studies Theses and Dissertations 2026

Compute express link (CXL) enables persistent memory disaggregation with memory pooling and hardware managed multi-host memory sharing capability, resulting in better resource utilization, increased scalability. Persistency-aware applications need to manage crash consistency across the system which results in significant performance overhead. This dissertation systematically investigates performance overhead to achieve crash consistency in disaggregated persistent memory and proposes solutions to enable persistency-aware application scaling for distributed system. First, we study persistent parallel programming to scale computation capability beyond single processor and determine the underlying hardware limitation to adopt lock-free data structure. We propose hardware support to design durable atomic instruction (DAI) …

Communication-Aware Energy Optimization For Electric Vehicles With Adaptive Cruise Control, Shahriar Shahram

Graduate Studies Theses and Dissertations 2026

This dissertation develops information-driven methods to reduce traction energy in battery electric vehicles during adaptive and cooperative cruise control. Physics-grounded energetics are embedded in a predictive controller that accounts for intermittent V2V preview, sensing noise, packet loss, and powertrain limits. To ensure deployability, the nonconvex traction–power map is replaced by locally convex surrogates so each step solves a small, strictly convex QP in real time (average ≈ 70 ms/step on a desktop CPU: 8 cores/16 threads, 4.2–5.0 GHz), leaving margin at typical sampling rates (Ts =0.05–0.10 s; N=15–25).

Across standardized drive cycles from NREL DriveCAT—including FTP–75 (light duty), NREL Class …

Evaluating The Brain-Muscle Connectivity Of Cyclic Ankle Pedaling Movement In A Clinical Setting, Matthew K. Shanosky

Graduate Studies Theses and Dissertations 2026

Clinical neurorehabilitation requires objective biomarkers to accurately detect and monitor neuromotor impairments. While traditional metrics are favored for their efficiency and minimal equipment demands, they typically rely on subjective observation and lack physiological resolution. High-resolution electrophysiological technologies, such as electroencephalography (EEG) and electromyography (EMG), offer objective insights into nervous system dynamics; however, prolonged data acquisition times have hindered their translation into frontline clinics. To bridge this translational gap, this study developed a time-efficient experimental paradigm designed for rapid clinical deployment. Healthy participants completed two initial resting baseline trials before performing an externally paced, dynamic, cyclic ankle movement task utilizing simulation …

Experimental Demonstration Of A Laboratory Scale Packed Bed Reactor For Thermochemical Energy Storage Using Embedded Heating Elements, Zachary Monem

Graduate Studies Theses and Dissertations 2026

Thermochemical energy storage (TCES) is an emerging technology that is being studied as a carbon-neutral renewable alternative to conventional methods of large-scale power generation, such as the utilization of fossil fuels. TCES makes use of thermochemical materials to store and discharge energy in two-step reversible chemical reactions. Among the most promising TCES materials are metal oxides, which possess significantly higher energy storage densities compared to other TCES materials; consequently, thermochemical reactors are used to store and discharge large amounts of energy during reduction-oxidation cycles using metal oxide materials. The current work focuses on the design and experimental demonstration of a …

Study On Fracture Toughness Under Different Modes Through Continuum Damage Mechanics Based Fracture Locus, Yeting Sun

Graduate Studies Theses and Dissertations 2026

Traditional elastic-plastic fracture mechanics (EPFM) relies on crack-tip analysis, whereas continuum damage mechanics (CDM) is typically calibrated from uncracked bodies. This dissertation aims to bridge the gap between these two fundamental branches by explicitly linking fracture toughness with ductile damage models. Based on the assumptions regarding Mode I crack deformation, analytical solutions are derived to establish a novel relationship among Mode I fracture toughness, CDM-based ductile fracture strain, and material strain hardening capability. This theoretical framework is subsequently extended to encompass Mode II and Mode III loading conditions. To validate the proposed relationships, finite element (FE) models are developed in …

Performance Assessment And Design Improvements For An Urban Coastal Detention Basin Under Intensifying Rainfall Extremes, Imiya Mudiyanselage Chathuranika, Agyare Asante, Faeghe Borhani, Xixi Wang, Mujde Erten-Unal, Dalya Ismael

Civil & Environmental Engineering Faculty Publications

Coastal urban areas are increasingly exposed to flooding driven by more frequent and intense rainfall events, rising sea levels, and expanding impervious surfaces. Norfolk, Virginia, a low-lying coastal city with aging stormwater infrastructure, faces heightened vulnerability to these hydrologic pressures. This study evaluates the hydraulic performance of an existing urban detention basin within the Edgewater–Larchmont catchment under 10-, 50-, and 100-year, 2-h design storms using the U.S. Environmental Protection Agency’s Storm Water Management Model (SWMM). Simulations were conducted for both pre- and post-development conditions to assess changes in peak discharge, storage capacity, and water level dynamics. Results show that urbanization, …

Short-Term Response Mechanisms Of Water Quantity And Quality Of Daihai Lake Under Temperature-Driven Changes, Hao Zhang, Xiaohong Shi, Xianhua Li, Junping Lu, Ruizhong Gao, Xixi Wang, Shuhao Zhang, Longmei Xie, Yu Liu

Civil & Environmental Engineering Faculty Publications

Temperature-driven mechanisms involving complex feedback and lag that affect the evolution of hydrological processes and ecological functions in cold- and arid-region lakes represent a core scientific issue in current hydrology and lake ecology research. In this study, based on month-scale temperature and environmental factor data from Daihai Lake in Inner Mongolia from January to December 2023, statistical methods (redundancy analysis, Tukey's test analysis, correlation analysis, structural equation modeling), time series analysis methods (dynamic time warping), and machine learning methods (random forest) were combined. A hierarchical and phased response framework was constructed that encompassed driver identification, path tracing, lag characterization, and …

Flood-Season Surface Water-Groundwater Interactions Across Distinct Geomorphic Units In A Yellow River Great Bend Tributary Basin, Yinlong Wang, Ruizhong Gao, Debin Jia, Xixi Wang, Tingxi Liu, Xiaomin Liu, Shiming Bai

Civil & Environmental Engineering Faculty Publications

Surface water-groundwater interactions are complex in the Great Bend region of the Yellow River. Clarifying water exchange and source differences among geomorphic units is important for understanding regional hydrological processes and improving water resources management. In this study, the Wulanmulun River Basin, a typical tributary of the Yellow River, was selected as the study area. A total of 90 water samples were collected, including 25 river water samples, 43 groundwater samples, and 22 precipitation samples. Gibbs diagrams, multivariate statistical analysis, PMF, and MixSIAR models were used to investigate the hydrochemical and isotopic characteristics, source contributions, and transformation relationships of surface …

Mathematical Modeling And Characterization Of A Variable Stiffness Ankle-Foot-Orthosis, David E.L. Richards

Graduate Studies Theses and Dissertations 2026

Conventional ankle–foot orthoses (AFOs) typically employ static stiffness profiles that do not replicate the dynamic quasi-stiffness of the human ankle during gait. Variable stiffness mechanisms (VSMs) offer a promising alternative solution for gait pathologies, such as foot drop and post-stroke hemiparesis; however, their implementation is limited by the lack of accurate mathematical models capable of predicting force and stiffness characteristics. The objective of this thesis is to develop and validate comprehensive mathematical models describing the kinematics and kinetics of a novel variable stiffness ankle–foot orthosis (VS-AFO). This study derives governing equations to characterize how mechanical adjustments influence the force transmission …

Photothermal Excitation And Optical Interferometric Readout Of Mos2 Nanomechanical Resonators, Sadia Afrin

Graduate Studies Theses and Dissertations 2026

Two-dimensional (2D) materials have emerged as promising candidates for nanoelectromechanical systems (NEMS) due to their exceptional mechanical, optical, and electrical properties. Among these materials, molybdenum disulfide (MoS2) has attracted considerable interest for nanomechanical resonator applications because of its low mass density, high mechanical strength, and semiconducting nature. This thesis presents the fabrication, theoretical modeling, and experimental characterization of suspended MoS2 drumhead resonators. The devices were fabricated by mechanically exfoliating MoS2 flakes from bulk MoS2 crystals and transferring selected flakes onto pre-patterned substrates using a dry-transfer process. Mechanical resonance was excited through photothermal actuation using a modulated blue laser, while device …

Cfd Analysis Of A Full Heat Exchanger Between Ammonia And Supercritical Co2 In Aviation Application, Mairah Ahmed

Graduate Studies Theses and Dissertations 2026

The aviation industry’s transition toward lower-carbon propulsion systems has accelerated interest in alternative fuels, including ammonia–hydrogen fuel blends. In this work, a supercritical CO2 Brayton cycle is integrated with the exhaust stream of a turbofan engine to recover waste heat and utilize it for ammonia preheating and cracking. The recovered thermal energy raises the ammonia temperature to the level required for catalytic decomposition, enabling onboard hydrogen production. The proposed architecture combines ammonia cracking with a high-bypass, two-shaft turbofan engine representative of the propulsion system employed on the Boeing 737 MAX 8. This approach addresses the challenges associated with onboard hydrogen …

Pseudo-Boiling Of Supercritical Co2 In A Parallel-Flow Microchannel And A Micro-Jets Impingement Device And Single-Phase And Two-Phase Heat Transfer Of Subcritical Co2 Jets, Pranzal Ahmed

Graduate Studies Theses and Dissertations 2026

Carbon dioxide (CO2) is gaining attention as a low-toxicity, zero-ozone-depletion refrigerant with a global warming potential of 1, making it an attractive alternative to synthetic HFCs/HFOs. Near its critical point, CO2's thermophysical properties change sharply with small shifts in temperature and pressure — a behavior that can be exploited to enhance heat transfer in trans-critical power cycles and electronics cooling. This dissertation experimentally investigates heat transfer during the pseudo-boiling of supercritical CO2 in a parallel-flow microchannel and a micro-jet impingement device, alongside CO2 flow boiling and single-phase water heat transfer in micro-jet impingement. Using microfluidic devices instrumented with embedded resistance …

Numerical Investigation Of Reacting Flow In Pmma-Fueled Solid Fuel Scramjet Combustors Under Experimental Test Conditions, Hunter Bassett

Graduate Studies Theses and Dissertations 2026

A simplified steady RANS-based numerical study of reacting flow in solid-fuel scramjet combustors is presented to evaluate the ability of commercial CFD frameworks to reproduce key features observed in experimental test sections. The work focuses on solid PMMA fuel in two supersonic combustor configurations: a cavity-assisted flameholding combustor and a variable-angle diverging combustor. The cavity combustor is analyzed as a baseline case and results are compared directly with experimental data. Three combustor geometry states corresponding to ignition, early-burning, and steady-burning conditions are investigated. Meshes are assessed through a systematic grid refinement method to establish grid independence. A novel variable-angle diverging …

Connecting The Existing Fiber Infrastructure To The Future With Antiresonant Hollow Core Fibers, Timothy Bate

Graduate Studies Theses and Dissertations 2026

Optical fiber systems based on solid-core silica waveguides underpin modern telecommunications, high-power laser delivery, precision sensing, and coherent optical systems. However, nonlinear effects, material absorption, and thermal limitations within silica increasingly constrain further scaling in both optical power and transmission performance. Antiresonant hollow-core fibers provide a promising alternative by guiding light predominantly in air, substantially reducing nonlinear interactions, latency, and optical damage while enabling transmission regimes inaccessible to conventional solid-core fibers. Despite rapid advances in antiresonant hollow-core fiber attenuation and power handling, one of the largest remaining barriers to widespread adoption is reliable integration with the existing solid-core fiber ecosystem. …

Integrated Optical Probes For Confocal Scanning Imaging And Adjustable Coherent-Gated Dynamic Sensing, Yonglin Huang

Graduate Studies Theses and Dissertations 2026

Optics and photonics have been one of the most important sciences and technologies that impact modern human life in a big way. For example, fiber-optics for communications and artificial intelligence. Optical probes are critical components for optical imaging and optical sensing technologies that have been actively researched and developed in the past decades. Advanced fiber-optic sensor probes with smaller size, better performance, lower noise, higher photon efficiency, rapid sensing time, and lower cost are needed in many applications, such as nanoscale material science, chemistry, and biomedical fields, etc.  In this project, new fiber-optic sensor probe technologies and integrated micro-optic devices …

Dermatology Skin Lesion Image Analysis, Victoria Wegley, Joshua Hoog, Tristan Crawford, Keith Miller, William Fons, K. Pugh, J. Taylor, S. Swinfard, A. Fernandes, G. Patel, J. Hagerty, W. V. Stoecker, Ronald Joe Stanley

Research Data

Dermatology skin lesion image analysis research has been ongoing at Missouri S&T (previously UMR) since the 1980s. Our group has been successful in finding over 20 key dermoscopic structures in melanoma, melanoma mimics, and nonmelanoma skin cancers using iterative structure-based analysis. Structures are chosen to reduce system errors which are concentrated in a few classes: amelanotic/featureless, regressed, and small in situ melanomas, and the most difficult benign lesions to identify: Clark nevi, lentigines, and seborrheic keratoses [1]. Preliminary research detecting and using annotated lesion structures [2-7] and lesion artifacts [8,9] guided by clinical experience [10] with image processing and deep …

Cognitive Load Classification Using Functional Near-Infrared Spectroscopy, Pratham Shah

Theses and Dissertations (Comprehensive)

This thesis investigates the classification of cognitive load using functional near-infrared spectroscopy (fNIRS) signals recorded during an N-back working memory task. The study introduces a novel short-channel correction layer designed to suppress superficial physiological noise adaptively, addressing limitations of traditional General Linear Model (GLM) based regression. A single participant dataset comprising 69 validated sessions was analyzed using both conventional machine learning and deep learning approaches. Traditional classifiers: Linear Discriminant Analysis (LDA), Support Vector Machines (SVM), Random Forests, and Gradient Boosting were first evaluated using statistical features (mean, variance, peak, and slope). Among these, Gradient Boosting achieved the highest accuracy (55.6%), …

A Novel Federated Llm Framework For Distributed Traffic Modelling In Intelligent Transportation Systems, Seerat Kaur

Theses and Dissertations (Comprehensive)

Intelligent transportation systems (ITS) depend on accurate traffic prediction to support congestion management, infrastructure planning, and real-time operational decisions. Despite substantial progress in data-driven forecasting, several challenges continue to limit practical deployment: traffic data is distributed across independent regional authorities, making centralized aggregation infeasible, standard federated aggregation strategies ignore traffic-specific characteristics that meaningfully affect model quality, and existing models produce only numerical outputs without interpretable reasoning that urban planners can act upon. This thesis addresses these challenges through four contributions that collectively advance privacy-preserving, explainable, and scalable traffic forecasting.

The first contribution provides a systematic review of 129 peer-reviewed publications, …

Taylorkan-Vit: Parameter-Efficient Vision Transformers For Medical Image Classification, Kaniz Fatema, Dr. Emad Mohammed, Dr. Sukhjit Singh Sehra

Theses and Dissertations (Comprehensive)

Effective and interpretable classification of medical images remains a critical challenge in computer-aided diagnosis, particularly in data-scarce and resource-constrained clinical settings where traditional deep learning models prove impractical. This study addresses the fundamental barrier to Vision Transformer adoption in medical imaging—massive parameter counts and data requirements—through a systematic two-phase methodology. Phase 1 evaluates three spline-based Kolmogorov–Arnold Network (KAN) variants to identify the optimal nonlinear approximation function for parameter-efficient medical image classification: SBTAYLOR-KAN (B-splines with Taylor series), SBRBF-KAN (B-splines with Radial Basis Functions), and SBWAVELET-KAN (B-splines with Morlet wavelets). Comprehensive experiments across brain MRI, chest X-rays, and tuberculosis datasets—without any image …

Assessing Dissolved Organic Matter Sources And Dynamics In Urban Stormwater: Implications For Greenhouse Gases, Harper W. Schmalz

Theses and Dissertations (Comprehensive)

Stormwater management ponds (SWMPs) are important aspects of land-use planning and increasingly recognized as active sites of biogeochemical processing that influence carbon cycling; however, little research has investigated the controls on dissolved organic and dissolved inorganic carbon (DOC and DIC) within these systems. This thesis examined the processing and transformations of dissolved carbon between three compartments to support the development of a greenhouse gas (GHG) box-model for urban stormwater ponds, including SWMP sediment, surface water, and vegetation. The objective of this thesis was to assess the biogeochemical processes that govern the rate and transformation of DOC and DIC between these …

Evaluating The Impact Of Cognitive Distraction On Spaceflight-Relevant Task Performance Using Surface Electromyography And Motion Capture, Allyson K. Mitchell

UNF Graduate Theses and Dissertations

Cognitive distraction poses a risk to astronaut performance during complex, multitasking operations in spaceflight environments. This study examined the effects of cognitive load on neuromuscular coordination and task execution using surface electromyography (sEMG) and motion capture. Thirteen participants performed spaceflight-relevant tasks under undistracted and distracted conditions, with distraction induced through verbal questioning. EMG signals from eight upper-extremity muscles were processed using envelope filtering, peak normalization, and time normalization to enable inter-subject comparison, and group-level mean activation with standard deviation was analyzed. While overall muscle activation was similar between conditions, phase-dependent differences were observed, with undistracted trials showing higher activation during …

Mechanical Behavior Of Additively Manufactured Ti-6al-4v Eli Parts: Effects Of Laser Parameter Selection, Samuel Lopez

UNF Graduate Theses and Dissertations

Additive manufacturing (AM) of TI-6AL‑4V Extra‑Low Interstitial (ELI) enables complex geometries for fatigue‑critical medical device applications, yet fatigue performance remains sensitive to process‑induced defects. This work investigates the effect of laser process parameter selection on the microstructure, mechanical properties, and fatigue behavior of TI- 6AL‑4V ELI fabricated via laser powder bed fusion (L‑PBF) using a Renishaw RenAM system. The influence of laser parameters was isolated by holding powder chemistry, build orientation, scan strategy, sub‑transus annealing, and post‑processing constant between a non‑optimized baseline and an optimized parameter set selected based on tensile performance.

Optical microscopy showed the optimized condition exhibited improved …

Structural Batteries For Aerospace Applications, Tariqullah Wardak

Honors Undergraduate Theses

There is increasing pressure on the aviation sector to lower carbon emissions and switch to entirely electric and hybrid propulsion systems. However, the feasibility of standard lithium-ion batteries for long-range aircraft is limited, as they add substantial weight and occupy significant volume. Structural batteries, which combine load-bearing capability with energy storage, offer a potential pathway to lighter and more efficient aerospace systems.

This work investigates a carbon-fiber-based structural battery that utilizes carbon fiber as both a current-collecting, load-bearing electrode and a component of the composite structure. In contrast to lithium-ion chemistries, a zinc-based aqueous electrolyte is chosen for better environmental …

Preventing G/J Tube Dislodgement: A Device And Communication Innovation, Sarah Clark

2026

The Problem
G/J tube dislodgement is a frequent complication in pediatric patients
Leads to:

• Emergency department visits
• Hospital admissions
• Delays in nutrition/medication

Impact on Patients & Families:

• IV placement (traumatic)
• Radiation exposure
• Overnight hospital stays

Impact on Nurses & System:

• Increased workload (admissions, coordination)
• Occupied inpatient beds for stable patients
• Inefficient care processes

Aims/Objectives
Aim: Reduce unplanned G/J tube dislodgements and related hospital utilization.
Objectives: Develop a breakaway connector prototype

Implementation and Evaluation
Setting: Pediatric inpatient & outpatient system
Participants: Nurses (bedside, GI, IR), caregiver, innovation team
Process:
Roundtable discussions → identified workflow gaps
Communication/workflow audit
Developed device …

Using A Study Journal To Support Class Engagement And The Development Of Entrepreneurial Mindset Habits, Otilia Popescu, Dimitrie C. Popescu

Engineering Technology Faculty Publications

Engineering Technology programs were historically introduced to support non-traditional students and offer college pathways for students working and having already a developing career. This is even more true in the current academic environment, with a large percentage of students enrolled in engineering technology programs being either fully or part-time employed, active or retired military, and at different stages in their lives, usually with families to care for. Often, non-traditional students attend classes online, either synchronously or even more often asynchronously, due to their schedule constraints. Course instructors regularly face schedule or time management constraints from the students’ side, and they …

Towards Supporting Real-Time Estimation Of Vehicle Fuel Consumption And Co2 Emissions In Smart City Applications, Abrar Alali, Stephan Olariu

Computer Science Faculty Publications

This paper evaluates a simplified physics-based energy demand model designed to estimate vehicle fuel consumption and CO₂ emissions—a critical tool for sustainable transportation planning and smart city applications. Unlike data-driven regression models that lack generalizability for user-defined conditions or complex physics-based approaches that rely on extensive, often proprietary data, the simplified model is distinguished by its minimal parameter requirements, depending primarily on a single, overarching powertrain efficiency value. A key contribution is the comprehensive empirical evaluation of the simplified model against official Environmental Protection Agency (EPA) test data across multiple driving cycles and vehicle types, providing a rigorous validation previously …

Privacy-Preserving Federated Learning With Optimized Ensemble Weighting And Knowledge Distillation For Covid-19 Detection From Non-Iid Medical Imaging Data, Richard Annan, Hong Qin, Robert Newman, Madhuri Siddula, Letu Qingge

Computer Science Faculty Publications

Medical imaging enables rapid and accurate diagnosis of COVID-19, with CT scans proving especially effective. However, data privacy concerns limit collaborative model development across hospitals. To address this issue, we introduce a novel federated learning framework. It is referred to as Independent Knowledge Distillation with post-Ensemble Federated Learning (IKDEFL). Differential Privacy (DP) is integrated into the framework to improve privacy guarantees. Three DP mechanisms are evaluated. These include Fixed Gaussian, Gaussian Adaptive, and Tree Adaptive. The evaluation has been conducted on heterogeneous and Non-Independent and Identically Distributed (Non-IID) datasets. These datasets reflect real-world hospital scenarios. Results show that IKDEFL significantly …