Engineering Commons^™

Study Of Capital And Operation Costs For Reverse Osmosis Desalination Plants, Habiba Mahdy Mohamed

Theses and Dissertations

Desalination is a progressively common solution to supply freshwater in numerous parts of the globe where this resource falls short. Among all desalination techniques, seawater reverse osmosis (SWRO) is the most globally prevalent technology. Evaluating a desalination technology's cost-effectiveness is essential to ensure a well-designed plant can be implemented successfully and within an acceptable budget. In the Egyptian context, where water scarcity heightens the urgency of effective resource allocation, economic indicators such as capital expenditure (CAPEX) and operational expenditure (OPEX) are pivotal in shaping policy and planning decisions. Adopting this integrated financial perspective ensures that desalination projects are not only …

Investigating Solvent Effects On Crystallization Kinetics, Ibrahim Joel

Theses and Dissertations

The use of crystallization for separation is not a recent phenomenon. However, the development of efficient crystallization processes is continually being challenged by the complexity and high cost of new drug substances, coupled with stringent regulatory requirements, which add to the uncertainty surrounding drug launches by pharmaceutical enterprises. Accurate characterization of crystallization kinetics is a key step in crystallizer design, which can be influenced by several factors, including process conditions, scale, and the measurement techniques used for tracking particle evolution. These factors often lead to inconsistencies between kinetic studies, hindering rapid implementation within industrial contexts. This thesis presents a case …

Constraining Nuclear Data Uncertainty Requirements For The 19F(A, N)22Na Reaction For Non-Proliferation Applications, Tyler R. M. Smith

Theses and Dissertations

This thesis explores the requirements on nuclear data uncertainties needed for the use of the ¹⁹F(α, n)²²Na reaction for nuclear non-proliferation applications. An overview of how neutrons are produced from alpha decays in a UF₆ medium is discussed. Calculation demonstrate the role nuclear data uncertainties effect the neutron yield and energy spectra as a function of enrichment.

Isotope Production Modeling In Sodium-Cooled Fast Reactors, Aaron W. Burkhardt

Theses and Dissertations

The accurate prediction of isotopic compositions in Sodium-Cooled Fast Reactors (SFRs) is essential for nuclear forensic analyses and international nuclear treaty monitoring, particularly with the increased global deployment of Generation-IV reactors. This research developed and validated a detailed computational model tailored specifically to the Prototype Fast Breeder Reactor (PFBR), employing advanced Monte Carlo neutron transport methods, sophisticated burnup modeling, and variance reduction techniques. Validation against empirical data from the Experimental Breeder Reactor-II confirmed the model’s accuracy, producing a comprehensive database of isotopic compositions across 301 assembly locations and 580 isotopes through the reactor’s initial operation and equilibrium cycle. The model …

Rotating Scatter Mask System Optimization Study For Determining Optimal Image Recreation, Seth L. Grover

Theses and Dissertations

The Rotating Scatter Mask (RSM) system is a radiation imaging technology currently limited by the mask design and governing identification algorithm parameters. To optimize the RSM design, Dakota—an optimization software—was integrated with a ray tracing code that simulates particle interactions with the RSM detector, and with the Locally Competitive Algorithm (LCA), which reconstructs the source image based on the ray tracing code’s Detector Response Matrix (DRM). Since the original ray tracing code was developed in MATLAB, it was translated into Python to improve compatibility with both Dakota and LCA. The Python version of the ray tracing code was then integrated …

Contract Quality Feature Extraction Using Llm, Aaron C. Washington

Theses and Dissertations

This study explored the potential insights generated from linguistic complexity measurements and large language model (LLM) based assessments on the quality of contract documents. By combining structured True/False prompts with log-probability analysis and ambiguity scoring, the study introduced novel contract-quality assessment methods. Results support a feature-driven approach to contract evaluation, one that offers automated, scalable insights for triaging risk and improving drafting practices. These assessment methods contribute to the growing field of legal natural language processing by offering modular tools for effective contract analysis.

Leveraging Large Language Models (Llms) For Automated Generation Of Sysml V2 State Machines In Guidance, Navigation, And Control (Gnc) Systems, Andrea Louise Ames

Theses and Dissertations

Modern defense systems continue to grow in complexity, placing increasing pressure on engineering workflows to be faster and more adaptable. While Model-Based Systems Engineering (MBSE) with the emerging SysML v2 standard provides a framework for capturing system behavior, its practical use is often limited by the expertise and time required for manual modeling. This research investigates whether large language models (LLMs) can help overcome that barrier by automatically generating SysML v2 state machines from Guidance, Navigation, and Control (GNC) textual inputs. Three LLM Flowise-based models were developed and evaluated: the Structured Transformation Model (STM), which uses a structured extraction and …

Fused-Silica Microelectromechanical Systems For Relative Gravimetry, Ethan Doerstling

Theses and Dissertations

Gravimeters are devices that measure gravitational acceleration which can be used by the United States Air Force (USAF) in the areas of navigation and remote sensing. Fused-silica microelectromechanical systems (MEMS) devices offer capabilities to make inexpensive relative gravimeters with higher thermal stability than common silicon devices while maintaining good gravitational sensitivity. The fused-silica devices in this research were designed, simulated, fabricated, and tested to observe their performance as gravimeters. The devices exhibit properties of highly sensitive accelerometers but the current designs do not qualify as gravimeters. This study provides information to improve the sensitivity and stability of these fused-silica MEMS …

Load Balancing In Mobile Networks Using Deep Reinforcement Learning And Traffic Prediction, Shorouk Raafat Mokhtar Abouamasha

Theses and Dissertations

Wireless communication networks are advancing at a rapid pace, driven by various challenges and ambitious goals. This rapid growth is driven by a range of applications, including technologies like the Internet of Things (IoT), as well as innovations in smart cities, autonomous vehicles, and more. Different applications demand specific performance criteria such as high data throughput, low latency, robust reliability, and efficient energy usage. In this thesis, we investigate two enhancements that can be adopted in wireless networks to tackle the challenges of resource optimization and network management. The motivation behind this is the fact that future networks will face …

Design And Performance Evaluation Of Pv-Powered Ev Charging Stations With Grid Integration And Comparative Analysis Of Dc-Dc Converters For Offboard Chargers, Mohammad Abidur Rahman

Theses and Dissertations

Grid-integrated photovoltaic (PV)-powered electric vehicle (EV) charging stations offer a sustainable solution for reducing grid dependency and fossil fuel consumption in workplace environments. This study proposes a PV-powered EV charging system with an AC bus configuration and grid support to ensure stable and efficient operation. A comparative analysis of four DC-DC converter topologies—Dual Active Bridge (DAB), LLC Resonant, Interleaved Buck-Boost, and Interleaved Buck—is conducted for offboard charging applications. Performance evaluation is carried out using MATLAB/Simulink, considering voltage and current ripple, power density, stress levels, bidirectional capability, and control complexity. Component-level reliability is assessed using MIL-HDBK-217 standards to estimate failure rates …

Leveraging Reduced Order Models And High-Fidelity Simulations For Efficient Multifidelity Uncertainty Quantification Of Thermal Systems, Jakob G. Bates

Theses and Dissertations

Simulation-led design is becoming an important part of thermal systems design. Simulations of thermal systems continue to improve in their fidelity, but this comes with an increased computational cost. Additionally, uncertainty in simulation inputs, such as thermophysical properties, leads to uncertainty in simulation outputs. For simulations to be used rigorously for simulation-led design, this uncertainty must be quantified. Performing uncertainty quantification on thermal simulations is made difficult by their many uncertain parameters and high computational cost. Multifidelity uncertainty quantification is a set of methods that reduce the cost of uncertainty quantification by leveraging high-fidelity, high-cost simulations with low-fidelity, low-cost simulations. …

Experimental Characterisation Of Laser Cladding Of Crniw And Crnifealzr Powders On H13 Tool Steel And Optimisation Of Process Parameters, Martin Vinoth S

Theses and Dissertations

In this work, laser cladding on H13 steel substrate with two different powder compositions CrNiW and CrNiFeAlZr has been carried out. The laser power, powder feed rate, and scanning speed were varied and the clad dimensions, aspect ratio, and dilution percentage were measured. The microhardness found in the CrNiW clad is 834 ± 20 HV0.5, which is higher than that of the CrNiFeAlZr clad (780 ± 20 HV0.5) as well as the substrate (548 ± 20 HV0.5).

The X-ray Diffraction (XRD) patterns identified the common phase creation of Ni3C and Fe3C for CrNiFeAlZr and CrNiW coatings, while the oxide formation …

Uhpc Incorporated With Non-Metallic/ Hybrid Fibers And Industrial Wastes - A Comprehensive Study On The Physical, Mechanical Properties And Performance, Sujitha Magdalene P

Theses and Dissertations

The demand for sustainable and high-performance construction materials has led to the exploration of alternative fine aggregates and fiber reinforcements for Ultra-High-Performance Concrete (UHPC). This study investigates the feasibility of using iron ore tailings (IOT), manufactured sand (MS), and copper slag (CS) as partial replacements for river sand (RS), along with various fiber reinforcements, to enhance mechanical properties, durability, and microstructural integrity in UHPC.

The results indicate that IOT at a 30% replacement level (IOT1) exhibited the highest 56-day compressive strength, outperforming MS and CS. Copper slag was found unsuitable for UHPC due to its lower long-term strength. While both …

Advancing Wood Chip Moisture Content Prediction Using Advanced Generative Ai Techniques, Daniel Esteban Marulanda

Theses and Dissertations

In this study we propose a deep learning method to optimize the classification of wood chip moisture content levels using the Vision Transformer and then ultimately increase the classification performance by creating synthetic images using the diffusion transformer model. In the first chapter of our study, we complete a detailed explanation of how the moisture content levels of 10 different wood chips were gathered ranging from 2 to 50$\%$. This chapter serves as a foundation for subsequent sections, illustrating the challenges associated with the current data collection process, which is both time-consuming and inefficient. Accurately determining moisture content for wood …

An Overview Of Global Navigation Satellite System Reflectometry In Coastal Wetlands, Luke Andrew Redwine

Theses and Dissertations

With rising global temperatures, increasing sea levels, and the accelerated erosion of coastal wetlands, efficient methods for monitoring this vulnerable ecosystem are crucial. Traditional approaches, such as manual surveys, are labor-intensive, hazardous, and invasive to the environment they are attempting to protect, while current remote sensing methods are cost prohibitive and rely on irregular data collection techniques. To address these challenges, a scalable solution is needed for reliable and frequent data collection. This study explores the use of GNSS Reflectometry (GNSS-R) combined with unmanned aerial vehicles (UAVs) to monitor the shifting topology in wetlands with minimal human invasion. By leveraging …

An Updated Viscoplastic Self-Consistent Model To Capture The Effects Of Residual Stress, Microstructural Heterogeneity, And Precipitation In Cold-Sprayed Aluminum Alloys, Aulora Williams

Theses and Dissertations

Cold spray additively manufactured (CSAM) aluminum alloys exhibit heterogenous microstructures and mechanical properties, primarily due to high dislocation densities, sub-grain structures, and variation in inter-particle (intersplat) bonding arising from high-velocity particle impacts. Thermal post-processing has been shown to enhance intersplat bonding, reduce high residual stress concentrations, and lower dislocation densities, thereby improving the overall mechanical properties. Building on previous advancements with a mean-field viscoplastic self-consistent (VPSC) model, integrating intersplat boundary terms, Hall-Petch relations, and physically informed residual stress parameters, the current work extends the model to include precipitates and their effects. Observations of CSAM aluminum 7050 alloy indicate precipitate congregation …

Adaptive Multi-Sensor Fusion For Robust Autonomous Perception In Unstructured Environments, Samantha S. Carley

Theses and Dissertations

Autonomous vehicles commonly employ multiple sensors to perceive their surroundings. Coupling these sensors would ideally improve perception compared to using a single sensor. An autonomous system can be equipped with object localization and classification, often performed using a visual camera to understand a scene intelligently. Object detection and classification can also be applied to LiDAR and infrared (IR) sensors to further enhance scene awareness of the autonomous system. Herein, sensor-level, decision-level, and feature-level fusion are explored to assess their impact on perception and mitigate sensor disagreements. Specifically, the fusing of RGB, LiDAR, and IR sensor data to improve object classification …

A Rapid Artificial Neural Network Interatomic Potential For Bismuth, Lee Michael Mayfield Jr.

Theses and Dissertations

To study molecular dynamics in bismuth, Quantum Espresso was used to create a density functional theory (DFT) database which was then used as the input for rapid artificial neural network (RANN). The RANN interatomic potential that was developed using this database was then validated. Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) was used to create simulations and gather data using the RANN potential. The properties of bismuth, including elastic constants, melting points, and volume change, were calculated and compared to DFT and experimentally observed data. The RANN potential coincided well with these values. The RANN potential shows good predictive capabilities for …

The Importance Of Community: An Investigation Of Stress, Coping, And The Value Of Social Support For First Responders, Brian Reid

Theses and Dissertations

People are designed to be in community with others, to work together and share the load and weight of life. First responders are a community that has not emphasized the importance of social support to mitigate and buffer against the stress inherent in their jobs. This study investigates the sources of stress, coping methods, and social support of first responders. Results from the first study show the impact of workplace and family stress on the first responder is impactful from the beginning. The secondary study finds that adaptive coping methods are the preferred method to cope with stress and that …

Enhancing Profitability In The Air Transport Industry Through Improved Air Passenger Forecasting: A Comparative Analysis Of Arima, Holt-Winters And Lstm Time Series Forecasting Techniques, Megan Skowronek

Theses and Dissertations

Predicting air passenger volumes is crucial for airports and airlines seeking to reduce costs and enhance profitability. Accurate forecasting enables better planning and efficiency improvements within the air transport industry. This study applies LSTM, ARIMA and HW to U.S. air passenger datasets. Each analysis shows a methodology for predicting air passenger volumes across airports, airlines and across airports and airlines simultaneously. ARIMA was found to have limited applicability, since only a subset of the datasets was stationary. LSTM and HW were applicable to all airlines and ARIMA was applicable to no airlines. LSTM had less error compared to HW at …

The Role Of K-12 Educators In Shaping Stem Pathways: Examining Social Capital And Self-Efficacy In Stem Education, Holly Trisch

Theses and Dissertations

This dissertation examines the impact of K-12 educators on students’ pathways in STEM (Science, Technology, Engineering, and Mathematics) by focusing on two main factors: the social capital of K-12 and elementary school teachers and the self-efficacy of preservice teachers in STEM education instruction. The first study investigates the social capital of first year engineering students, emphasizing the relationships and resources they gained during their K-12 education that influenced their decision to major in engineering. A quantitative study using survey data collected from first-year undergraduate engineering students indicates that K-12 educators play a crucial role by providing mentorship and resources that …

A Fine-Tined Bert Model For Improved Querying Of The Unmanned Aerial System Integration Safety And Security Technology Ontology, Minh Hong To

Theses and Dissertations

The use of unmanned aerial vehicles (UAS) in all industries is steadily increasing every year. To govern the use of UAS, the Federal Aviation Administration (FAA) seeks to provide a foundation of rules and regulations for UAS operation in the National Airspace System (NAS). The UAS Integration Safety and Security Technology Ontology (ISSTO) was developed using the Web Ontology Language (OWL) in 2023. In 2024, a query application was developed to search ISSTO for information about the safety and security of UAS operations. While the application is functional, the search results can be further fine-tuned to match what the user …

An Approach To Expanding The Industrial Training And Assessment Center To The Residential Sector, Cailee Addison Bush

Theses and Dissertations

The Industrial Training and Assessment Center (ITAC) conducts no-cost energy audits for small and medium sized industrial and commercial buildings across the United States, with a goal to train students in energy optimization and cost reduction, while helping companies to reduce inefficiencies and waste. Expanding this program to the residential sector can reduce energy usage across the United States, largely due to this sector contributing to 15% of America’s energy usage. This research examines the development of a procedure to transition the ITAC into including the residential sector. To ensure a seamless introduction of this sector, the procedure must contain …

Multi-Modal Sensor Fusion Of Radar And Lidar For Enhanced Navigation In Obstacle-Occluded Environments, Kyler Ashton Farrar

Theses and Dissertations

Multi-sensor fusion is a practical and well-researched methodology to combine a variety of incoming sensory data into an enhanced digital representation of a real-world environment. A typical use-case for multi-sensor fusion is the combination of LiDAR and RADAR data to obtain simultaneous 3D positioning and velocity measurements for a particular RoI (Region of Interest). This study investigates LiDAR/RADAR sensor fusion for enhanced navigation information when placed in obstacle-occluded environments such as highly vegetated areas. Specifically, a novel fusion-map approach is designed and evaluated for use with a LiDAR/RADAR sensor suite to produce a fused cost map to determine optimal and …

Lateral Control Of Autonomous Vehicle Using Deep Cnn And Ampc, Iffat Ara Ebu

Theses and Dissertations

Autonomous functionalities are pivotal for the advancement of Advanced Driver Assistance Systems (ADAS), driving towards collision-free and environmentally sustainable transportation. This thesis presents two distinct studies addressing critical aspects of autonomous vehicle control: lane centering via deep learning and lateral vehicle control using model predictive control. The first study explores end-to-end learning f or autonomous s teering command generation, focusing on lane centering. A convolutional neural network (CNN) model, inspired by NVIDIA’s PilotNet, is employed to directly map raw camera pixel inputs to steering commands, eliminating the need for intermediate feature engineering. The model is trained and validated using datasets …

Investigating Structure-Property Relationships Of Bio-Inspired Gel, Mohammad Moinul Hossain

Theses and Dissertations

High-modulus, stretchable, and resilient hydrogels possess a wide array of promising applications across multiple fields, such as the development of sophisticated prosthetic devices, artificial skin, electronic devices, and soft robotics. Elastomeric biopolymers, like resilin, show high stretchability and resilience, facilitating power-amplified movement in various species essential for feeding and defense mechanisms. To mimic the properties of resilin, we developed a hydrogel system of hydrophobic and hydrophilic components. These gels are synthesized by free radical polymerization of acrylic acid (AAc), methacrylamide (MAM), n-tert-beutylacrylamide (BAM) or n-isopropylacrylamide (NIPAM), and poly (propylene glycol) diacrylate (PPGDA). This research aims to compare the large-strain mechanical …

Wildfire Hydrologic Impacts, Kathleen E. Inman

Theses and Dissertations

Wildfires are essential processes for certain ecosystems but are increasing in severity and occurrence. These increases are negatively changing hydrology. Anticipating the hydrologic changes is necessary for management of effected watersheds, infrastructure, and downstream users. This study hypothesized land cover changes post-fire would increase water temperature and discharge in burned watersheds located in the Willamette Basin. This study (1) evaluated the change in estimated curve numbers (CN) from land cover pre-fire and post-fire to assess expected runoff impacts in watersheds, and (2) identified the significance of actual water temperature and discharge changes using non-parametric statistical analysis. An unburned watershed and …

Interactions Between Different Deformation Mechanisms In Magnesium, Ethan T. Holder

Theses and Dissertations

Magnesium is a strong and lightweight material with the potential to be used for weight reduction in various industries. However, manufacturing magnesium parts is difficult because magnesium is brittle at room temperature. Understanding the underlying deformation mechanisms in magnesium is critical to improving its ductility. In this work a Rapid Artificial Neural Network (RANN) potential was used to perform a Molecular Dynamics (MD) simulation in Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) to study twin formation and growth as well as interactions between different twin modes in a magnesium bicrystal. This work offers insight into the mechanisms of plastic deformation in …

Finite Element Analysis Of Hydroxyapatite (Ha) Coated Porous We43 Magnesium Scaffolds For Simulating Long-Time In Vitro Degradation Using A Continuum Damage Model, Dam Kim

Theses and Dissertations

While magnesium and its alloys are viable biodegradable implant candidates for its similarity of Young’s modulus with human bone and its strong biocompatibility, a pure magnesium scaffold degrades too rapidly to be used in many orthopedic implications. Overcoming this high degradation rate has been one of the biggest technical challenges for Mg-based biomedical applications. This research focuses on validating a finite element analysis framework using a continuum damage model and its application to simulate the degradation process of non-coated additively manufactured WE43 and HA-coated WE43 magnesium scaffolds. This work includes determining model input parameters by matching in vitro experiment results …

Impact Of Circular And Non-Circular Nozzle Exit Geometries On Jet Flow Propagation And Turbulence Characteristics, Hiba Maazioui

Theses and Dissertations

This thesis aims to investigate the impact of nozzle exit geometry on jet flow propagation and turbulence characteristics. Computational fluid dynamics simulations were performed using ANSYS Fluent, employing the Reynolds-Averaged Navier-Stokes (RANS) approach, to compare circular, elliptic, and rectangular nozzle geometries. The analysis focused on velocity distributions, turbulence characteristics, and cross-flow interactions. Results indicate that circular jets have the longest potential core and slowest velocity decay, reflecting lower mixing rates. In contrast, elliptic and rectangular jets have shorter potential cores, faster velocity decay, and elevated TKE peaks, suggesting enhanced turbulence and mixing. These findings highlight the significant role of nozzle …