Engineering Commons^™

Catalytic Deoxygenation Of Oleaginous Biomass To Renewable Diesel And Sustainable Aviation Fuel Via Decarboxylation/Decarbonylation, Chukwudalu Great Umenweke

Theses and Dissertations--Chemistry

Several technologies have been developed to produce hydrocarbon biofuels – renewable diesel (RD) and sustainable aviation fuel (SAF) – from fats, oils, and greases (FOG), with the hydroprocessing of esters and fatty acids (HEFA) representing one of the most mature pathways. In its current form, HEFA is mainly reliant on the hydrodeoxygenation (HDO) reaction, which has several drawbacks since HDO requires large amounts and pressures of hydrogen, feedstocks of high purity and cost, as well as problematic sulfided catalysts that risk contaminating the biofuel product with sulfur. A process based on decarboxylation/decarbonylation (deCO_x) offers an attractive alternative to …

Development And Prototyping Of A Modular Quadruped Towards Testing Standardization For Legged Robot Stability, Michael Conner Larsen

Graduate Research Theses & Dissertations

Legged robots are well-suited for navigating uneven and unmapped terrain, making them valuable in various robotics applications. Maintaining balance and stability in such environments relies on a combination of sensors, control strategies, and mechanical design. However, selecting the most effective sensing and control method for a given use case remains challenging. Previous studies have explored various approaches, integrating combinations of joint angle measurement, inertial measurement units (IMUs), torque-based control, leg force measurement, image processing, and machine learning, paired with numerous controller designs, which can contribute to stability. However, direct comparisons of these methods are often limited by the need for …

Characterization Of A Large-Scale Electrohydrodynamic Vortex Confinement Flow For Particle Agglomeration, Sanjay Dangi

Graduate Research Theses & Dissertations

With industrialization and the increasing use of microplastics and nanoparticle-based products, the concentration of fine particulate matter (PM2.5) in the biosphere has increased due to the disposal of manufacturing waste and expired parts. If inhaled, PM2.5 can have detrimental health effects, as these particles can travel deep into the lungs and even penetrate blood vessels. Conventional fabric filters used for indoor air quality control have drawbacks, including the need for periodic filter replacement and a high-pressure drop across the filter over time, which leads to increased power consumption. In power plants, electrostatic precipitators (ESPs) are primarily used to collect fly …

Piv Visualization Of A Sinusoidal Ehd Confinement Flow Induced By Variation In Ion Density For Electrostatic Particle Agglomeration, Md Eyasin Hossain

Graduate Research Theses & Dissertations

Long-term exposure to PM2.5, which is responsible for four million cardiovascular-related deaths worldwide, is a major concern as people spend 90% of their time indoors. Fabric filters have been commonly utilized for particle pollution control in indoor settings. However, the maintenance cost of fabric filters is relatively high, as particle accumulation on filters can lead to higher pressure drops (45 ∼ 300 Pa) and energy consumption, as well as the growth of biological organisms and the generation of airborne pathogens. An electrostatic precipitator (ESP) is filterless and widely used in the electric power industry for collecting coal fly ash. ESPs …

Md Simulation Of Femtosecond Laser-Controlled Melting Of Multiple Core-Shell Nanoparticle Systems, Shivansh Patel

Graduate Research Theses & Dissertations

This thesis presents a molecular dynamics (MD) simulation study of femtosecond laser-induced melting and heat transfer in multiple Cu–Al core–shell nanoparticle systems. The research builds upon previous single-particle studies and extends the investigation to multiple interacting nanoparticles to better understand nanoscale thermal transport and melting behavior under ultrafast laser irradiation. Understanding this process is essential for improving laser-based additive manufacturing and sintering of metal matrix nanocomposites (MMNCs), where precise control of heat flow and particle bonding determines the final material quality. The simulations were performed using the Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) integrated with the Modified Two-Temperature Model (MTTM). …

Simulated Efficiency Of A Modified Bmw I3 Traction Motor Operating As An Isolated Dc-Dc Converter, Shayne Taylor

Graduate Research Theses & Dissertations

Battery electric vehicles are currently fighting to have any advantage over internal combustion engine powered vehicles to reduce global transportation greenhouse gas emissions. Electric motors are typically deemed as the largest source of loss in many vehicles but have recently become more efficient on average than the AC-DC converter used to charge the vehicle. This paper investigates the potential for a dual three phase electric traction motor based on a BMW i3 electric vehicle traction motor to take the place of an isolated DC-DC converter, an important part of the AC-DC converter. This electric machine in simulations produced a similar …

Synthetic Data–Driven Early Prediction Framework For Acute Kidney Injury In Patients Receiving Vancomycin And Ceftazidime/Avibactam, Maryam Ramazani

Graduate Theses, Dissertations, and Problem Reports (ETD)

Background: The nephrotoxic risks of combining ceftazidime/avibactam (AVI) with vancomycin (VAN) remain underexplored, despite both agents independently being linked to acute kidney injury (AKI). This study assessed the risk of AKI associated with concurrent VAN and ceftazidime/avibactam (VAN-AVI) therapy and developed synthetic data models to enable early prediction of AKI.

Methods: We conducted a retrospective analysis using electronic health record data from hospitalized adults between 2015 and 2022. The incidence of AKI was compared among patients receiving VAN-AVI or VAN in combination with piperacillin/tazobactam (VAN-TPZ) versus VAN monotherapy. AKI was defined as a composite of de novo and recurrent AKI …

Parametric Analysis Of Proppant Selection Impact On The Hydraulic Fracture And Productivity Of Extended-Reach Marcellus Shale Wells, Nicholas Hunter Lapinski

Graduate Theses, Dissertations, and Problem Reports (ETD)

Hydraulic Fracture Proppant is the gateway to reservoir connectivity, allowing for decades of natural gas production from hydraulically fractured wells in the Marcellus Shale. The proper selection of proppant can have major ramifications on the productivity of the extended-reach Marcellus shale wells. The proppant penetration into the induced fracture attempts to close the gap between the realistic non-uniform fracture conductivity and the idealistic uniform fracture conductivity. Consequently, the more proppant residing within these fractures, the more likely the proppant is to resist crushing due to the compaction. Phenomena, Advancements have been made to create more durable proppant types or proppant …

Recovery Of Iron And Aluminum From Acid Mine Drainage For Beneficial Uses, Katelyn Renee Pepe

Graduate Theses, Dissertations, and Problem Reports (ETD)

Acid mine drainage (AMD) is a widespread issue across the globe, in which some of the most critical cases are created by the mining industry. Researchers have investigated ways to derive benefits from AMD, such as precipitating rare earth elements (REEs) to generate potential revenue from AMD treatment and supplement market demand. However, the bulk of precipitated sludge is composed of iron and aluminum, which also have market value but are discarded in current practice.

Using the Omega site in West Virginia (WV) as a representative AMD source, the objectives of this study are (1) to determine a replicable precipitation …

Sustainable Hemp Industrial Panels (Ship) And Its Industrial Possibilities For The Replacement Of Oriented Strand Board (Osb), Anthony Ollins

Masters Theses

This study explores the feasibility of using industrial hemp fiber to create composite panels—termed Sustainable Hemp Industrial Panels (SHIP) as a potential competitor for oriented strand board (OSB), a commonly used structural wood product. Given hemp's historical and environmental advantages, including rapid growth, carbon sequestration capacity, and material strength, this research investigates its performance when combined with Urea-Formaldehyde (UF) resin, and in a hybrid form with Southern Yellow Pine (SYP). Two hemp-based composites were produced and tested: one with hemp and UF, and another with hemp and SYP. Using a custom-built hydraulic press, composite panels were fabricated and subjected to …

Framework For Development Environment Selection In Digital Twin Applications, Carlos Dodero Fernandez

Graduate Theses, Dissertations, and Problem Reports (ETD)

Digital Twin (DT) technology, a cornerstone of Industry 4.0, facilitates real-time synchronization between virtual models and physical manufacturing systems, enhancing operational efficiency and decision-making. However, its widespread adoption is hindered by the absence of standardized methods for selecting Development Environments (DEs) for DTs, compounded by challenges in cost, interoperability, and connectivity with Industrial Internet of Things (IIoT) protocols. This thesis proposes a Systematic Selection Framework to address this gap, offering a structured methodology to evaluate DEs based-on visualization quality, scalability, interoperability, and cost-effectiveness for manufacturing applications. The framework categorizes and compares sixteen DEs into Game Engines, Robotics Engines, and Simulation …

Delineating Underground Geological Formations: An Integrated Lidar And Camera-Based Approach For Enhanced Feature Identification In Poorly Lit Mining Environments, Timothy James Batchler

Graduate Theses, Dissertations, and Problem Reports (ETD)

Underground mining environments present challenges in accurately identifying geological formations and potential hazards due to poor lighting conditions and confined spaces. Traditional imaging methods often fall short, making it difficult to detect critical geological features such as limestone, shale, and other rock formations. This research addresses these challenges by integrating camera imagery with Light Detection and Ranging (LiDAR) data to improve geological formation detection in poorly lit mining settings.

LiDAR, with its ability to generate high-resolution three-dimensional models in low-light or dark conditions, offers a promising solution to these limitations. By combining LiDAR’s precise 3D models with camera imagery, the …

Physics-Informed Neural Network Based Aerodynamic Modeling Framework, Nathaniel E. Michek

Graduate Theses, Dissertations, and Problem Reports (ETD)

Significant advances have been made in developing aerodynamic models over the years. While these advances span many modeling techniques and data collection methods, certain aerodynamic regimes still pose significant challenges. These regimes commonly occur when an aerodynamic body is under extreme flight conditions. Many of these conditions occur simultaneously in the rare and poorly understood case of a tumbling aerodynamic body. The flight of a tumbling aerodynamic body goes through the entire range of aerodynamic angles, alpha and beta, causing significant non-linearities and time-dependent effects associated with flow separation. During tumbling, the aerodynamic body simultaneously rotates about all three axes …

A Strategic Infrastructure Improvement Framework For Intermodal Transportation Networks, Ayoub Abusalih

Graduate Theses, Dissertations, and Problem Reports (ETD)

In this research, we propose a novel approach to design infrastructure networks for intermodal freight transportation systems, which incorporates railways, highways, and inland waterways (IWW). The objective of our study is to identify the optimal set of hubs to be built and operated over an extended time, based on the projected domestic cargo demand. Unlike traditional hub location models, our approach introduces hybrid hubs, where hybrid transportation modes are integrated to facilitate cargo handling. This innovative integration enables more efficient intermodal connections, leading to tangible reductions in operating costs, and carbon emissions. Specifically, we propose a mixed integer programming model …

Expanding The Vibrating Sharp-Edge Spray Ionization Toolkit For Oligonucleotide Characterization, Sultan Mahmud

Graduate Theses, Dissertations, and Problem Reports (ETD)

A gentle or soft Ionization process is a critical component in native mass spectrometry (MS) to lift the biomolecules from the bulk solution into the gas phase environment of the mass spectrometer preserving their shape, topology and non-covalent interactions. Electrospray ionization (ESI) facilitates structural preservation of proteins, nucleic acids and their complexes and as a result it has been extensively used in native MS. However, in negative ion mode, ESI is somewhat limited in sensitivity due to corona discharge effect resulting from the requirement of a high amount of voltage. This often disrupts the ESI process and may not preserve …

Customer Segmentation And Fuel Economy Prediction Using Telemetry Data From Heavy-Duty Trucks, Batishahe Selimi

Graduate Theses, Dissertations, and Problem Reports (ETD)

Heavy-duty trucks constitute only a modest fraction of on-road vehicles, yet their intensive duty cycles and high fuel demands yield a disproportionately large share of transportation fuel use and greenhouse gas emissions. Addressing this imbalance requires data-driven tools that capture the realities of fleet operation and translate complex telemetry into actionable insight.

This dissertation introduces a unified machine-learning framework that operates exclusively on high resolution time-series data collected from fifty-nine diesel trucks deployed across Southern California. It begins by constructing a multi-modal feature space that blends statistical summaries of key engine signals, static vehicle descriptors, and Mel-Frequency Cepstral Coefficients, thereby …

Leveraging Synthetic Data For Efficient Training Of Ai Models For Real-World Object Detection, Reinaldo A. Moraga

Graduate Research Theses & Dissertations

Modern computer vision (CV) systems largely depend on real-world data for training, which is costly in terms of time, materials, and resources. As industries push toward automation and Artificial Intelligence (AI) -driven solutions, the need for enabling more efficient model training is growing. The primary aim of this work is to explore a framework tailored for industrial applications that uses synthetic images generated from 3D models to train a CV model capable of real-world object detection. This approach seeks to reduce the time, cost, and resources typically required for training AI models with real-world data. This work presents a method …

Order Acceptance And Detailed Scheduling In A Make-To-Order Job Shop With Discrete And Batch-Processing Machines, Dheeban Kumar Srinivasan Sampathi

Graduate Research Theses & Dissertations

In today's ever-evolving production landscape, characterized by a growing demand for personalized products to enhance consumer satisfaction, the strategy of pursuing high-mix, low-volume manufacturing has gained importance. More than ever, manufacturers are adopting the Make-To-Order (MTO) approach, aiming to balance efficient cost management by meeting strict customer deadlines. This research explores the complex state of job shop scheduling, a significant challenge faced by manufacturing entities trying to optimize production time and costs while making the best use of their machinery and resources. The primary concern is the dynamic relationship between order acceptance and scheduling within a job shop environment, which …

Identification Of Potential Superconductor Quench Precursors Using Frequency Domain Feature Analysis, Benjamin C. Roehrig

Graduate Research Theses & Dissertations

Superconducting magnets are important pieces of technology in the world of particle accelerators, allowing researchers to study atomic and subatomic phenomena, among other things. In some instances, superconductors can lose this non-resistive property in a phenomenon known as quenching, which can cause damage to the magnets. This potential danger prompts the introduction of systems to predict when a quench is imminent; one such implementation is through the use of acoustic sensors that detect vibrations within the magnet. Within these acoustic sensor signals, significantly above-noise disturbances (referred to as ”events”) can be identified. Our research applies the statistical framework of a …

Material And Mechanical Characterization Of Sla 3d Printed Graphene Nanoplatelet-Based Nanocomposites Fabricated Within A Magnetic Field, Soka Suliman

Graduate Research Theses & Dissertations

The process of utilizing a static magnetic field to fabricate a nanomaterial-based composite via a stereolithography (SLA) 3D printing process is still a relatively new approach within the field of additive manufacturing. By using this magnetic field during the 3D printing process, both material and mechanical properties can be oriented and axially varied for enhanced characteristics. In this investigation, between 0% to 2% volume fractions of high aspect ratio, graphene nanoplatelets (GNP) are suspended within UV-curable resin during a SLA 3D printing process with a static magnetic field applied. The objective of this investigation is to determine the effect of …

Human Swarm Interaction Using Non-Verbal Communication, Arunim Bhattacharya

Graduate Research Theses & Dissertations

This research presents experimentally validated strategies for human-swarm robotic interaction through nonverbal communication. Applications of this work are in large-scale coverage problems that include search and rescue operations and environmental monitoring missions. The non-verbal interaction becomes critical in situations where wireless communication methods may be limited by bandwidth constraints, privacy concerns, or environmental clutter. The research objective of this dissertation is to design and evaluate methods of nonverbal communication between a human teleoperator and robotic swarms towards a bidirectional human-swarm interaction framework. Towards this, we first establish a reliable measure of real-time cognitive load that can serve to close the …

Monte Carlo Modeling Of Spin Polarized Photoemission From Gaas At Low Temperatures And Positive Electron Affinity Surfaces, John Rison Callahan

Graduate Research Theses & Dissertations

Research and development of new photocathode materials are essential to the continuing success and productivity of accelerator technology. High-quality photocathodes characterized by high quantum efficiencies, long lifetimes, low mean transverse energies, and robustness to vacuum environments and operation loads are becoming increasingly essential to the successful operation of the next generation of high brightness accelerator applications. For nuclear and high-energy physics experiments and other applications that rely on spin-polarized electron beams, photocathodes must also demonstrate high electron spin polarizations. The development of state of-the-art spin-polarized photocathodes will require both development of methods to improve the quality of already existing cathode …

Electric Vehicles Historical Sales, Minerals Demand Risks, And Supply Chain Dynamics, Md Saidur Rahman

Electronic Theses and Dissertations

The growing adoption of electric vehicles (EVs) is transforming the automotive industry as governments, businesses, and consumers seek sustainable transportation options. This thesis examines the Electric Vehicles Historical Sales, future demand, key minerals demand risks, focusing on critical supply chain dynamics and sustainability challenges that influence EV production scalability. Specifically, the research explores demand forecasts and resource needs under policy scenarios from the International Energy Agency (IEA): the Stated Policies Scenario (STEPS), Announced Policies Scenario (APS), and Net Zero Emissions by 2050 Scenario (NZES). Key materials analyzed include lithium, cobalt, and nickel, assessing potential bottlenecks in sourcing, refining, and logistics. …

Facial Chick Sexing: An Automated Chick Sexing System From Chick Facial Image, Marta Veganzones Rodriguez, Thinh Phan, Arthur F.A. Fernandes, Vivian Breen, Jesus Arango, Michael T. Kidd, Ngan Le

Computer Science and Computer Engineering Faculty Publications and Presentations

Chick sexing, the process of determining the gender of day-old chicks, is a critical task in the poultry industry due to the distinct roles that each gender plays in production. While effective traditional methods achieve high accuracy, color, and wing feather sexing is exclusive to specific breeds, and vent sexing is invasive and requires trained experts. To address these challenges, we propose a novel approach inspired by facial gender classification techniques in humans: facial chick sexing. This new method does not require expert knowledge and aims to reduce training time while enhancing animal welfare by minimizing chick manipulation. We develop …

Development Of A Compliant Soft Gripper With Embedded Force Sensors, Ayman Abbas, Abdelrahman Said, Tamer Kahlil, Mahmoud Magdy

Mechanical Engineering

Robotic manipulators have the capability to perform repetitive tasks with a level of efficiency and precision that exceeds the capabilities of human operators. Currently, they are commonly found and extensively utilized across various disciplines. However, robotic manipulators have gradually begun to make inroads into fields beyond manufacturing, such as medicine and agriculture. Due to the diverse range of industries utilizing robotic manipulators, the nature of tasks assigned to these devices can often be more intricate and multifaceted than conventional assignments. Hence, conventional mechanical grippers may not always be suitable, prompting a growing need for grippers capable of adapting to effectively …

Design Of Modular Soft Gripper For Harvesting, Mostafa Abdelaziz, Ahmed Reda, Abdulrhman Atef, Mahmoud Magdy

Mechanical Engineering

Soft robotics presents a transformative approach to agricultural automation, addressing the limitations of traditional mechanical systems in handling delicate crops. This paper introduces a modular soft robotic gripper designed for gentle harvesting applications, with a focus on adaptability, precision, and crop safety. The gripper's performance was evaluated through Finite Element Analysis (FEA) and experimental testing, targeting its ability to conform to objects of varying shapes, sizes, and fragility. The FEA confirmed the gripper's capability to apply a load based on the gripped crop of the range 0.6 – 0.75 N, sufficient for damage-free harvesting of sensitive produce like strawberries and …

Design And Implementation Of Smart Automation For Sustainable Plastic Recycling With Iot Integration, Mostafa Abdelaziz, Mahmoud Khedr, Amr Bakkar, Yossef Zidan, Abdelrahman Youssef, Mahmoud Magdy

Mechanical Engineering

Plastic pollution poses a critical environmental challenge, infiltrating ecosystems and impacting human health. One innovative solution involves repurposing recycled plastics into interlocking blocks as a sustainable alternative to concrete in construction. However, manual production methods hinder scalability, efficiency, and product consistency while generating material waste. This research addresses these limitations by automating the production process using PLC and IoT technologies. The findings demonstrate that automation significantly enhances production rates, ensures consistent quality, and minimizes waste, thereby improving operational efficiency and environmental sustainability. IoT is integrated to enhance the system's capabilities by providing real-time connectivity and data exchange. The IoT dashboard, …

Pre-Programmable Directional Stiffness In Continuum Robotic Arms: Effects Of Truss Configurations, Mostafa Abdelaziz, Zahy Elgendy, Mahmoud Magdy

Mechanical Engineering

This paper investigates the implementation of trussed designs in modular tendon-driven continuum arms (CAs) to address stiffness and stability limitations while maintaining adaptability. Various truss configurations— Single-Level, Combined-Level, and Alternated trusses—were analyzed using Finite Element Analysis (FEA) to evaluate their impact on flexural and axial stiffness under realistic loading conditions. Results demonstrate that truss placement significantly influences performance, with bottom-level trusses improving flexural stiffness by up to 33%, middle-level trusses enhancing axial stiffness by 43%. Further, Combined-Level configurations provide superior overall stiffness, with MiddleBottom trusses achieving a 66.5% improvement in flexural stiffness and a 70.9% increase in axial stiffness, while …

Multi-Objective Monitoring Of Cvd Diamond Micro-Grinding Tools Using Acoustic Emission And Force Signals With Neural Network Optimization, Ahmed Elkaseer, Jianfei Jia, Bianbian Meng, Bing Guo, Jun Qin, Guicheng Wu, Huan Zhao, Zhenfei Guo, Qingyu Meng, Qingliang Zhao, Honghui Yao, Amr Monier

Mechanical Engineering

Micro-grinding has been widely used in aerospace and other industry, and its application was mainly the asymmetric microstructure. Chemical Vapor Deposition (CVD) diamond has drawn attention for its good wear resistance. However, the small diameter and high spindle speed may cause difficulties on the monitoring of the micro-grinding processes. In order to solve the mentioned problem, a novel multi-objective monitoring method of structured CVD diamond micro-grinding tool based on acoustic emission (AE) and force signals is presented in this study to achieve the high efficiency of the tool condition and grinding quality. The relationship between the grinding quality, tool condition, …

Integrating Machine Learning And Symbolic Regression For Predicting Damage Initiation In Hybrid Frp Bolted Connections, Sherif Sorour

Mechanical Engineering

No abstract provided.