Engineering Commons^™

Advancement Of The Zinc Ion Battery: Polymer Electrolyte And Electrode Development For Aqueous Zinc-Ion Batteries, Roya Rajabi

Theses and Dissertations

Rechargeable aqueous zinc-ion batteries (ZIBs) have garnered significant attention in recent years as a promising candidate for stationary large-scale energy storage due to their distinct safety features and cost-effectiveness compared to conventional lithium-ion batteries. Despite their great potential, ZIBs are currently facing critical challenges for commercialization, including poor cycle stability at low discharge rates, lower energy density (Wh/kg) and higher self-discharge rate. These issues must be addressed for them to become a viable energy storage solution. The above challenges are fundamentally rooted in the bulk properties of electrolytes and interactions with electrodes, such as; 1) formation of insulating layered double …

Augmented Reality (Ar) And Virtual Reality (Vr)-Based Data Visualization Frameworks For The Manufacturing Industry, Nitol Saha

Theses and Dissertations

Industry 4.0 is transforming the manufacturing industry by integrating digital technologies throughout the production lifecycle, leading to the development of smart factories. The integration of Augmented Reality (AR) and Virtual Reality (VR) alongside smart manufacturing is transforming traditional industry practices by establishing a robust cyber-physical infrastructure, enhanced data visualization, and improved task execution. This thesis aims to develop AR and VR-based data visualization frameworks for the manufacturing industry, focusing on detailed implementation strategies, initial results, and key findings of these frameworks. One major focus of these frameworks is the generalization of the technological assets so that these frameworks can be …

Augmented Reality Based Maintenance Operations And Training, Victor Scott Gadow

Theses and Dissertations

Augmented Reality (AR) is the process of superimposing virtual information on top of objects or other structures in the real-world environment. It is considered one of many paradigms included in the idea of smart manufacturing and can enable a mixture of the other technologies involved. A large increase in research on AR has been seen in the past decade as technologies have begun to evolve to become more robust and reliable. It has been implemented into several key areas of manufacturing such as maintenance, assembly, training, and quality control. The rise of industry 4.0 is changing how data is used …

Characterizing Mechanical Behaviors Of Railroad Ballast Based On Large-Scale Triaxial Tests, Shihao Huang

Theses and Dissertations

Ballast, typically composed of large unbound aggregates with uniform gradation, is essential for the structural integrity of railroad tracks, facilitating load transfer, drainage, and ensuring stability and resilience. The mechanical behaviors of ballast, including shear resistance, resilient modulus, and permanent deformation, are critical for effective railroad design and maintenance, directly impacting track geometry. Degradation of these mechanical properties can lead to significant track-related issues, such as excessive settlement and train derailments, resulting in substantial property damage, injuries, and fatalities. This dissertation aims to characterize mechanical behaviors of railroad ballast from perspectives of aggregate interaction, cyclic loading pulses and climatic conditions, …

Data-Driven Discovery Of Extreme Thermal Materials By High-Throughput Computation And Machine Learning, Joshua Ojih

Theses and Dissertations

The quest for materials with extraordinary properties has been a longstanding endeavor in material science and engineering, driving future technological advancement. However, the discovery of such materials is non-trivial. Recent advancements in computational methods, particularly the integration of machine learning (ML) techniques with density functional theory (DFT), have opened new avenues for accelerating the discovery of materials with exceptional and extreme properties. This dissertation focuses on developing a synergistic approach and workflow combining ML and DFT to identify materials with properties that are pushed beyond current limits, using lattice thermal conductivity (LTC) as a case study of the workflow.

We …

Electroless Deposition And Galvanic Displacement For The Control Of Supported Nanoparticle Size And Composition, Haiying Zhou

Theses and Dissertations

Catalyst performances can be greatly affected by properties such as particle size, composition, geometry, and cleanliness of the active surface. To achieve optimal catalytic performance, appropriate synthesis methods are required to synthesize the desired structures. Supported metal particle catalysts are usually prepared by impregnation and precipitation methods in industry. Although these two methods are simple, they exhibit poor control over surface morphology, leading to a wide particle size distribution and uncontrolled distribution of different metal components. In this dissertation, three topics on controlling surface morphology are discussed.

For structure sensitive reactions, reactivity and selectivity can be strongly affected by particle …

Rational Catalyst Synthesis For Sustainable Energy Applications, Alaba Upe Ojo

Theses and Dissertations

Energy accounts for two-thirds of the global climate challenges. Effective utilization of green hydrogen or finding cleaner ways to improve energy generation is necessary to combat climate crisis and allow for a more sustainable future. This work evaluates three heterogeneous catalytic processes which contribute to a sustainable future. In chapter 2, we studied the hydrogenation of toluene to methylcyclohexane; a reaction that can potentially serve as a medium for hydrogen storage and help to overcome the safety challenges of transporting gaseous hydrogen. We found that palladium catalysts on certain carbons exhibited significantly enhanced toluene hydrogenation rates compared to activated carbons …

Real-Time Robot Pose Estimation For Industry 4.0: Enhancing Motion Validation And Monitoring With A Vision-Based Framework, Jad Samaha

Theses and Dissertations

Amidst the era of Industry 4.0, robots became integral to automated production lines by performing complex tasks with high precision and adapting to changing production needs in real-time. Therefore, ensuring their precise and reliable operation is paramount for maintaining high-quality standards and operational efficiency. This invoked the need for an automated motion validation tool that guarantees accurate program task execution, by detecting deviations or anomalies that may indicate mechanical faults or software errors. Given the exponential advancements in AI, particularly in Computer Vision, a vision-based solution is ideal for ensuring the correct positioning of a robot in real-time. Operating independently …

Redefining Gas Turbine Engine Development: A Digital Twin Framework Informed By Operational Dynamics And Numerical Analysis, Sowmya Raghu

Theses and Dissertations

Gas Turbine Engines (GTEs) serve as primary propulsion systems in aviation and are key for power generation units in various industrial applications. The conventional Gas Turbine Engine Development and Monitoring Lifecycle (EDML) typically encompasses six stages: preliminary design, numerical analysis, prototyping and testing, manufacturing, systems integration, and subsequent systematic monitoring processes. This dissertation redefines the gas turbine engine design and development process by synergistically integrating design capabilities, real-time operational data, and predictive maintenance through the implementation of digital twins. The primary objective is to establish a comprehensive framework for gas turbine engine design by utilizing thermodynamic and aerodynamic modeling, supported …

Tracking Deposition And Settling Characteristics Of Airborne Metallic Particulate, William Kahale Caspino

Theses and Dissertations

Transport and deposition of metal particles is a source of environmental and public health concern. Understanding how ambient conditions and the properties of the particles interact to influence the dispersal range can provide information on and the possible extent of environmental contamination. Controlled laboratory experiments and modeling were utilized to determine when such particles would deposit. Particle samples containing heavy metals, a Palladium-dominant alloy and a Nickel/Aluminum dominant alloy LANA, were released in a static column, and the vertical displacement was tracked utilizing a Phantom v7.3 camera and a camera lens. Electron microscopy revealed that particles are not spherical and …

Thermal Management Of Power Electronic Devices Using Single Crystal Aln Heat Spreaders, Md Abdullah-Al Mamun

Theses and Dissertations

Due to high critical electric field and saturation velocity, wide bandgap (WBG) III-Nitride semiconductor materials (AlxGa1-xN) and their heterostructures have gone through extensive research in academia and industry for applications requiring high-voltage, high-current, high-frequency, and high-temperature transistor operation. AlGaN/GaN high electron mobility transistor (HEMT) has been commercialized for 650-V power converters, smartphones, PCs, USB wall power outlets, on-board and off-board EV chargers, and numerous other applications. However, AlGaN/GaN HEMTs grown on low-cost sapphire or Si substrates face significant self-heating issues due to the poor thermal conductivity of the substrate. The high thermal resistance (RTH) and heat capacity of the substrates …

A Process Planning Software For Modeling Parameter Behavior In Automated Fiber Placement, Benjamin Jeffrey Francis

Theses and Dissertations

The manufacturing of large-scale, geometrically complex composite structures is often accomplished today using the Automated Fiber Placement (AFP) process. AFP utilizes a fiber placement end effector and a gantry or robotic kinematic system to lay up groups of composite tows, iteratively building the complete structure. The reduced width of each tow allows the deployment of AFP for builds with significant curvature, unlike other automated methods such as automated tape laying. Despite its proven track record and widespread use, the current AFP process contains inefficiencies and suffers from workflow bottlenecks that significantly increase cycle time, material wastage, and overall cost. A …

Development Of Avalanche Photo Detector For Uv-C Using Gallium Oxide Material System, Md Ghulam Ghulam Zakir

Theses and Dissertations

This work describes the metal-organic chemical vapor deposition (MOCVD) optimization process for epitaxially grown gallium oxide (Ga2O3) layers, electrical field distribution, and the design for Avalanche Photo Detector (APD). MOCVD is a well-accepted process in the semiconductor industry, as it is well-known for its precise deposition of ultra-thin, high-quality semiconductor layers with extraordinary control over composition and thickness. The choice of Ga2O3 is due to r its distinctive properties of ultra-wide bandgap and low turn-on resistance. Thus, Ga₂O₃-based materials can withstand high voltage and current with the least energy loss, making them an attractive choice for …

Neuro-Symbolic Ai For Deep Analysis Of Social Media Big Data, Vedant Khandelwal, Manas Gaur, Ugur Kursuncu, Valerie Shalin, Amit P. Sheth

Faculty Publications

This tutorial introduces a neuro-symbolic AI framework to analyze big data from social media platforms. Integrating human-curated knowledge through symbolic AI with the pattern recognition capabilities of neural networks enhances the adaptability and efficiency of traditional neural network approaches. Knowledge-guided zero-shot learning techniques enable swift adaption to new linguistic contexts and emerging events [6]. Participants will explore how to design, develop, and utilize these models in specific domains, such as public health surveillance, that require dynamic adaptation to new terminologies. This session The tutorial aims to equip attendees with practical skills and a deep understanding of how to apply neuro-symbolic …

Boosting Steam Tolerance And Electrochemical Performance Of An La0.6Sr0.4Co0.2,Fe0.8O3− Δ-Based Air Electrode For Protonic Ceramic Electrochemical Cells, Lei Wu, Jiqiang Sun, Huiyang Qi, Baofeng Tu, Chunyan Xiong, Fanglin Chen, Peng Qiu

Faculty Publications

La_0.6Sr_0.4Co_0.2Fe_0.8O_3−δ (LSCF) is the state-of-the-art air electrode material for solid oxide electrochemical cells using oxide-ion electrolytes, yet its application in proton ceramic electrochemical cells (PCCs) remains limited, mainly attributed to its instability under operating conditions of high temperature and high humidity. To address this issue, coating a PrCoO_3−δ (PCO) catalyst onto the LSCF scaffold has been evaluated in this study. The introduction of the PCO coating not only enhances the LSCF electrode's electrochemical performance but also significantly improves its steam tolerance by preventing direct contact between steam and …

First-Order Comprehensive Adjoint Sensitivity Analysis Methodology For Neural Ordinary Differential Equations: Mathematical Framework And Illustrative Application To The Nordheim–Fuchs Reactor Safety Model, Dan Gabriel Cacuci

Faculty Publications

This work introduces the mathematical framework of the novel “First-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Neural Ordinary Differential Equations” (1st-CASAM-NODE) which yields exact expressions for the first-order sensitivities of NODE decoder responses to the NODE parameters, including encoder initial conditions, while enabling the most efficient computation of these sensitivities. The application of the 1st-CASAM-NODE is illustrated by using the Nordheim–Fuchs reactor dynamics/safety phenomenological model, which is representative of physical systems that would be modeled by NODE while admitting exact analytical solutions for all quantities of interest (hidden states, decoder outputs, sensitivities with respect to all parameters and initial conditions, …

Addressing Strain And Porosity Changes Of Battery Electrodes Due To Reversible Expansion Through Dem Simulations, Hunter Teel, Taylor R. Garrick, Srikant Srinivasan, Fengkun Wang, Yangbing Zeng, Sirivatch Shimpalee

Faculty Publications

In this work, discrete element method (DEM) simulations were used to probe changes in electrode porosity, electrode strain, and the resultant pressure changes for composite electrodes comprised of active material and binder particles. Through the results acquired by these simulations, three cases that are representative of two limiting cases for electrode operation, and one case for realistic electrode face pressure during operation were captured and the implications on design and performance are discussed. Predicting changes in the porosity is a unique insight that is difficult if not impossible to capture experimentally but is important for predicting changes in electrochemical performance …

Quantifying The Impact Of Microstructure Variation On Charging Capability In Lithium-Ion Batteries, Hunter Teel, Taylor R. Garrick, Mitchell A. Sepe, Joseph S. Lopata, Srikant Srinivasan, Fengkun Wang, Yangbing Zeng, Sirivatch Shimpalee

Faculty Publications

Through the use of electrochemical simulations, variation in the local onset of lithium plating can be predicted and used to set charging guidelines to reduce the risk of lithium plating. The pseudo-two-dimensional (P2D) model is typically used for capturing this behavior; however, it only provides a global lithium plating onset estimate and does not consider the local variation. With material properties translated to an average continuum value, the P2D model can simulate rapid charge and capture global onset of lithium plating. However, this model lacks the ability to resolve localized behaviors across individual components due to local non-uniformities. Our three-dimensional …

Approximate Computing And In-Memory Computing: The Best Of The Two Worlds!, Mohammed Essa Fawzy Essa

Theses and Dissertations

Machine learning (ML) has become ubiquitous, integrating into numerous real-life applications. However, meeting the computational demands of ML systems is challenging, as existing computing platforms are constrained by memory bandwidth, and technology scaling no longer yields substantial improvements in system performance. This work introduces novel hardware architectures to accelerate ML workloads, addressing both compute and memory challenges. In the compute domain, we explore various approximate computing techniques to assess their efficacy in accelerating ML computations. Subsequently, we propose the Approximate Tensor Processing Unit (APTPU), a hardware accelerator that utilizes approximate processing elements to replace direct quantization of inputs and weights …

Developing A Hierarchical Digital Twin Framework For Dc Microgrid Implementation, Khari Sado

Theses and Dissertations

This research introduces a hierarchical digital twin framework for DC microgrids implementation, particularly those utilized in naval power systems. Unlike traditional digital twins, this hierarchical digital twin structure offers a layered perspective. Hierarchical digital twin design promotes computational efficiency by distributing computational burden across a layered configuration that integrates lower-level digital twin blocks with a system digital twin. The layered approach breaks down complex systems into smaller manageable units that can be examined individually and collectively. Central to this strategy is the adoption of a multi-domain and multi-functional technique through the integration of the digital image framework. This allows the …

The Effect Of Chromium Coatings On Hydrogen Uptake In Zirconium Alloy Nuclear Fuel Cladding, Jorie Lyn Walters

Theses and Dissertations

The amount of hydrogen in a nuclear reactor can have a profound impact on its performance and safety when it is absorbed into or released from fuel rods. Hydrogen pickup in modern fuel cladding materials has been minimized by alloying additions and microstructural texture engineering, but these materials are still susceptible to hydrogen release during high temperature oxidation. The nuclear accident at the Fukushima Daiichi power plant in 2011 resulted in hydrogen gas production and subsequent explosions which led the United States Department of Energy to initiate a program to develop enhanced nuclear fuel cladding materials. New cladding materials include …

End-To-End Full-Width Induction Welding Of Unidirectional Tape-Based Thermoplastic Composites, Jaspreet Singh Pandher

Theses and Dissertations

The current large scale application of thermoset composite materials in large, twin aisle, civil transport aircraft have resulted in significant performance enhancements, such as aerodynamic efficiency, weight reduction, and durability. These large aircraft are, however, produced in relatively low numbers. For the next generation smaller single aisle aircraft, large scale applications of composites are of interest in the airframe. Application of composites in single aisle aircraft will require not only proof of similar and/or significant performance improvements, but also proof of adequate manufacturing rates. One option to achieve both is large scale application of thermoplastic instead of thermoset composites.

Thermoplastic …

Guiding 3d Chiral Self-Assembly At Nano/Micro Length Scales Via 3d Printing, Mohsen Esmaeili

Theses and Dissertations

This thesis delves into the intricate realm of 3D printing bio-inspired materials with tailored nano/microscale architectures. The first chapter investigates the flow-induced alignment of cellulose nanocrystals (CNC) during 3D printing, employing a microfluidic strategy integrated with polarized optical microscopy (POM). Birefringence measurements under varying conditions reveal the influence of initial CNC suspension structures on flow-induced patterns, particularly in the chiral nematic phase. Hydrodynamic simulations complement experimental findings, elucidating the impact on CNC particle alignment, providing insights for designing 3D printed architectures with internal chirality for advanced applications.

The second chapter explores the 3D printing of complex geometries inspired by Bouligand …

Microchannel Slip Flow Characteristics By Time Travel After Photobleaching Velocimetry, Brandon James Sellers

Theses and Dissertations

Interfacial science follows the study of observing behavior between two or more phases of matter when in contact. For example, a liquid solution passes through a microchannel, and the walls interact with the fluid shearing along the surface. The fluid particles develop momentum changes from interfacial phenomena and slip along the wall begins to affect the fluid body. Slip flow is a name for the phenomenon, and with it, modeling velocity for the interfacial behavior demands both resolution and minimal interference. Laser-induced fluorescence photobleaching anemometry (LIFPA) works as a sound method for acquiring data on microchannel flow, but it needed …

Uav-Based Tracking And Following Of Railroad Lines, Keith Michael Lewandowski

Theses and Dissertations

Given the pivotal role of the railroad industry in modern transportation and the potential risks associated with track malfunctions, the inspection and maintenance of railroad tracks emerges as a critical concern. While existing solutions excel in performing accurate measurements and detection, they often rely on large, expensive, and time-consuming platforms for inspections. This project, however, seeks to solve the same problem with the use of an unmanned aerial vehicle (UAV), significantly reducing time and cost while maintaining detection capabilities. In particular, this solution is ideal for large-scale, high-level inspections following major events such as floods [6], hurricanes [7] or earthquakes …

B-Spline Impulse Response Functions For Transient Ssi Analysis Of Pile Foundations, Kingsley C. Ozegbe

Theses and Dissertations

The advent and consequential advancements in geotechnical earthquake engineering has made soil-structural analysis (SSI) an important component in the analysis and design of earthquake resistant structures. The filtering effects of pile foundations which reduces the seismic demand on pile-supported superstructure when they are subjected to seismic waves have been investigated and confirmed by several researchers in the last 40 years. To this end, several methods of analyzing the effects of SSI have been developed over the years. From the simplified Winkler model to the more robust finite element method (FEM) and boundary element method (BEM), researchers and structural engineers alike …

Classifying Floor Accelerations For Gait Estimation And Detection, Jean Michel Franco Lozada

Theses and Dissertations

Structural vibrations are traditionally used to learn about structural systems, such as determining the dynamic characteristics of a structure and evaluating its structural performance under certain dynamic loads. Recently, researchers have proposed the use of structural vibrations to know more about the occupants of the structure in addition to the structure itself. One example of such would be to determine when a person falls, or to identify the location of a person walking in a building. Using structural vibrations to study occupants can be directly applicable to many fields, ranging from healthcare to security applications. One powerful use of structural …

Erodibility Of Sand-Silt-Xanthan Gum Mixtures, Edwin Kotey

Theses and Dissertations

The high frequency of earthen embankment failure recorded during floods has led to the general rule that embankments should not be overtopped. This notwithstanding, overtopping cannot be entirely avoided particularly during extreme events, such as winter storms and hurricanes. Reducing soil erodibility is thus fundamental to prevent and control disasters caused by embankment failure. Recent studies have explored the use of environmentally friendly additives, such as biopolymers, to improve soil properties. Geotechnical tests have shown that biopolymers can effectively increase soil strength, but little is known about biopolymer-treated soil resistance to erosion by flowing water. Results of flume experiments to …

Thermodynamic Modeling Of Uranium Nitride With Select Actinides And Fission Products, Eric Reece Mcmanus

Theses and Dissertations

Uranium mononitride fuel is being investigated as a potential nuclear fuel for a Westinghouse lead-cooled fast reactor due to factors such as its high uranium density, high melting point, and favorable thermal conductivity. To obtain an understanding of the thermochemical behavior of UN fission products and minor actinides, thermodynamic data was obtained from various resources to create a database to represent the behavior of the fuel. This database was used to generate an Ellingham diagram to represent the relative thermodynamic stability of the phases over the reactor temperature range. A simulation was run computing the equilibrium state of the fuel, …

Mathematical Modeling And Reconstruction Of Porous Media To Understand Transport Phenomena For Electrochemical System Applications, Mitchell Sepe

Theses and Dissertations

Alternative power generation has grown significantly in the space of energy production over the last ten years. Development of new technologies to produce energy is vital to the growing need for electricity. Batteries, solar panels, wind turbines, and countless other renewable energy options have been deemed necessary to create an overall greener future. Fuels cells when combined with electrolyzer show a promising system for stationary power generation. Both technologies are comprised of multiple parts in contact that must work together simultaneously to create an ideal environment for catalytic reactions to take place. A crucial component to a properly functioning cell …