Engineering Commons^™

Development Of Dip-Coated Carbon Fibers For Structural Power Composites And Optimization Of Bus Plates For Passively Propagation Resistant Batteries, David Petrushenko

Theses and Dissertations

Increasing demand for lithium-ion batteries in electric vehicles, portable electronics, and electric aircraft is a driving force for the expansion in new battery architectures to achieve higher gravimetric and volumetric efficiencies. In practice, maximizing energy density can be achieved by introducing state-of-the-art materials to increase the capacity of cells or by reducing the system's mass by incorporating lightweight structural materials. An alternative approach is to develop systems capable of performing multiple functions simultaneously that combine mono-functions of the battery and vehicular structure in a multifunctional component capable of storing electrical energy and providing structural support.

The initial focus of this …

Simultaneous Crack & Wave Propagation And Acoustic Emission Signal Modelling Using Peri-Elastodynamic, Md Mushfiqur Rahman Fahim

Theses and Dissertations

This work presents the use of Peri-Elastodynamic, a guided wave simulation method based on meshfree non-local Peridynamics theory. To model simultaneous crack and wave propagation simulation and its application on Acoustic Emission (AE) signal modelling, a new formulation is presented. The field of nondestructive evaluation (NDE) and structural health monitoring (SHM) is slowly embracing the advancement in Machine Learning (ML) / Artificial Intelligence (AI) for better and cost-effective assessment of structures and damage prediction. AI/ML can revolutionize the NDE/SHM field by automating the data collection and analyzing processes. However, the big challenge is that the model needs a sheer amount …

A Plug-And-Produce Connectivity Framework For Manufacturing Systems, Theodros Abraham Tarekegne

Theses and Dissertations

The Industrial Internet of Things (IIoT) movement has birthed technologies that enable the fusing of physical and digital environments. However, the extensive number of available options for industrial communication and data formatting has remained a barrier to achieving digital knowledge synonymy in industry. There have been previous attempts to establish standards for industrial connectivity and communication, but legacy machines, as well as custom and non-proprietary devices, still face issues communicating data with other manufacturing equipment. To address these challenges, the Industrial Internet of Things initiative has led to the creation of the Plug and Produce (PnP) concept to facilitate the …

A Click Chemistry Amplified Nanopore Assay For High Performance Testing Of Protein Biomarkers In Diseases, Xiaoqin Wang

Theses and Dissertations

Nanopore detection technology enables nanometer-scale single-molecule detection, yielding valuable insights into analyte molecules' properties such as size, shape, charge, and concentration. Due to its label-free nature, high sensitivity, and real-time capabilities, it finds widespread application in genomics, proteomics, drug discovery, and environmental monitoring. Click chemistry, encompassing the attachment of a probe or substrate to a biomolecule, termed bioconjugation, features the copper-catalyzed azide-alkyne cycloaddition as a quintessential reaction, forming a 5-membered heteroatom ring. This study harnesses this reaction to craft single-strand DNA probes for nanopore testing, leveraging copper's catalytic properties for signal amplification. Host-guest reaction, a noncovalent bond between molecules, specifically …

On The Use Of Cfd Modeling And Analytic Methods To Describe Pressure Drop In Highly Dense Structured Adsorbents In Gas Separation Processes And Fundamentals Of Adsorption, Ryan Timothy Sanders

Theses and Dissertations

The scope of this work can be divided into two main thrusts on topics found within adsorption. The first, and primary, topic is the use of CFD and analytical modeling to describe the flow of gas through a parallel, structured adsorbent channel which is described in Chapters 1 and 2. Chapter 1 establishes a non-experimental methodology based on using a 3D Navier-Stokes (NS) computational fluid dynamics (CFD) model in lieu of experiments, for developing 1D axial pressure drop correlations for structured adsorbents with parallel channels. Chapter 2 utilizes the methodology established in Chapter 1 in order to develop a new …

Coastal And Inland Flooding - From Advanced Hydrodynamics And Data-Driven Modeling To Multi-Variate Coastal Vulnerability Assessment, Ahad Hasan Tanim

Theses and Dissertations

Flood risks in coastal and inland areas have historically been underestimated and underpredicted, resulting in increased flood damage and loss of human life. Flood risk under climate change and sea level rise will disproportionately impact low-wealth and marginalized communities, as they are often located in areas with less flood protection and have limited resources to adapt to the impacts of flooding. The systematic workflow of the life cycle of FRM is frequently disengaged in the current state of flood hazard assessment with system vulnerability assessment. This research aims to improve the life cycle of FRM by incorporating flood observation, monitoring, …

Field Implementation Of A Stereo Vision System For Rnt And Stress Measurements In Cwr, Brittany Stinson

Theses and Dissertations

The use of Continuous Welded Rail (CWR) provides many advantages to the rail industry compared to the alternatively used jointed-track segments. However, one significant disadvantage is the development of thermal stresses longitudinally in the rail, which is not of concern when expansion joints are used. This is due to CWR’s inability to release thermal expansion in the absence of joints. The Rail Neutral Temperature (RNT) is the temperature at which the rail is in a stress-free state. A desired RNT is calculated based on local climate conditions and CWR installation practices are implemented to set the desired RNT at installation. …

Towards The Induction Welding Of Complex, Curved Thermoplastic Composite Structures, Andrew Cole Cromer

Theses and Dissertations

Recent advancements in the aerospace industry, coupled with the anticipated future significance of air travel, have spurred research aimed at increasing manufacturing production and aircraft flying efficiency by implementing new materials and assembly methods. Advanced air mobility (AAM), a subset of the aerospace industry, is anticipated to become a crucial component of the transportation infrastructure in densely populated regions. To meet the expected demand, there is a need for investigations into novel manufacturing and joining methods. This industry necessitates materials that are lightweight, durable, and amenable to high-rate production. One potential avenue under exploration is the utilization of thermoplastic composites. …

Dynamic Response Evaluation Of Loose Gravelly Soils In Centrifuge Modeling Experiments, Siwadol Dejphumee

Theses and Dissertations

Dynamic behavior of gravelly soil has gained more attention in recent years as several case histories of liquefaction of gravelly soil have been reported. Liquefaction can cause failure of infrastructure, leading to economic damage and loss of life. Gravelly soil has unique characteristics and engineering benefits, providing a prevalent and versatile construction material for various infrastructure projects. Therefore, understanding of the gravelly soil behavior under seismic load is critical for assessing the resilience of infrastructure located in seismically active regions. To date, only a few experimental research studies have focused on the dynamic response of gravelly soil, and these studies …

State Estimation And Prediction Based On Simplified First Principle Model Of Lithium-Ion Batteries In Lebesgue Sampling Framework, Enhui Liu

Theses and Dissertations

State-of-charge (SOC) and remaining-dischargeable-time (RDT) are critical states of Lithium-ion batteries (LIBs). SOC indicates the available charge stored in LIBs compared to the total charge capacity of LIBs, while RDT refers to the remaining dischargeable time that LIBs can support under given loading profiles. Accurate SOC estimation and RDT prediction play important roles in guaranteeing the safe and efficient operation of batteries in real applications.

Taking advantage of high fidelity of simplified first principle (SFP) model of LIBs, this research aims to accurately estimate SOC and predict RDT. Firstly, this research establishes an SFP model to describe the battery internal …

Application Of Machine Learning Techniques And The Unscented Kalman Filter To Real-Time Gas Turbine Clearance Prediction, Donald Earl Floyd

Theses and Dissertations

The growth in renewable energy sources and retirement of large baseload coal-fired power stations has led to an accompanying decrease in reliability and security of the electrical grid. Since renewable energy sources are typically non-dispatchable, this can lead to blackouts and/or brownouts for customers. Heavy duty gas turbine power plants (HDGT) offer a solution to this problem. HDGTs are dispatchable, clean, and offer flexibility in the fuel they consume, but operational limitations must be well understood to fully exploit their benefits.

One of the main operational limitations is the tip clearances in the gas turbine. In many cases, the gas …

The Study And Development Of Autonomous Scarf Repair For Composite Structures: A Focus On Advanced Air Mobility Vehicles, Stephen Hilton

Theses and Dissertations

“I’m sorry I haven’t been able to truly give you a solution to thermoplastic repair” – Arnt. Director GKN Global Tech Center, 2023

The aerospace industry has a prevalence of composite materials due to their outstanding benefits to the mechanical properties of structures while serving to reduce the overall structure weight. With the development of the Advanced Air Mobility market, there is an anticipated growth in the number of composite structures. Also, with the manufacturing environment of the 21st century, these composite structures are more and more being made using thermoplastic composites that can be recycled at the end of …

A Study Of Direct Sensitivity Method Solving Optimal Control Problems With Single And Multiple Time Grids With An Application In An Experimental Hybrid System, Hainan Wang

Theses and Dissertations

Computational methods for optimal control are important for dealing with bottlenecks in industries. By implementing optimal operation strategies obtained from the computational methods into dynamic systems, objectives such as saving energy, reducing cost, exploiting potential, and improving efficiency can be achieved. Computational methods for optimal control have been used in a broad range of disciplines, including aeronautics and astronautics, oil and chemical engineering, power systems, clean energy, biomedical engineering, economics, and management. Due to the great application value of optimal control, its computational methods have drawn worldwide attention. Direct methods are most effective in computational methods for optimal control. Direct …

Enhanced Two-Phase Heat Spreading Enabled By Dropwise Condensation, Kai Luo

Theses and Dissertations

The rapidly increasing power density of electronic systems has raised challenges for thermal management. Efficient heat spreading plays an important role in distributing high-density heat to the large-area heat sink and maintaining the junction temperature below the temperature limit during operation. Vapor chambers, a type of flat heat pipe utilizing two-phase heat transfer and fast travel of vapor flow, can achieve far more efficient two-dimensional heat spreading than most conduction-based thermal ground plane materials. By promoting dropwise condensation in vapor chambers, the thermal performance and scalability can be further improved due to the enhanced condensation heat transfer and unique droplet …

Crystal Plasticity Modeling Of Heterogeneous Microstructure Of Additively Manufactured Metals, Md Mahabubur Rohoman

Theses and Dissertations

Additive manufacturing (AM) has emerged as a promising technique in the manufacturing industry for producing complex metal components as it provides shape freedom and simplistic processing chain.

Powder bed fusion is the widely used AM technique that uses laser or electron beam as the energy source to melt the metal powder and deposit it in a layer-by-layer fashion. While doing so, the previously molten layers are constantly are in re-heating and re-cooling processes which end up creating an intricate solidification for the deposited layers. Due to the complexity involved in the thermal cycles for the solidification process, columnar grains develop. …

Experimental And Computational Understanding Of Solid Oxide Iron Air Battery Performance, Chaitali Morey

Theses and Dissertations

Long-duration energy storage (LDES) (10+ hours) is considered a key technical solution for a widespread penetration of renewable energy into the utility market. However, the currently available storage technologies are limited to less than 10 hours for cost reasons. The benchmark Li-ion battery technology would be economically prohibitive if the storage time goes beyond 4 hours. Therefore, developing new low-cost LDES-compatible battery technologies is highly desirable. A solid oxide iron air battery (SOIAB) has been developed which consists of a reversible solid oxide cell (RSOC) and energy storage unit (ESU) of an iron bed. This battery is considered a promising …

High-Rate Production Of Thermoplastic Composite Structures For Urban Air Mobility Vehicles Utilizing Fastener-Free Assembly Methods, Robert H. Shumpert

Theses and Dissertations

This study aimed to develop a manufacturing plan for a Thermoplastic fiber-reinforced propeller blade for urban air mobility applications. This propeller blade offer a few unique challenges including the complex geometries of the blade. Another important aspect of the blade is using fusion bonding methods to increase the strength of joints in the product while reducing weight from fasteners and adhesives. This manufacturing process will be validated by producing a physical demonstrator to ascertain the efficacy of the manufacturing techniques used. First, the techniques that will make up the manufacturing plan must be selected. To do this, a review of …

Dual-Phase Membrane Reactor And Calcium Oxide-Based Sorbents For High-Temperature Carbon Capture, Utilization And Storage, Kangkang Zhang

Theses and Dissertations

Greenhouse gases, especially CO2 emissions, are responsible for global warming and the reduction of greenhouse gases is vitally important for the sustainability of our modern society. Currently, the most mature CO₂ capture, utilization and storage (CCUS) technology relies on flue gas “amine washing”, a costly and energy intense process that can negatively impact on the efficiency of existing power plants and the cost of electricity produced. Therefore, developing more efficient and cost-effective CCUS technologies is highly imperative. With the increasing production of natural gas in recent years, direct natural gas conversion into valuable chemicals also becomes more attractive than …

A Holistic Quality Management Model For Optimization Of Quality Assurance In Manufacturing, Devon Blakeney Clark

Theses and Dissertations

Quality Management (QM) is essential in manufacturing to ensure products are consistent and functional every time. Consumers expect high quality products that last, and industries unable to accomplish this are destined to fail. Therefore, product quality has always been at the forefront of manufacturer decision making, though it is normally viewed as a given more than as a goal. This means that businesses want quality because it is needed for their survival, but there has not been consideration for how to incorporate innovation into this essential field. Quality needs to be viewed holistically with regards to all manufacturing factors that …

Healthcare Assistance Challenges-Driven Neurosymbolic Ai, Kaushik Roy

Publications

Although Artificial Intelligence technology has proven effective in providing healthcare assistance by analyzing health data, it still falls short in supporting decision-making. This deficiency largely stems from the predominance of opaque neural networks, particularly in mental health care AI applications, which raise concerns about their unpredictable and unverifiable nature. This skepticism hinders the transition from information support to decision support. This presentation will explore neurosymbolic approaches that combine neural networks with symbolic control and verification mechanisms. These approaches aim to unlock AI’s full potential by enhancing information analysis and decision-making support for healthcare assistance.

Evaluating The Role Of Data Enrichment Approaches Towards Rare Event Analysis In Manufacturing, Chathurangi Shyalika, Ruwan Wickramarachchi, Fadi El Kalach, Ramy Harik, Amit P. Sheth

Publications

Rare events are occurrences that take place with a significantly lower frequency than more common, regular events. These events can be categorized into distinct categories, from frequently rare to extremely rare, based on factors like the distribution of data and significant differences in rarity levels. In manufacturing domains, predicting such events is particularly important, as they lead to unplanned downtime, a shortening of equipment lifespans, and high energy consumption. Usually, the rarity of events is inversely correlated with the maturity of a manufacturing industry. Typically, the rarity of events affects the multivariate data generated within a manufacturing process to be …

Review Of Fourth-Order Predictive Modeling And Illustrative Application To A Nuclear Reactor Benchmark. I. Typical High-Order Sensitivity And Uncertainty Analysis, Dan Gabriel Cacuci, Ruixian Fang

Faculty Publications

This work (in two parts) will review the recently developed predictive modeling methodology called “4th-BERRU-PM” and its applicability to nuclear energy systems as exemplified by an illustrative application to the Polyethylene-Reflected Plutonium (acronym: PERP) OECD/NEA reactor physics benchmark. The acronym 4th-BERRU-PM designates the “Fourth-Order Best-Estimate Results with Reduced Uncertainties Predictive Modeling” methodology, which uses the Maximum Entropy (MaxEnt) principle to incorporate fourth-order experimental and computational information, including fourth (and higher) order sensitivities of computed model responses to model parameters, while yielding best-estimate results with reduced uncertainties for the first fourth-order moments (mean values, covariance, skewness, and kurtosis) of the optimally …

Modeling Rate Dependent Volume Change In Porous Electrodes In Lithium-Ion Batteries, Taylor R. Garrick, Miguel A. Fernandez, Brian J. Koch, Erin Efimoff, Matthew Jones, Rafid Mollah, Hunter Teel, Xiaoniu Du, Sirivatch Shimpalee, Song-Yul Choe, Venkat R. Subramanian, Jason B. Siegel

Faculty Publications

Automotive manufacturers are working to improve individual cell, module, and overall pack design by increasing the performance, range, and durability, while reducing cost. One key piece to consider during the design process is the active material volume change, its linkage to the particle, electrode, and cell level volume changes, and the interplay with structural components in the rechargeable energy storage system. As the time from initial design to manufacture of electric vehicles decreases, design work needs to move to the virtual domain; therefore, a need for coupled electrochemical-mechanical models that take into account the active material volume change and the …

Advances In Electrocatalytic Dehydrogenation Of Ethylamine To Acetonitrile, Yanlin Zhu, Dezhen Wu, Jinyao Tang, Dakota Braaten, Bin Liu, Zhenmeng Peng

Faculty Publications

The electrocatalytic dehydrogenation of ethylamine (EDH), owing to its high hydrogen content, holds broad prospects in electrochemical hydrogen (H2) production, H2 storage, and addressing energy issues, thus deserving wide attention. In this feature article, we first summarized the fundamentals of thermocatalytic and electrocatalytic EDH and reviewed the recent state-of-the-art advances in catalyst research, specifically platinum group metal (PGM) catalysts and non-PGM catalysts. We systematically discussed the potential applications of electrocatalytic EDH in energy storage and conversion. Finally, we provide our perspective on the key challenges and future developments in this field. We believe this feature article will offer helpful guidance …

Development Of A Large Format Additive Manufacturing System Based On An Off-The-Self Pellet Extruder, Aywan Das

Theses and Dissertations

Large Format Additive Manufacturing (LFAM), or Big Area Additive Manufacturing (BAAM), was introduced to resolve the limitations of the low deposition rate, low scalability, and therefore long print times, of traditional 3D printing methods when applied to the manufacturing of large structures and tooling. LFAM can be used to overcome the high conventional tooling costs of large structures. However, even with robotic setups, LFAM still mainly relies on quasi-planar, 2.5D printing strategies. This fails to reap the advantages of multi-axis printing, such as improved adhesion, reduced support material use, and the ability to create complex curved surfaces. In this research, …

Improving Tcp Performance Using P4-Programmable Data Planes, Jose Antonio Gomez Gaona

Theses and Dissertations

The Transmission Control Protocol (TCP) forms the foundation of reliable end-to-end communication and is widely used by many applications for efficient data transfers across the Internet. TCP relies on various congestion control algorithms (CCAs) to manage its response to network congestion. These algorithms ensure fairness among competing flows and optimize the use of available bandwidth. However, since TCP is deployed within end hosts, its capacity to attain visibility of network events is constrained. This limitation arises from the closed nature of non-programmable network devices, which prevents researchers from exploring customized actions in response to network events. Recently, the emergence of …

Machine Learning Approaches To The Exploration Of Ammonia Synthesis Catalysts Utilizing Experimental Data, Rasika Jayarathna

Theses and Dissertations

Traditional heterogeneous catalyst discovery process relies upon human expert-guided experiments based on domain knowledge and human intuition supported by catalyst characterization. However, this process is time and resource-consuming and suffers from human bias. Machine learning (ML) models trained on experimental data have the potential to significantly accelerate this discovery process by guiding experiments to optimize the catalyst performance and increase the understanding of the catalysts. Ammonia synthesis catalysts are a class of catalysts widely investigated in the literature, which has generated decades of experimental data. Moreover, ammonia has been gaining attention since it can be used as a carbon-free next-generation …

Investigation Of Ethane Dehydrogenation And Hydrogenolysis On Pt(111), Pt(211) And Pt(100): Bayesian Quantification And Correction Of Dft-Based Enthalpic And Entropic Uncertainties, Mubarak Bello

Theses and Dissertations

Computational investigations of heterogeneously catalyzed reactions using density functional theory (DFT) are often inaccurate, largely due to uncertainties in the choice of DFT functional (enthalpic uncertainty) and approximations for modeling adsorbate movement along the catalyst surface (entropic uncertainty). This work illustrates that both uncertainties are significant in the investigation of the ethane dehydrogenation (EDH) and hydrogenolysis on Pt catalysts by considering the complete deconstruction of ethane on Pt(111), Pt(211), and Pt(100) using microkinetic modeling (MKM). Hence, this work uses both non-calibrated and Bayesian calibrated MKMs to quantify and correct inaccuracies in macroscopic properties due to both uncertainties. A Bayesian approach …

Exploring Shape Dependency Of Catalysts For Chemical Reactions, Kaveh Shariati

Theses and Dissertations

Recent advancements in the synthesis of nanoparticles, particularly one-dimensional (1D) nanoparticles, have significantly enhanced the catalytic activity of various processes by enabling precise control over their morphologies and exposing unique crystallographic facets. The shape of nanoparticles is closely linked to their chemical, physical, electrical, optical, magnetic, and catalytic properties. This dissertation investigates the impact of 1D nanoparticle catalysts on two distinct and well-known chemical reactions. In the first part of the study, we explore the catalytic activity and selectivity of silver catalysts in the ethylene epoxidation reaction, which are intrinsically linked to their faceting. Silver nanowire catalysts representing Ag(100) and …

Design And Development Of A Direct Medium Voltage Solar Pv Resonant Inverter, Parthkumar Sureshkumar Bhuvela

Theses and Dissertations

In a grid-tied photovoltaic (PV) system connected to a medium voltage (MV) grid, an inverter is generally employed with a line frequency transformer (LFT) to connect to the grid. These LFTs are large in size and weight, exhibit high cost and losses. In recent studies, the LFTs replaced by are by (high frequency transformer) HFT embedded in DC-DC converters. These DC-DC converters are used to boost voltage levels and DC-AC inverters are employed for MV inversion. This leads to high frequency switching at MV which increases losses in inversion stage. In this study, a novel MV grid-connected solar PV inverter …