Digital Commons Network^™

Methodology For Parameter Determination For Simulation Software, Aaron Flood

Doctoral Dissertations

"This research aims to present a methodology for optimizing input datasets to increase the accuracy of mathematical models and accelerate their application to engineering problems. To accomplish this goal, this work focused on the application of mathematical models to metal additive manufacturing (AM), specifically the thermal history of laser directed energy deposition (DED) of aluminum alloys. The initial steps of this body of work were to develop a mathematical model that is capable of simulating the metal AM process and applying it to the laser DED of aluminum. It was validated using the well characterized material Ti-64 and shown to …

Secure And Privacy-Preserving Federated Learning With Rapid Convergence In Leo Satellite Networks, Mohamed Elmahallawy

Doctoral Dissertations

"The advancement of satellite technology has enabled the launch of small satellites equipped with high-resolution cameras into low Earth orbit (LEO), enabling the collection of extensive Earth data for training AI models. However, the conventional approach of downloading satellite-related data to a ground station (GS) for training a centralized machine learning (ML) model faces significant challenges. Firstly, the transmission of raw data raises security and privacy concerns, especially in military applications. Secondly, the download bandwidth is limited, which puts a stringent limit on image transmissions to the GS. Lastly, LEO satellites have sporadic visibility with the GS, and orbit the …

Modeling And Control For Precision Robotic Machining, Patrick Bazzoli

Doctoral Dissertations

"Robots are used in a wide variety of manufacturing applications, but machining applications in which robots can excel are limited by their lower accuracy and stiffness relative to traditional CNC machines. This work is composed of two parts: one to evaluate a robot’s accuracy and one to compensate for the vibrations of the robot due to its lower stiffness.

In order to evaluate whether a robot has the necessary accuracy to perform a given machining task, Paper 1 discusses a novel Model Invalidation method. This methodology provides a statistical framework as well as a measurement strategy for determining if a …

Dynamics And Inverse Problems For Nonlinear Schrödinger Equations, Christopher Hogan

Doctoral Dissertations

"The cubic nonlinear Schrödinger equation (NLS) is a model of interest in the study of physical problems including nonlinear optics and Bose-Einstein condensates. Of particular interest is the study of cubic NLS with inhomogeneities such as localizations of the nonlinearity or terms introducing potential barriers. We first address some preliminaries and techniques useful in the study of the cubic NLS and its variations. We then consider the cubic NLS with a localized nonlinearity in dimensions d ≥ 2. We show that solutions with data given by small-amplitude wave packets accrue a nonlinear phase that determines the X-ray transform of the …

Mission-Driven Inverse-Design Of Conventional And Unconventional Airplane Configurations Using Machine Learning, Rohan Srinivas Sharma

Doctoral Dissertations

"A key challenge in airplane design has been the long-desired ability to quickly create an airplane design with specific performance properties. To tackle this problem, researchers have traditionally leveraged design space exploration methodologies to iteratively explore a design space via surrogate models. On the other hand, inverse design is a process wherein performance objectives are fixed while a suitable design for satisfying these requirements is calculated. In recent years, artificial neural networks (ANNs) have been explored as viable surrogate models because traditional surrogate models struggle with the large number of output to input mapping needed for inverse design problems. In …

Kinetic Modeling And Simulations Of Plasma-Surface-Dust Interactions For Lunar Exploration, David Clifford Lund

Doctoral Dissertations

"Due to the recent relevance of NASA’s focus on lunar missions, a better understanding of the lunar plasma-surface-dust environment is vital for their success. The lunar surface, devoid of an atmosphere and a global magnetic field, is directly exposed to solar radiation and solar wind plasma. This exposure leads to the electrical charging of the lunar surface due to the bombardment of solar wind plasma and the emission/collection of photoelectrons. Therefore, this research developed accurate and efficient computational models of plasma-surface-dust interactions and extend a legacy simulation code, namely the Immersed-Finite-Element Particle-in-Cell (IFE-PIC), to a parallel version: Parallel Immersed-Finite-Element Particle-in-Cell …

Accurate And Time Efficient Signal Integrity And Power Integrity Modeling Of High-Speed Digital Systems, Chaofeng Li

Doctoral Dissertations

"Signal integrity (SI) and power integrity (PI) play an important role in the modern high-speed digital system design, which are closely related to the printed circuit board (PCB) dielectric material property, the PCB interconnect performance, and the power delivery network (PDN) on PCB. Generally, the full-wave simulation is used to accurately analyze and evaluate the designed PCB. But full-wave simulation is not a good option for the complex PCB structure with high aspect ratio, for example, PCB vias, and PDN, which will require significant computing time and storage resources. Equivalent circuit models have been developed to efficiently predict the electrical …

Optimization Of Fire Emergency Preparedness In Underground Mining Environments: An Agent-Based Evacuation Approach, Oluwafemi Babatunde Salami

Doctoral Dissertations

"Underground mining environments present a complex interplay of thermal and non-thermal hazards, with fires constituting a significant risk due to the release of heat smoke from incomplete combustion. The propagation of these hazards through the ventilation networks underscores the critical need for understanding fire scenarios and their interaction with the underground environment. Existing knowledge regarding past mine fire disasters, and quantification of associated hazards and risks are insufficient for optimizing emergency evacuation strategies in the event of an underground fire emergency.

This research endeavors to bridge this gap by developing advanced quantitative risk assessment and evacuation models tailored specifically for …

Investigating The Potential Of Blended Feedstocks For Biofuel Production Via Pyrolysis Process: Experimental And Aspen Simulation Approach, Hasan Jawad Hammood Al-Abedi

Doctoral Dissertations

"The development of renewable energy sources has become increasingly urgent considering the climate crisis and the need to reduce greenhouse gas emissions. Pyrolysis, which is decomposition of an organic feedstock without oxygen, is a thermo-chemical process that has garnered significant attention as a promising technology for sustainable energy production, capable of converting biomass and waste materials into biofuels.

The primary objective of this study is to investigate the pyrolysis and co-pyrolysis behaviors of corn stover (CS), refuse-derived fuel (RDF), and oil shale (OS) in equal mass ratios. Utilizing a thermogravimetric analyzer and differential scanning calorimetry (DSC), the co-pyrolysis process is …

Improving Syngas Quality In A Downdraft Biomass Gasifier With Blended Feedstocks, Rania Almusafir

Doctoral Dissertations

"Biomass gasification is the greatest potential renewable energy source and will play an important role in the energy mix of the future. To achieve a high quality of produced synthesis gas (syngas) in the gasification system, the syngas cleaning and cooling processes pose challenges. The main objectives of the present work are advancing the knowledge of the gasification process and producing syngas in the studied pilot-scale downdraft biomass gasifier.

A Thermogravimetric analysis (TGA) has been developed and utilized to experimentally investigate the impact of biomass feedstock diversity on the performance of the gasification process of hardwood (HW), softwood (SW) pellets, …

In-Depth Characterization Of The Selective Oxidation Products Of Hafnium Carbide, Jonathan Allen Scott

Doctoral Dissertations

"Materials capable of withstanding oxidative environments at temperatures >2000°C are necessary for hypersonic applications. Hafnium carbide (HfC) shows a combination of properties that lends itself toward these applications; however, its oxidation behavior is poorly understood. At 1300°C, HfC was found to oxidize via the following mechanism: 1) Initial oxidation of both C and Hf present in the system, 2) Formation of an interconnected pore network, whose size is related to the volume of gases being generated during the oxidation process, 3) Growth of the oxide scale to become sufficiently protective, 4) Formation of an initially amorphous “HfO₂C” at …

Critical Behavior And Dynamics Of The Superfluid-Mott Glass Transition, Jack Russell Crewse

Doctoral Dissertations

This work studies the effects of disorder on the thermodynamic critical behavior and dynamical properties of the superfluid-Mott glass quantum phase transition. After a brief introduction covering relevant fundamentals, we present the dissertation in the form of four separate but related publications. In the first two publications, we calculate the thermodynamic critical exponents of the superfluid-Mott glass quantum phase transition in both two and three spatial dimensions. The undiluted transition exhibits critical exponents that violate the Harris criterion, and thus the critical behavior is expected to change upon introducing disorder. We confirm this behavior via Monte Carlo simulation of a …

Adversarial Transferability And Generalization In Robust Deep Learning, Tao Wu

Doctoral Dissertations

Despite its remarkable achievements across a multitude of benchmark tasks, deep learning (DL) models exhibit significant fragility to adversarial examples, i.e., subtle modifications applied to inputs during testing yet effective in misleading DL models. These meticulously crafted perturbations possess the remarkable property of transferability: an adversarial example that effectively fools one model often retains its effectiveness against another model, even if the two models were trained independently. This research delves into the characteristics influencing the transferability of adversarial examples from three distinct and complementary perspectives: data, model, and optimization. Firstly, from the data perspective, we propose a new method of …

Highly Dipole-Parallel Aligned Nonlinear Optical Organic Molecular Crystalline Materials: Rational Design, Experimental And Theoretical Studies Of Supramolecular Structures And Non-Covalent Interactions, Harmeet Singh Bhoday

Doctoral Dissertations

Highly dipole-parallel aligned donor-acceptor substituted organic molecules are attractive for a wide array of applications, including nonlinear optics. However, only a limited number of crystals are known to adopt polar non-centrosymmetric space groups. The concepts guiding the fabrication of these polar materials have been described. The study focused on unsymmetrical donor-acceptor substituted azines and butadiene's. An improved design over (MeO, Y)-azines led to the realization of three crystals perfectly aligned in dipole parallel orientation for (PhO, Y)-azines with Y = Cl, Br, I, and one nearly perfectly aligned crystal for Y = F (Paper I). The unique bonding properties associated …

Crystal Structure Prediction Of Metal Chalcogenides, Qi Zhang

Doctoral Dissertations

A novel crystal structure prediction (CSP) method has been developed to predict energetically favorable (stable) structures based on targeted chemical compositions. It leverages the structural characteristics of recurring motifs featured in many crystals and symmetry restrictions from space groups to effectively lower the degrees of freedom of a system when conducting CSP simulations. The proposed method is applied to predicting low-energy structures of two metal chalcogenide systems: Li₃PS₄ and Na₆Ge₂Se₆. Both systems feature rigid bodies in their structures as building blocks, making them particularly suited to the proposed method. The validity …

Variability In Semidiurnal Surface And Internal Tides In Global Ocean Model Simulations, Harpreet Kaur

Dissertations

This dissertation focuses on semidiurnal (D2) surface and internal tides. Chapter 2 investigates the transition of M₂ barotropic Kelvin waves into Hybrid Kelvin-Edge (HKE) waves and the associated generation of internal tides at widening shelves using theory and a realistic global baroclinic Hybrid Coordinate Ocean Model (HYCOM) simulation. To understand the effect of complex, realistic bathymetry on the HKE wave transition, we perform quasi-realistic barotropic HYCOM simulations of the Celtic Sea/Bay of Biscay shelf areas. We conclude that the HKE wave transition is most likely masked by the effects of complex bathymetry and offshelf baroclinic fluxes cannot be exclusively …

Simulation Of Lc Circuits In Cylindrical Photoemission Driven Cavities Using Coupled Monte Carlo And Particle-In-Cell Codes, Ravi Sanjay Shastri

Masters Theses

"This work presents a computational experiment simulating irradiation of gold in a cylindrical cavity. The full 3-D simulation with a B-Dot diagnostic is modeled, and a subset of the results are compared to modeling the system as a coupled anode/cathode (AK) gap and transmission line. The cavity is filled with N2 and Ne gasses at pressures ranging from vacuum to 1000 mTorr. Space-charge limited emission physics, electric discharge physics, LC circuit physics, and Monte-Carlo methods are explored.

The computation process happens in two steps. First, the electron emission material is irradiated with an input x-ray photon spectrum to produce a …

The Deep Bsde Method, Daniel Kovach

Masters Theses

"The curse of dimensionality is the non-linear growth in computing time as the dimension of a problem increases. Using the Deep Backwards Stochastic Differential Equation (Deep BSDE) method developed in [HJE18], I approximate the solution at an initial time to a one-dimensional diffusion equation. Although we only approximate a one-dimensional equation, this method extends well to higher dimensions because it overcomes the curse of dimensionality by evaluating the given partial differential equation along "random characteristics''. In addition to the implementation, I also present most of the mathematical theory needed to understand this method"-- Abstract, p. iii

Hysplit In Simulating The Atmospheric Dispersion Of Hazardous Aerosols: A Case Study In St. Louis, Missouri, Ahmet Tolga Odabasi

Masters Theses

"Atmospheric dispersion and transmission play an important role in the behavior and effects of air pollution. Human health can be adversely affected by air pollution in a variety of ways, both immediately and over time. The Hybrid Single Particle Lagrangian Integrated Trajectory Model (HYSPLIT) modeling program, a computer model and software package, tracks the transport trajectories and distributions of air pollution and various pollutants, including radioactive pollutants, in the atmosphere. It also facilitates research on pollution sources. This study simulated the transport of hazardous aerosols in St. Louis region for the years 2020, 2021, and 2022 using the HYSPLIT modeling …

Enabling Smart Healthcare Applications Through Visible Light Communication Networks, Jack Manhardt

Masters Theses

"Future smart healthcare operations are envisioned to require the support of high-performance wireless networks. Researchers are presented with a problem, however, as the hospital environment brings unique challenges to the application of traditional radio-frequency wireless communication networks due to health concerns and electromagnetic compatibility standards. To meet these challenges and support the advancement of high-quality healthcare, we propose the use of an alternative wireless technology in visible light communication (VLC). Contributing to the growing interest in VLC amongst researchers, we construct both a VLC network simulation testbed as well as real-world testbed to serve as a platform for the development …

Open-Ended Hollow Coaxial Cable Resonance Sensing Via Permittivity Fluctuations For Applications To Exhaled Breath Health Monitoring, Peter Henry Holtmann

Masters Theses

"We report a pre-diagnostics breath analyzer based on the open-ended hollow coaxial cable resonator (OE-HCCR) to achieve real-time differentiation of healthy and compromised lung function through electromagnetic analysis of exhaled breath matter. A two-phase amplification scheme of electromagnetic signatures metered via the S11 phase curve offers high sensitivity to permittivity fluctuations in exposed airflow. The mathematical model of the breath analyzer is explained, followed by experimental validation of numerical findings from previous work. The collection of breath transient signals is performed through monitoring the reflected power magnitude and phase of the scattering parameter (S11) at the resonance frequency. Material fluctuations …

Modeling Redistribution Of Nanozeolites In Holographic Recording, Dana Mackey, Jack Lyons, Izabela Naydenova

Articles

Zeolite doped photopolymers have been studied experimentally due to their potential application in the development of optical sensors. It has been shown that dopant redistribution can be achieved by holographic recording and has a direct influence on the sensitivity of the recorded grating. To achieve better theoretical understanding of these processes, this paper proposes an extended photopolymerization-diffusion mathematical model for describing the dynamics of nanozeolite redistribution during recording in an acrylamide-based photopolymer. Using numerical simulations of this model, we investigate how recording conditions, dopant transport parameters, and initial load affect the refractive index modulation of the resulting photonic structure.

Radiofrequency Interference Detection Using Lstmand Statistical Analysis Discriminator, Luke Smith

Masters Theses

"Wireless devices are becoming increasingly pervasive across all aspects of society. Examples of such devices include radios, routers, mobile phones, tablets, and more. As the number of radio frequency (RF) devices continues to rise, so does the amount of interference and noise increase. This is why an efficient approach to interference detection is explored. Most research within this area has been done strictly within the frequency domain as viewing a signal within this domain provides many insights into what makes the signal. This has, however, led to the time domain being underutilized for this area of research.

To explore the …

Discrete Event Simulation (Des) In Swapping/Charging Of Battery Electric Vehicles In Underground Mining, Albert Einstein Amponsem

Masters Theses

"With climate change concerns escalating, international agreements such as the Kyoto Protocol, the US Presidential Policy, and the Paris Agreement aim to reduce greenhouse gas (GHG) emissions, targeting significant reductions by 2050. The mining sector, a notable contributor to GHG emissions primarily through diesel-powered material haulage, emits approximately 68 million tons of CO₂ annually. Transitioning to Battery Electric Trucks (BETs) presents a viable mitigation strategy by replacing diesel trucks with electric alternatives, thus eliminating CO₂ emissions.

However, the effectiveness of BETs hinges on optimized battery swapping and charging procedures. This study employs Discrete Event Simulation (DES), a computational …

Comparative Study Of Crypto Volatility And Price Forecasting Using A Mixture Of Time Series And Machine Learning Models, Abhishek Kafle

Masters Theses

"Forecasting financial product volatility and price is crucial for informed decision-making in investment and risk management. The models considered include GARCH, LSTM, GRU, BiLSTM, and hybrid models that incorporate various combinations of these models. We present a comparative analysis of forecasting volatility and price using the aforementioned models.

We also introduce a user-friendly dashboard for model training and evaluation, enabling users to upload datasets and customize model parameters. The dashboard allows users to select the type of model, specify the dataset range for training, determine the number of epochs, adjust the number of layers for deep …

Learn From The Past: Using Peer Data To Improve Course Recommendations In Personalized Education, Colton Walker

Masters Theses

"This work describes a recommendation approach designed to enhance student success by identifying semester schedules and graduation paths. The primary objective is to provide personalized graduation path recommendations rooted in individual student performance and draw insights from the academic journeys of similar students who successfully graduated. The original research contribution of this work lies in the development of a graduation path recommender system that leverages a combination of Markov Decision Process, Q-Learning, and collaborative filtering techniques to pinpoint graduation paths with a higher likelihood of leading students to success based on their academic progress thus far. The effectiveness of the …

Evaluating Electromagnetic Interference On Gnss Receivers, Giorgi Tsintsadze

Masters Theses

"Due to high power and efficiency requirements of modern electrical drive system, inverters are utilizing fast-edge pulses as a drive signal. The high frequency pulses contain higher order harmonics can radiate electromagnetic interference above accepted levels. Modelling and understanding the mechanism that causes the radiation is studied, modelled and presented as gray-box model which contains circuit level modelling of coupling between electrical machine phase windings and low power sensor harness. The thesis consists of two main papers. In the first paper, radiated emissions from an electrical drive system is charac- terized thru gray-box modelling where coupling between electrical machine phase …

Iterative Power Flow Control Architecture For Dc-Ac-Ac Triple Active Bridge Converters: Design, Simulation, And Hardware Testing, Jonathan Henri Saelens

Masters Theses

Driven by widespread electrification and escalating energy demands, efficient and cost-effective converter systems are necessary to maintain and improve our nation's electrical grid. Facilitating this necessity are power electronic converters in applications such as smart grids, renewable energy integration, and electric vehicles. Guided by the demand for improved converter topologies and conversion efficiency, much research has been conducted on varying designs, development, and control implementations. One such topology gaining significant research attention is the triple active bridge (TAB) converter. The TAB is a three-port power converter enabling both bidirectional power flow on each port and galvanic isolation for safety and …

Synthesis And Characterisation Of Molecularly Imprinted Polymers On Functionalised Silica Gel Designed For The Selective Extraction And Detection Of Nitroaromatic Compounds Coupled With Colorimetric Methods, Raymond Tang

Masters

HPLC and LC-MS are analytical instruments used to detect the trace explosives, however, the instrumental methods are expensive and require specially trained operators to prepare the samples and interpret the results, and these methods are not suitable for use in conflict zones. The overall aim is to deliver a method for the selective, sensitive and rapid detection of trace explosives in the field.

Disaggregating Longer-Term Trends From Seasonal Variations In Measured Pv System Performance, Chibuisi Chinasaokwu Okorieimoh, Brian Norton, Michael Conlon

Articles

Photovoltaic (PV) systems are widely adopted for renewable energy generation, but their performance is influenced by complex interactions between longer-term trends and seasonal variations. This study aims to remove these factors and provide valuable insights for optimising PV system operation. We employ comprehensive datasets of measured PV system performance over five years, focusing on identifying the distinct contributions of longer-term trends and seasonal effects. To achieve this, we develop a novel analytical framework that combines time series and statistical analytical techniques. By applying this framework to the extensive performance data, we successfully break down the overall PV system output into …