Physical Sciences and Mathematics Commons^™

Nuclear Energy, Evan Detina

Op-Eds from ENSC230 Energy and the Environment: Economics and Policies

The use of nuclear power as a primary energy source is a controversial discussion. However, if reversing or stopping the effects of climate change is our main goal, then this is a top contender. Fossil fuels account for 34 billion tons of emissions annually according to Ritchie, Hannah, et al. (2020). Instead, we can create energy through nuclear fission. I believe nuclear energy should become a much larger player in the energy game.

The first practical use of nuclear power became apparent on December 2, 1942 when a physicist, Enrico Fermi, developed a self-sustaining nuclear fission reaction at the University …

Puerto Rico Left In The Dark, Again, Eulices Garcia

Op-Eds from ENSC230 Energy and the Environment: Economics and Policies

Puerto Rico, the United States third largest island, often gets overlooked when hurricane season comes and goes. Where most of the attention goes to the Florida peninsula or East coast, Puerto Rico is still one of America’s closest territories. As part of America’s extended family, Puerto Rico should not be overlooked when natural disasters occur. When these disasters happen, they can have a tremendous impact on the island itself and the people in it. One major concern that has not been truly fixed yet is the energy crisis in Puerto Rico. Whenever storms hit, there is always a possibility of …

Big Blue Wind Project: Why Solar May Be A Better Solution For Nebraska's Energy Future Than Wind, Page Nippert

Op-Eds from ENSC230 Energy and the Environment: Economics and Policies

With nonrenewable resources such as coal and oil causing greenhouse gas emissions, a shift to renewable resources is needed not only to reduce CO₂ emissions, but also to allow energy independence. The switch to renewable resources is vital, and in Nebraska, these resources are being introduced commonly as solar and wind farms depending on the area.

NextEra Energy is proposing The Big Blue Wind project in Jefferson County. I’m opposing this project for reasons similar to why it’s being proposed – for the environment and the community.

The project aims to benefit the community economically by creating jobs, county …

Are Electric Cars A Solution In Rwanda?, Elysee Ndayishimiye

Op-Eds from ENSC230 Energy and the Environment: Economics and Policies

Numerous studies have been conducted that demonstrate how environmentally friendly electric vehicles are. They produce fewer greenhouse gases, which makes them an effective way to reduce both air pollution and greenhouse emissions. In order to combat rising air pollution and support a green city initiative, Rwanda considered introducing more electric vehicles. The Global Electric Mobility Program, run by the United Nations Environment Program (UNEP), aims to assist low- and middle-income nations in switching from conventional (gas) to electric vehicles. Rwanda has joined this program. Due to the high cost of switching to electric vehicles in poor nations like Rwanda and …

New Natural Gas Pipeline Benefits Europe And Africa, Victor Moreno Lozano

Op-Eds from ENSC230 Energy and the Environment: Economics and Policies

European countries have agreed to start filling up their natural gas gap, with the new natural gas pipeline from Africa. Nigeria and Morocco agreed to develop this pipeline in 2016, but after the beginning of the Ukraine-Russia war, things have speeded up.

After the economical punishments Europe imposed on Russia, Russia decided to increase the price of the natural gas exported to Europe and decrease the amount of gas. Most European countries have a big dependency on Russia's natural gas, countries like Germany import 50% of their natural gas from Russia.

Since winter is coming up, European countries are dealing …

Serendipity Shape Function For Hybrid Fluid/Kinetic-Pic Simulations, Trevor V. Taylor

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

The Sun in our solar system and stars are capable of generating enormous amounts of energy. The process by which these gaseous, celestial bodies are able to produce such large amounts of energy is called thermonuclear fusion. Fusion happens when particles collide with one another at energy levels high enough to overcome the Coulomb force and then release vast amounts of energy. Plasma, the fourth state of matter, is the natural state of stars. Plasma is an ionized gas that consists of negatively and positively charged particles. Stars, which have immense mass, can confine the plasma through their gravity to …

Time Series Classification With Multistage Modeling Using Deep Learning, James Arthur

Open Access Theses & Dissertations

Time series classification (TSC) can be efficiently implemented with several techniques. Many techniques are based on analyzing 1-D signals in the time series data. In this work, we make an intrinsic analytical implementation of a new time series classification that involves a two-stage process. Firstly, by using Recurrence Plots (RP), we transform the time series into 2D images. The second stage consists in taking advantage of deep learn- ing models to perform our classification. The image illustration of time series introduces different feature types that are not available for all 1D signals, and therefore our classifi- cation problem is treated …

Region Detection & Segmentation Of Nissl-Stained Rat Brain Tissue, Alexandro Arnal

Open Access Theses & Dissertations

People who analyze images of biological tissue rely on the segmentation of structures as a preliminary step. In particular, laboratories studying the rat brain delineate brain regions to position scientific findings on a brain atlas to propose hypotheses about the rat brain and, ultimately, the human brain. Our work intersects with the preliminary step of delineating regions in images of brain tissue via computational methods.

We investigate pixel-wise classification or segmentation of brain regions using ten histological images of brain tissue sections stained for Nissl substance. We present a deep learning approach that uses the fully convolutional neural network, U-Net, …

Glacier Segmentation From Remote Sensing Imagery Using Deep Learning, Bibek Aryal

Open Access Theses & Dissertations

Large-scale study of glaciers improves our understanding of global glacier change and is imperative for monitoring the ecological environment, preventing disasters, and studying the effects of global climate change. In recent years, remote sensing imagery has been preferred over riskier and resource-intensive field visits for tracking landscape level changes like glaciers. However, periodic manual labeling of glaciers over a large area is not feasible due to the considerable amount of time it requires while automatic segmentation of glaciers has its own set of challenges. Our work aims to study the challenges associated with segmentation of glaciers from remote sensing imagery …

Online/Incremental Learning To Mitigate Concept Drift In Network Traffic Classification, Alberto R. De La Rosa

Open Access Theses & Dissertations

Communication networks play a large role in our everyday lives. COVID19 pandemic in 2020 highlighted their importance as most jobs had to be moved to remote work environments. It is possible that the spread of the virus, the death toll, and the economic consequences would have been much worse without communication networks. To remove sole dependence on one equipment vendor, networks are heterogeneous by design. Due to this, as well as their increasing size, network management has become overwhelming for network managers. For this reason, automating network management will have a significant positive impact. Machine learning and software defined networking …

Nano-Engineered Soft Magnets: Potential Application In Water Treatment, Hyperthermia And Molecular (Organic) Magnets, Yohannes Weldemariam Getahun

Open Access Theses & Dissertations

Scrutinizing the remarkable and tunable properties of magnetic materials at a nanoscale size "There's Plenty of Room at the Bottom..." Richard Feynman, this study attempts to find sustainable solutions to some of the deteriorating environmental, health, and energy problems the world is encountering. Due to their simple preparation, surface adaptability, and tunable magnetic and optical properties, magnetic nanoparticles have been extensively investigated in water treatment, cancer therapy, data storage, and more. However, relying on non-reusable and chemical-based treatment agents in water, complex and costly cancer treatment procedures and molecular magnets that operate far below room temperature limited those attempts from …

Evaluation Of Effect Of Preprocessing Algorithms On Resting State Fmri Data, Hortencia Josefina Hernandez

Open Access Theses & Dissertations

Graph theory modeling is a common modeling approach in neurobiology research studies. These models are useful since they describe patterns of connection for regions of interest in the brain using resting state fMRI images. The standard rule of thumb is to threshold the observed activation levels prior to model building. It is reasonable to assume that the use of this threshold affects the statistical distribution of commonly reported centrality metrics from the graph theory model, such as degree, betweenness, and closeness. In this study we examine the differential effect of using the standard approaches versus alternative direct thresholds and incorporation …

Application Of Flo-Sic To F-Electron Systems: Sixth Row Elements And Ligated Molecules, Alexander Irun Johnson

Open Access Theses & Dissertations

Density functional theory - the most widely used theoretical method to study atoms,molecules, and solids - suffers from the well-known self-interaction error. A solution to the problem was suggested by Perdew and Zunger [1], who showed the self-interaction error can be removed with self-interaction correction. In 2014, Pederson showed a unitary transformation can be performed on the Kohn-Sham orbitals to generate Fermi-Löwdin orbitals which improve atomization energies, and avoid the computational costs of solving the localization equations.[2] This method is known as the Fermi-Löwdin Orbital Self-Interaction Correction (FLO-SIC). Until now, the FLO-SIC methodology has been used for atoms not containing …

Black And Brown Carbon Optical Characterization In The El Paso - Ciudad Juarez Airshed, Pamela I. Lara

Open Access Theses & Dissertations

Black (EBC) and Brown (BrC) Carbon are ubiquitous constituents of atmospheric particulate matter that affect peopleâ??s health, disrupt ecosystems, and modulate local and global climate. Tracking the local deposition and sources of these aerosol particles is essential to better understanding their multidimensional environmental impact. The main goal of the current study is to measure the absorption coefficient (Babs) of particles within the Planetary Boundary Layer (PBL) of the El Paso (US)–Ciudad Juárez (Mexico) airshed and assess the contribution of black and brown carbon particles to the total optical absorption. Measurements were taken during winter (January, 2022), spring (May, 2022), and …

The Qualification Of Sealability And Creep Relaxation Of Additively Manufactured Zytel Gaskets For Pem Fuel Cells, Robert Lazarin

Open Access Theses & Dissertations

The purpose of this thesis is to study the feasibility of low-cost additive manufacturing of gaskets for proton exchange membrane fuel cells exposed to extreme temperature conditions ranging from -55°C to 100°C. With the growing popularity and decreasing costs of additive manufacturing technologies, specifically Material Extrusion (ME), research is being conducted to determine the feasibility of ME components. Thermally cycled PEMFCs may exhibit accelerated gasket deterioration, therefore, the mechanical stability of material extruded gaskets following a harsh thermal cycle must be assessed. The feasibility of the material extruded gaskets will be proven by manufacturing optimization and mechanical testing. The target …

Synthetic Data Generation For Intelligent Inspection Of Structural Environments, Noshin Habib

Open Access Theses & Dissertations

Automated detection of cracks and corrosion in pavements and industrial settings is essential to a cost-effective approach to maintenance. Deep learning has paved the path for vast levels of improvement in the area. Such models require a plethora of data with accurate ground truth and enough variation for the model to generalize to the data, which is notwidely available. There has been recent progress in computer graphics being used for the creation of synthetic data to address the issue of deficient data availability, but it is limited to specific objects, such as cars and human beings. Textures and deformities within …

Modulation Of Non-Diffracting Hermite Gaussian Beams And Nonlinear Optical Microscopy For Nanoscale Sulfur Imaging, Gilberto Navarro

Open Access Theses & Dissertations

Hermite Gaussian beams are the solutions of the scalar paraxial wave equation in Cartesian coordinates. A method was developed to modulate the intensity profile of non-diffracting Hermite Gaussian (HG) beams. The original HG beamâ??s intensity profile consists of high intense corner lobes and low intense central lobes which is not ideal for structured illumination in light-field microscopy. The modulated HG beams were generated by multiplying the original HGâ??s beam envelope by a super-Gaussian envelope to modify the intensity profile to attain equal intensity lobes. The propagation of the original HG beam and modulated HG beam were compared to determine that …

A Case Study In Design, Construction, And Operation Of A Meromictic Solar Pond In Texas, Usa, Bianca Paola Meneses Brassea

Open Access Theses & Dissertations

Over the last four decades, meromictic solar ponds have been the subject of limnological studies and engineering research. A case of practical interest is the salinity gradient solar pond (SGSP). SGSP science and technologies have been systemically advanced in El Paso, Texas. This dissertation aims to share lessons learned in designing, constructing, and operating the El Paso Solar Pond, a NaCl-based solar pond that achieved high-temperature performance over two decades, commencing in 1984. Many of the practical lessons learned have not been published and are thus not readily available in archival journals, and this contribution provides a remedy. The value …

Analyzing And Quantifying The Impact Of Software Diversification On Return-Oriented Programming (Rop) Based Exploits, David Reyes

Open Access Theses & Dissertations

With the implementation of modern software mitigation techniques such: as Address Space Layout Randomization (ASLR), stack canaries, and the No-Execute bit (N.X.), attackers can no longer achieve arbitrary code execution simply by injecting shellcode into a vulnerable buffer and redirecting execution to this vulnerable buffer. Instead, attackers have pivoted to Return Oriented Programming (ROP) to achieve the same arbitrary code execution. Using this attack method, attackers string together ROP gadgets, assembly code snippets found in the target binary, to form what are known as ROP Chains. Using these ROP Chains, attackers can achieve the same malicious behavior as previous code …

Fabrication And Characterization Of Iron-Based Catalysts For The Dehydrogenation Of Fossil Fuels, Victoria Isabel Reyes

Open Access Theses & Dissertations

For a prosperous and sustainable future, hydrogen is an encouraging solution due to its simple transition for industrial decarbonization and synergy for economic development. Paradoxically, current hydrogen production pathways release substantial amount of greenhouse gases into the atmosphere contributing to climate change. To keep up with increasing demand, hydrogen could be produced through microwave-assisted thermocatalytic dehydrogenation of fossil fuels without emitting carbon dioxide. This requires specified catalysts to meet the requirements of hydrogen yield and selectivity. The objective of the present research is to fabricate, characterize, and compare iron-based alumina (FeAl_x O_y) catalysts produced via solution combustion synthesis and iron-based …

Magnetic Structures Of Sawtooth Olivines Mn2six 4 (X = S, Se) Determined Through Neutron Powder Diffraction, Melaku Sisay Tafere

Open Access Theses & Dissertations

In olivine chalcogenide Mn2SiX 4 (X = S, Se) compounds, the Mn lattice produces a sawtooth, which is of critical significance in magnetism due to the potential for manifesting at bands in the magnon spectrum, a crucial component in magnonics. The compounds Mn2SiS4 and Mn2SiSe4 in Mn2SiX 4 family undergo antiferromagnetic phase transitions at T â?? 85 K and â?? 66 K, respectively, as determined from the specific heat, Cp(T). The average and local crystal structuresare determined using synchrotron X-ray, neutron diffraction, and X-ray total scattering data followed by Rietveld and pair distribution function (PDF) analysis. It is found from …

Identifying Particulate Matter Spatial Variation In The El Paso Del Norte Region Using Land-Use Regression Modeling And Data Obtained From A Network Of Low-Cost Sensors, Leonardo Demetrio Vazquez-Raygoza

Open Access Theses & Dissertations

The emergence and rise in popularity of low-cost sensors for atmospheric observation aresetting a new precedent in identifying emission hotspots and providing high-resolution spatial and temporal data. Furthermore, low-cost sensors are becoming popular among institutions and the public, allowing community scientists to become more involved in air quality monitoring. However, concerns about the accuracy and precision of low-cost sensors have been questioned. Most recent research has focused on the utility of real-time monitoring and calibration requirements for these sensors. A low-cost monitoring project has deployed sensors in the El Paso del Norte region in low and high annual average daily …

Radio Frequency Fingerprinting And Its Application To Scada Environments, Evan White

Open Access Theses & Dissertations

With the introduction of IoT into ICS and smartgrid environments there has been a mod-ernization of communication protocols through the internet. This has led to the use of features such as TCP/IP but with it comes modernized attack vectors against these sys- tems. These attacks can be Man In the Middle (MITM), rogue device communication and device cloning. To prevent these attacks, this thesis deploys Radio Frequency Fingerprint- ing (RFF) techniques to verify the uniqueness and legitimacy of known devices. It is crucial to employ security measures within ICS that do not add to the network complexity as this effects …

Spectroscopic Study Of Bi5ti3feo15 Aurivillius Compound For Multifunctional Applications, Mariana Castellanos

Open Access Theses & Dissertations

No abstract provided.

Transportation Asset Management For The Electric Road System, Kamalen Maria Santos Diaz

Open Access Theses & Dissertations

Electric road systems (ERS) have been presented as a new solution towards a sustainable transportation future, fueling the widespread adoption of electric vehicles by eliminating range anxiety, reducing battery size, and being regional friendly. These systems consist of four components: electric power supply, roads, vehicles, and operations. Much of the early research conducted on ERS has been on how to initially construct these systems by focusing on the first three components, however, there is limited knowledge on how ERS will impact traditional road operations after the systems are in place. Transportation Asset Management (TAM), a major focus within the transportation …

Molecularly Inspired Organic Macrocycles Catalyzed Water Splitting Reaction For Sustainable Fuel Production, Yulu Ge

Open Access Theses & Dissertations

Hydrogen fuel generation through electrochemical water splitting is considered as an advanced energy conversion technology driven by sustainable energy. High activity and cost effective electrocatalysts that are able to drive down the energy cost needed for both two half reactions, namely, hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) are required to fulfill the energy transfer process. Exploring new electrocatalysts with enhanced OER and HER activity and stability is crucial for renewable energy applications. Porphyrin and macrocycle derivatives are versatile and can electrochemically catalyze water splitting efficiently. In our work, we use porphyrin as platform for both HER and …

Generation Of Phase Transitions Boundaries Via Convolutional Neural Networks, Christopher Alexis Ibarra

Open Access Theses & Dissertations

Accurate mapping of phase transitions boundaries is crucial in accurately modeling the equation of state of materials. The phase transitions can be structural (solid-solid) driven by temperature or pressure or a phase change like melting which defines the solid-liquid melt line. There exist many computational methods for evaluating the phase diagram at a particular point in temperature (T) and pressure (P). Most of these methods involve evaluation of a single (P,T) point at a time. The present work partially automates the search for phase boundaries lines utilizing a machine learning method based on convolutional neural networks and an efficient search …

Elucidation Of Active Site And Mechanism Of Metal Catalysts Supported In Nu-1000, Hafeera Shabbir

All Dissertations

Advances in extraction of shale oil and gas has increased the production of geographically stranded natural gas (primarily consisting of methane (C1) and ethane (C2)) that is burned on site. A potential utilization strategy for shale gas is to convert it into fuel range hydrocarbons by catalytic dehydrogenation followed by oligomerization by direct efficient catalysts. This work focuses on understanding metal cation catalysts supported on metal-organic framework (MOF) NU-1000 that will actively and selectively do this transformation under mild reaction conditions, while remaining stable to deactivation (via metal agglomeration or sintering). I built computational models validated by experimental methods to …

Learning Graphical Models Of Multivariate Functional Data With Applications To Neuroimaging, Jiajing Niu

All Dissertations

This dissertation investigates the functional graphical models that infer the functional connectivity based on neuroimaging data, which is noisy, high dimensional and has limited samples. The dissertation provides two recipes to infer the functional graphical model: 1) a fully Bayesian framework 2) an end-to-end deep model.

We first propose a fully Bayesian regularization scheme to estimate functional graphical models. We consider a direct Bayesian analog of the functional graphical lasso proposed by Qiao et al. (2019).. We then propose a regularization strategy via the graphical horseshoe. We compare both Bayesian approaches to the frequentist functional graphical lasso, and compare the …

Computational And Experimental Investigations Of Alkali Cation Interactions At The Rutile – Water Interface, Isaac Johnston

All Dissertations

Overall, the objective of this dissertation was to investigate the degree of sorption for the alkali cations on rutile to ascertain the impact of different cation properties, such as ion size and charge density, on sorption mechanics as well as probe how the ion may alter the surface – aqueous interface. Initial molecular dynamic simulations and batch experiments showed minimal surface sorption for any alkali cation at relatively low concentrations while simultaneously suggesting the enthalpy of deprotonation shifts slightly in the presence of the alkali cations at different ionic strengths. The cations are likely causing small reorientations of the near-surface …