Digital Commons Network^™

Modeling Of Gas-Solid Flows In Industry With Computational Fluid Dynamics Tools: An Assessment Of Modeling Methodologies And Computational Challenges, Kaylee Smith

Theses and Dissertations

The modeling work and simulation results contained within this thesis come from two different applications that together emphasize multiple of the challenges currently faced by researchers in the field of numerical modeling of gas-solids flows with computational fluid dynamics (CFD) tools, and highlight avenues of potential resolutions to these challenges.

In the first body of work, the MFiX CFD suite, developed by the Department of Energy’s National Energy Technology Laboratory (DOE NETL), was utilized to model and simulate several experimental conditions of a fluidized bed (in 2D), and a hopper (in 3D), where solid-solid collision effects play a dominant role. …

Case Judgments And Juror Perceptions Of The Stereotypical Defendant, Mariah Sorby

Theses and Dissertations

Stereotypes and prejudice have been shown to bias information processing and decision making. There are physical traits that are stereotypically associated with criminals, i.e. tattoos, dark skin-tone, facial untrustworthiness, Afrocentric facial features. These features have been shown to influence verdict decisions and sentencing outcomes. However, there is a paucity of research investigating the additive effects of these features while also considering individual levels of prejudice and egalitarian views. The current research aimed to investigate the effects of several combinations of features on defendant verdict, sentencing, and criminal appearance ratings, rather than assessing the features in isolation, while controlling for prejudice …

First-Principles Studies Of Two-Dimensional Transition Metal Carbides For Spintronics And Energy Applications, Edirisuriya Mudalige Dilanga Siriwardane

Theses and Dissertations

Next-generation spintronic nanoscale devices require two-dimensional (2D) materials with robust ferromagnetism. Among 2D materials, MXenes are favorable for spintronic applications due to their high electron conductivity, mobility, and chemical diversity. Since 2D materials have greater elastic strain limits than their bulk counterparts, their properties can be tuned effectively using strain engineering. In this dissertation, we discuss density functional theory (DFT) based first-principles studies on ferromagnetic MXenes for spintronics applications. In Chapter III, we investigated modifications in the structural, electronic, and magnetic properties produced by strain on 2D Hf2MnC2O2 and Hf2VC2O2 ferromagnetic semiconductors. The calculations in Chapter III reveal that the …

Carbon-Dioxide Pipeline Infrastructure Route Optimization And Network Modeling For Carbon Capture Storage And Utilization, Karthik Balaji

Theses and Dissertations

Carbon capture, utilization, and storage (CCUS) is a technology value-chain which can help reduce CO2 emissions while ensuring sustainable development of the energy and industrial sectors. However, CCUS requires large-scale deployment of infrastructure for capturing feasible amounts of CO2 that can be capital intensive for stakeholders. In addition, CCUS deployment leads to the development of extensive pipeline corridors, which can be inconsistent with the requirements for future CCUS infrastructure expansion. With the implementation and growth of CCUS technology in the states of North Dakota, Montana, Wyoming, Colorado and Utah in mind, this dissertation has two major goals: (a) to identify …

Deepmag+ : Sniffing Mobile Apps In Magnetic Field Through Deep Learning, Rui Ning, Cong Wang, Chunsheng Xin, Jiang Li, Hongyi Wu

Electrical & Computer Engineering Faculty Publications

This paper reports a new side-channel attack to smartphones using the unrestricted magnetic sensor data. We demonstrate that attackers can effectively infer the Apps being used on a smartphone with an accuracy of over 80%, through training a deep Convolutional Neural Networks (CNN). Various signal processing strategies have been studied for feature extractions, including a tempogram based scheme. Moreover, by further exploiting the unrestricted motion sensor to cluster magnetometer data, the sniffing accuracy can increase to as high as 98%. To mitigate such attacks, we propose a noise injection scheme that can effectively reduce the App sniffing accuracy to only …

Advances In Atomic Layer Deposition (Ald) Nanolaminate Synthesis Of Thermoelectric Films In Porous Templates For Improved Seebeck Coefficient, Xin Chen, Helmut Baumgart

Electrical & Computer Engineering Faculty Publications

Thermoelectrics is a green renewable energy technology which can significantly contribute to power generation due to its potential in generating electricity out of waste heat. The main challenge for the development of thermoelectrics is its low conversion efficiency. One key strategy to improve conversion efficiency is reducing the thermal conductivity of thermoelectric materials. In this paper, the state-of-the-art progresses made in improving thermoelectric materials are reviewed and discussed, focusing on phononic engineering via applying porous templates and ALD deposited nanolaminates structure. The effect of nanolaminates structure and porous templates on Seebeck coefficient, electrical conductivity and thermal conductivity, and hence in …

Generation Of Large-Volume High-Pressure Plasma By Spatiotemporal Control Of Space Charge, Shirshak K. Dhali

Electrical & Computer Engineering Faculty Publications

Any attempt to scale pressure and volume of nonthermal plasma usually leads to instabilities due to the formation of localized space charge. The control of the plasma is limited by the discharge geometry, type of excitation, and gas composition. This article explores the possibility of controlling the space charge in a discharge with a spatially and temporally varying electric field. It is shown that a phase-staggered sinusoidal excitation to a set of conformal azimuthal electrodes in a cylindrical geometry leads to a traveling electric field. Simulations show that in space charge dominated transport, the charged species are dispersed both in …

Gold/Qds-Embedded-Ceria Nanoparticles: Optical Fluorescence Enhancement As A Quenching Sensor, Nader Shehata, Effat Samir, Ishac Kandas

Electrical & Computer Engineering Faculty Publications

This work focuses on improving the fluorescence intensity of cerium oxide (ceria) nanoparticles (NPs) through added plasmonic nanostructures. Ceria nanoparticles are fluorescent nanostructures which can emit visible fluorescence emissions under violet excitation. Here, we investigated different added plasmonic nanostructures, such as gold nanoparticles (Au NPs) and Cadmium sulfide/selenide quantum dots (CdS/CdSe QDs), to check the enhancement of fluorescence intensity emissions caused by ceria NPs. Different plasmonic resonances of both aforementioned nanostructures have been selected to develop optical coupling with both fluorescence excitation and emission wavelengths of ceria. In addition, different additions whether in-situ or post-synthesis have been investigated. We found …

Special Section Guest Editorial: Machine Learning In Optics, Jonathan Howe, Travis Axtell, Khan Iftekharuddin

Electrical & Computer Engineering Faculty Publications

This guest editorial summarizes the Special Section on Machine Learning in Optics.

Mitochondrial Utilization Of Competing Fuels Is Altered In Insulin Resistant Skeletal Muscle Of Non-Obese Rats (Goto-Kakizaki), Nicola Lai, Ciarán E. Fealy, Chinna M. Kummitha, Silvia Cabras, John P. Kirwan, Charles L. Hoppel

Electrical & Computer Engineering Faculty Publications

Aim: Insulin-resistant skeletal muscle is characterized by metabolic inflexibility with associated alterations in substrate selection, mediated by peroxisome-proliferator activated receptor 𝜹 (PPAR𝜹). Although it is established that PPAR𝜹 contributes to the alteration of energy metabolism, it is not clear whether it plays a role in mitochondrial fuel competition. While nutrient overload may impair metabolic flexibility by fuel congestion within mitochondria, in absence of obesity defects at a mitochondrial level have not yet been excluded. We sought to determine whether reduced PPAR𝜹 content in insulin-resistant rat skeletal muscle of a non-obese rat model of T2DM (Goto-Kakizaki, GK) ameliorate the inhibitory effect …

Prefrontal High Gamma In Ecog Tags Periodicity Of Musical Rhythms In Perception And Imagination, S.A. Herff, C. Herff, A. J. Milne, Garett D. Johnson, J. J. Shih, D. J. Krusienski

Electrical & Computer Engineering Faculty Publications

Rhythmic auditory stimuli are known to elicit matching activity patterns in neural populations. Furthermore, recent research has established the particular importance of high-gamma brain activity in auditory processing by showing its involvement in auditory phrase segmentation and envelope tracking. Here, we use electrocorticographic (ECoG) recordings from eight human listeners to see whether periodicities in high-gamma activity track the periodicities in the envelope of musical rhythms during rhythm perception and imagination. Rhythm imagination was elicited by instructing participants to imagine the rhythm to continue during pauses of several repetitions. To identify electrodes whose periodicities in high-gamma activity track the periodicities in …

Vegetation Detection Using Deep Learning And Conventional Methods, Bulent Ayhan, Chiman Kwan, Bence Budavari, Liyun Kwan, Yan Lu, Daniel Perez, Jiang Li, Dimitrios Skarlatos, Marinos Vlachos

Electrical & Computer Engineering Faculty Publications

Land cover classification with the focus on chlorophyll-rich vegetation detection plays an important role in urban growth monitoring and planning, autonomous navigation, drone mapping, biodiversity conservation, etc. Conventional approaches usually apply the normalized difference vegetation index (NDVI) for vegetation detection. In this paper, we investigate the performance of deep learning and conventional methods for vegetation detection. Two deep learning methods, DeepLabV3+ and our customized convolutional neural network (CNN) were evaluated with respect to their detection performance when training and testing datasets originated from different geographical sites with different image resolutions. A novel object-based vegetation detection approach, which utilizes NDVI, computer …

A New Method Of Detecting And Interrupting High Impedance Faults By Specifying The Z-Source Breaker In Dc Power Networks, Sagar Bhatta, Ruiyun Fu, Yucheng Zhang

Electrical & Computer Engineering Faculty Publications

High impedance faults (HIFs) that cause a relatively smaller current magnitude compared to the traditional low impedance faults are not easily detectable but can cause an extreme threat to electric apparatus and system operation. This paper introduces a new method of detecting and interrupting HIFs in DC power networks by specifying Z-source circuit breakers (ZCBs). The ZCB is a protective device for high power DC branches, with the capabilities of protecting bidirectional power flow and automatic/controllable turnoff function. In this new method, the operational mode of ZCB (i.e., either the detection mode or interruption mode) can be specified. Beyond previous …

Real-Time Optimization Of Anti-Reflective Coatings For Cigs Solar Cells, Grace Rajan, Shankar Karki, Robert W. Collins, Nikolas J. Podraza, Sylvain Marsillac

Electrical & Computer Engineering Faculty Publications

A new method combining in-situ real-time spectroscopic ellipsometry and optical modeling to optimize the thickness of an anti-reflective (AR) coating for Cu(In,Ga)Se₂ (CIGS) solar cells is described and applied directly to fabricate devices. The model is based on transfer matrix theory with input from the accurate measurement of complex dielectric function spectra and thickness of each layer in the solar cell by spectroscopic ellipsometry. The AR coating thickness is optimized in real time to optically enhance device performance with varying thickness and properties of the constituent layers. Among the parameters studied, we notably demonstrate how changes in thickness of …

Priority Based Routing And Link Scheduling For Cognitive Radio Networks, Peng Jiang, Mitchell Zhou, Song Wen

Electrical & Computer Engineering Faculty Publications

To address the challenges caused by the time-varying rate requirement for multimedia communication sessions, we propose a Priority Based Routing and link Scheduling (PBRS) scheme for multi-hop cognitive radio networks. The objective is to minimize disruption to communication sessions due to channel switching as well as to minimize network resource consumption for multimedia applications based on a prioritized routing and resource allocation scheme. PBRS includes a priority based optimization formulation and an efficient algorithm to solve the problem. The main idea is to allocate the available resource to different types of services with their Quality of Experience (QoE) expectation as …

Superconducting Radio-Frequency Cavity Fault Classification Using Machine Learning At Jefferson Laboratory, Chris Tennant, Adam Carpenter, Tom Powers, Anna Shabalina Solopova, Lasitha Vidyaratne, Khan Iftekharuddin

Electrical & Computer Engineering Faculty Publications

We report on the development of machine learning models for classifying C100 superconducting radio-frequency (SRF) cavity faults in the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab. CEBAF is a continuous-wave recirculating linac utilizing 418 SRF cavities to accelerate electrons up to 12 GeV through five passes. Of these, 96 cavities (12 cryomodules) are designed with a digital low-level rf system configured such that a cavity fault triggers waveform recordings of 17 rf signals for each of the eight cavities in the cryomodule. Subject matter experts are able to analyze the collected time-series data and identify which of the …

Deep Learning With Context Encoding For Semantic Brain Tumor Segmentation And Patient Survival Prediction, Linmin Pei, Lasitha Vidyaratne, Md Monibor Rahman, Khan M. Iftekharuddin

Electrical & Computer Engineering Faculty Publications

One of the most challenging problems encountered in deep learning-based brain tumor segmentation models is the misclassification of tumor tissue classes due to the inherent imbalance in the class representation. Consequently, strong regularization methods are typically considered when training large-scale deep learning models for brain tumor segmentation to overcome undue bias towards representative tissue types. However, these regularization methods tend to be computationally exhaustive, and may not guarantee the learning of features representing all tumor tissue types that exist in the input MRI examples. Recent work in context encoding with deep CNN models have shown promise for semantic segmentation of …

Low Temperature Plasma Jets: Characterization And Biomedical Applications, Mounir Laroussi

Electrical & Computer Engineering Faculty Publications

No abstract provided.

Generative Adversarial Networks For Visible To Infrared Video Conversion, Mohammad Shahab Uddin, Jiang Li, Chiman Kwan (Ed.)

Electrical & Computer Engineering Faculty Publications

Deep learning models are data driven. For example, the most popular convolutional neural network (CNN) model used for image classification or object detection requires large labeled databases for training to achieve competitive performances. This requirement is not difficult to be satisfied in the visible domain since there are lots of labeled video and image databases available nowadays. However, given the less popularity of infrared (IR) camera, the availability of labeled infrared videos or image databases is limited. Therefore, training deep learning models in infrared domain is still challenging. In this chapter, we applied the pix2pix generative adversarial network (Pix2Pix GAN) …

Removal Of Blocking Artifacts From Jpeg-Compressed Images Using Neural Network, Md Nurul Amin

Theses and Dissertations

The goal of this research was to develop a neural network that will produce considerable improvement in the quality of JPEG compressed images, irrespective of compression level present in the images. In order to develop a computationally efficient algorithm for reducing blocky and Gibbs oscillation artifacts from JPEG compressed images, we integrated artificial intelligence to remove blocky and Gibbs oscillation artifacts. In this approach, alpha blend filter [7] was used to post process JPEG compressed images to reduce noise and artifacts without losing image details. Here alpha blending was controlled by a limit factor that considers the amount of compression …

Self-Efficacy Of Nacep Accredited Concurrent-Enrollment Program Instructors In Rural Community Colleges, Cecil B. Holland

Theses and Dissertations

Across the United States, high schools and community colleges are collaborating to offer students non-traditional educational programs that allow them to gain college credit including those accredited by the National Alliance of Concurrent Enrollment Partnerships (NACEP). Those teaching these classes must have high self-efficacy and enjoy their work if they are going to make a positive impact on the students they are educating. The theoretical framework for this research is based on Bandura’s Self-Efficacy Theory. The methodology for this qualitative research study utilized an integrated approach. Data collection consisted of one-on-one interviews with instructors who teach NACEP courses, administrators who …

Twice-Exceptional College Students Narratives: When Giftedness And Mental Health Intersect, Emily Dubord Hill

Theses and Dissertations

Gifted college students often arrive at universities with high GPAs and/or ACT/SAT scores. Their achievements in extracurricular activities such as in the arts, athletics, service, and leadership are well beyond the average student. To admissions representatives and faculty, these students look well-adjusted and successful on paper. However, many of these gifted college students come with unique challenges that go misunderstood, ignored, and underserved during their years in higher education—specifically involving their mental health.

There are copious amounts of literature on gifted K-12 students and their mental health behaviors but very limited research done on the gifted college student population. Although …

Not Your Advisor’S Doctorate: The Doctor Of Arts And The Modernization Of Higher Education 1945-1970, Andrew Faber Larson

Theses and Dissertations

The “modernization” of higher education, 1945-1970, was a transitional period in American higher education. It was marked by a number of challenges that prompted rapid change in institutions around the United States. These changes were accompanied by expedient expansion in curriculum, faculty size, and physical plant of universities. One of the changes that came out of the period of modernization was the establishment of the Doctor of Arts degree as a way to produce professional faculty to fill open positions created by the rapid expansion of the modernization. As a result, the Doctor of Arts served as a modernization solution …

Pilot Perception Of Automation Use: A Generational Assessment, Ryan Leadens

Theses and Dissertations

As flight deck technology has become more advanced, the pilot–machine interaction has become a larger point of emphasis in pilot training programs. Increasing demand for air travel in future decades will create greater need for highly accurate and reliable navigation systems. These systems reduce a pilots’ exposure to “stick and rudder” skills while increasing the knowledge and situational awareness required to operate safely.

It is imperative that pilots are properly trained on these systems prior to conducting line operations. In order to create an efficient and effective training program, it is important to understand how pilots perceive their role on …

Performance Evaluation Of Sustainable Pavement Materials, Robeam Solomon Melaku

Theses and Dissertations

In the United States (US), there are more than 2 million miles of paved roads. About 93 percent of those are surfaced with asphalt mixtures (flexible pavements). Shortage of natural resources, environmental impact of pavement life cycle and pavement distress are the major concerns of the pavement industry. Higher percentage Reclaimed Asphalt Pavement (RAP) usage, alternative asphalt pavement additives and development of performance related pavement analysis are the major factors to improve sustainability of the pavement. In this dissertation, extensive studies were conducted on the use of sustainable materials and performance analysis. Use of Waste Cooking Oil (WCO) and Soy …

A Study Of The Feasibility Of Growth, Extraction, And Industrial Scale Up Processing Of Microalgae Lipids., Jasmine Oleksik

Theses and Dissertations

The interest in microalgae as a plausible alternative to crop oils as a raw material in the form of triglycerides and free fatty acids (FA oils) for renewable fuels and chemicals is increasing and it is a widespread research topic at the lab scale. Microalgae contain a higher lipid content on a dry weight basis compared to oilseeds such as soybeans. Additionally, the growth and cultivation cycle of microalgae is 15 days, in comparison to soybeans where the cycle occurs once or twice annually. Despite these advantages, to date it has been uneconomical to produce microalgae oils in a world-scale …

A New Approach To Measure Unique Spectral Response Characteristics For Irregularly Shaped Photovoltaic Arrays, Anthony Rafael Peters

Theses and Dissertations

Current photovoltaic (PV) panel test methods do not provide efficient and repeatable standardization, which can result in inconsistent results. Test requirements for individual PV cells are promulgated by standard test conditions (STC), but do not directly translate to new array or panel designs, particularly for panels that are irregularly shaped and used for different applications. Optimal angles that yield the most power delivery from the PV device when integrated into a panel are achieved by manipulating the panel’s orientation via single or dual axis tracking (e.g., maximum power point tracking). In applications where PV is intended to be integrated into …

Critical Contingency Eva’S For 3d-Printed Planetary Habitats, James Robert Stoffel

Theses and Dissertations

This novel pilot study evaluates the potential associated tools, methods, and concept of operations required for a Critical Contingency Extravehicular Activity (CCE) repair of a 3D-printed in-situ resource utilization (ISRU) Lunar and Martian habitat. With NASA’s current 2020 Technology Roadmap and Taxonomy for TX06: Human Health, Life Support, and Habitation Systems (e.g. Extravehicular Activities, Habitation, Human Factors), TX07: Exploration Destination Systems (e.g. ISRU, Maintenance, Repair, Operations, Safety), TX12: Materials, Structures, Mechanical Systems, and Manufacturing, and the Centennial 3D-Printed Habitat Challenge, this research will provide an initial evaluation of standard repair methods on the system’s functional abilities, environmental, and human factors …

Coupled Simulation Of Hydraulic Fracturing, Production, And Refracturing For Unconventional Reservoirs, Xincheng Wan

Theses and Dissertations

Horizontal well drilling and multi-stage hydraulic fracturing are two key techniques for the development of unconventional reservoir. However, the production from tight formation is associate with fast depletion of reservoir. When oil price is low, drilling new horizontal wells is not profitable. Creating secondary fractures from existing hydraulic fractured wells, i.e., refracture is an alternative method to increase stimulated reservoir volume (SRV) and gain additional production from existing hydraulic fractured wells. To optimize refracturing well selection and operation, it’s of economic importance to acquire knowledge from initial hydraulic fracturing operation, production history, and refracturing design perspectives. This initiated the idea …

Gemütlichkeit Verboten: The Influence Of World War I Anti-German Sentiments On Prohibition, Susanne Schenk Watts

Theses and Dissertations

The proximity and simultaneity of World War I and Prohibition pose questions of a shared and connected relationship. The current historiography falls short to connect these two seminal events and their impact on German-American communities. This study expands the existing literature by analyzing the reactions of two German-American communities (New Ulm, Minnesota, and St. Louis, Missouri) to Prohibition against the backdrop of anti-German sentiments of World War I. Using a diverse range of sources (anti-German war propaganda material, Anti-Saloon League posters, material from the United States Brewers’ Association and US Senate investigation, as well as German and English-language newspapers from …