Digital Commons Network^™

Experimental Investigation Of High-Temperature Brine-Shale Interactions, Anna Atasha Hoffmann

Doctoral Dissertations

"Hydrofracturing (fracking), a common practice in the Petroleum Industry to induce or improve fluid flow in tight formations, creates chemical disequilibrium that further alters the porosity and permeability of host rocks and results in the production of saline and contaminated produced waters (PW). The PW of the Tuscaloosa Marine Shale (TMS) are Na-Ca-Mg-K-Cl brines with mean concentrations of approximately 16% Total Dissolved Solids (TDS) and circumneutral pH. Analysis of composition suggests the PW result from a 20 to 80% dilution of formation waters (relict brines of the Louann Salt) by fracking fluid. Trace element concentrations generally show moderate to strong …

Integrated Study Of Heat Transfer And Local Gas Dynamics In A Pebble Bed Very High Temperature Nuclear Reactor Using Advance Measurement Techniques, Muhna N. Alshammari

Doctoral Dissertations

"The aim of this study, pebbles of diameter of 5 cm and a pebble-to-diameter ratio (aspect ratio) of 6 were used. In part I, the local gas velocities were studied at different radial and axial locations in the pebble bed using a sophisticated hot wire anemometry (HWA) technique, which was supported with a novel probe-protector case to protect the fragile probe, allowing the measurements to be taken between the pebbles for the first time. The local gas velocities were found to be significantly higher in the near wall region due to the higher void fractions in the near-wall region, compared …

The Comprehensive Study Of High Viscosity Friction Reducers In High-Tds And High-Temperature Environments, Xiaojing Ge

Doctoral Dissertations

"High viscosity friction reducers (HVFRs) have been recently gaining more attention and increasing in use, not only as friction-reducing agents but also as proppant carriers. Reusing of produced water has also been driven by both environmental and economic benefits. Currently, most friction reducers on the market are anionic friction reducers, which are fully compatible with most produced water with low to medium level of Total Dissolved Solids (TDS) but show a significant drop at high TDS conditions in term of their friction reduction performance in most cases. On the contrary, cationic friction reducers are believed to have better TDS tolerance …

Understanding Catalyst Design Principles In Transition Metal Mixed Anionic Chalcogenides For Electrocatalytic Energy Conversion, Ibrahim Abdullahi

Doctoral Dissertations

"This research focused on the synthetic design of transition metal mixed anionic chalcogenide catalysts containing various ligand types around the central metal atom (chalcogen anion and chalcogen-based organic ligand) generating diverse crystal structure types applied for water splitting and carbon dioxide reduction reactions (CO₂RR).

A series of catalysts were synthesized starting with isolated metal complexes (ME_n) with a central metal core (M = Co, Ni, Cu, and Cr) through molecular clusters, to bulk nanostructured solids of similar M-E coordination. Bis(dichalcogenoimidodiphosphinato) were employed as ligands in the metal complexes, and anionic chalcogen (E = S, Se, and …

Improving Decision-Making Processes In Construction And Infrastructure Bidding: Qualitative And Quantitative Approaches Including Graph Theory, Game Theory, And Machine Learning, Muaz Osman Elzubeir Ahmed

Doctoral Dissertations

"Construction and infrastructure bidding is a highly competitive process that entails various uncertainties faced by contractors. Contractors weigh various factors to determine the expected benefits of a construction project and decide their bid value. However, the situation is more complex in multi-stage bidding (MSG), where general contractors must account for the bids of their subcontractors and face a greater threat of the winner’s curse (i.e., situation where the winning contractor underestimates the actual cost of the project). As such, bidding-related complexities, risks, and uncertainties, if uncontrolled, can lead to the rise of claims and disputes between stakeholders. Existing research falls …

A Lightweight Machine-Learning Framework For Enhancing Security In Iot Blockchain Networks, Charles Connor Rawlins

Doctoral Dissertations

"Blockchain is one of the fastest technologies that rivals the Internet in terms of adoption speed. This security method is applicable to data-centric environments for validating data in the presence of faults. However, traditional blockchain implementation introduces bottlenecks with computationally intense security measures to prevent malicious spam and resolve conflicts. This dissertation explores a new direction for blockchain technology that allows limited nodes, like IoT devices, to make independent decisions with compressed knowledge of past blockchain history through the use of machine-learning for active decisions (or the first machine-intelligent blockchain protocol). Proposing to introduce machine-intelligence into the rapidly evolving paradigm …

Development And Testing Of High Strength Scalable High Entropy Alloys, Hans Jakob Pommerenke

Doctoral Dissertations

"High entropy alloys have shown promise through their ability to be tailored to specific scenarios. From highly corrosive environments to precipitation strengthened alloys to radiation environments high entropy alloys allow tailor made alloys for every solution. New compositions are developed and tested but little work focuses on the processing effect choosing rather than using processing as a steppingstone to achieve properties without investigating the processing effects. This work focuses on single phase face-centered cubic alloys strengthened by processing and precipitation strengthening. In conjunction with the development of these alloys, the ability to scale production will be investigated and characterized to …

Communication Modality And Activity Recognition In Smart Manufacturing, Haodong Chen

Doctoral Dissertations

"Advancements in sensors, computational intelligence, and big data have been rapidly transforming and revolutionizing the manufacturing sector, leading to robot-rich and digitally connected factories. To facilitate such a transformative process, workforce training and coordination between the human workforce and robots have remained a major challenge. This study aims to create intelligent workforce training systems for human-computer interaction and human-robot collaboration. It proposes the use of dynamic gestures and speech commands for seamless communication between a worker and a robot, leveraging Convolutional Neural Networks (CNN) and multiple threading for recognition and integration. Additionally, a fine-grained activity recognition model has been crafted …

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 …

Efficient Modeling And Simulation For The Aerothermal Analysis Of Particle-Laden Hypersonic Flows, Andrew Hinkle

Doctoral Dissertations

"Standard approaches for simulating hypersonic flows in particle-laden environments have key limitations in practice, such as high cost and numerical noise. In this work, efficient solution strategies for particle-laden hypersonic flows were developed using both Lagrangian and Eulerian models for the particle phase with the focus on investigating spacecraft surface erosion, as well as convective and radiative heat flux augmentation due to atmospheric particulate encountered during planetary entry.

First, an efficient integration strategy for Lagrangian methods, the Trajectory Control Volume (TCV) method, was developed for steady analysis of dilute particle phase problems on general geometries. The TCV method was shown …

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 …

Investigation Of Wide Beam And Interfacial Shear Transfer In Reinforced Concrete Structures, Nikkolas Edgmond

Doctoral Dissertations

"The use of reinforced concrete (RC) allows for unique designs of structural elements and connections because of the ability to vary the geometry and reinforcement detailing with ease. However, this freedom in the design process can lead to specialized conditions that have not been extensively studied by means of experimental testing. This is especially true for components or regions of components that are subjected to high shear loads, which are susceptible to undesirable and brittle failures. While many studies have been conducted to investigate the shear behavior of RC structural members and components to determine the critical design parameters, these …

Investigation Wettability Contact Angle Using 2d Imaging Technology, Saleh Alsayegh

Doctoral Dissertations

"Investigation wetting preference of tight carbonate reservoir rocks and several other unconventional reservoir rocks, and their relation to oil production, is becoming noticeably important for field development in Kuwait, as in many future unconventional tight carbonate reservoirs in the Middle East. The overall objective of this investigating and modeling study is to discover many fundamental relationships from totality wettability preference as a tool for reservoir recovery predictions and management. The investigation includes advancing position of water wet preference into smaller capillaries of the matrix voids and incrementally more oil-wet into larger capillaries of natural fractures (NF). Also, investigating water/ oil …

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 …

Development Of A Comprehensive Multi-Factored Methodology For Identification Of Landslides In The Buffalo National River Of Arkansas, Abdurraouf Okok

Doctoral Dissertations

"In northern Arkansas's Springfield and Boston Mountain Plateaus, distinctive geomorphological landslide features have shown historical continuity. USGS topographic maps (1:24,000, 7.5-minute series) serve as valuable resources for studying terrain characteristics and hydrological patterns.

This study uses a manual mapping approach with high-resolution LiDAR data and geological maps in a GIS environment. The method identifies historic landslide features by analyzing anomalous topographic contour patterns overlaid on LiDAR-derived hillshade maps, revealing various mass movements along the Buffalo National River. Data from the Office of State Geologist and fieldwork reconnaissance were utilized to map older landslide features with high confidence. Some previously unrecognized …

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 …

Optimizing The Total Life Cycle Of Li-Ion Batteries: From Constant Gradient Charging To Aged Cell Performance Restoration, Kasim Adesegun Adewuyi

Doctoral Dissertations

As demand for Lithium-Ion Batteries (LIBs) have skyrocketed over the past decade, the need for better charging methodologies and recycling methods have become vitally important. At a fundamental level, this dissertation strives to fulfill the green promise of a future without fossil fuels. In order to promote a transition away from fossil fuels, LIBs for vehicles require ultrafast charging times equivalent to a normal vehicle (6 mins). However, this process leads to high volume expansion for next generation electrode materials which causes degradation. Without limiting this factor, the environmental impact shifts from oil rigs to Li mines and landfills. The …

Advancing A Systems Perspective On Innovative Behavior, Stephen Demski

Doctoral Dissertations

"Engineering organizations pursue innovation in strategy, structure, processes, and the services and products offered to remain relevant and competitive. Identifying factors supporting or constraining innovative work behavior and recognizing the complexity of their interactions are vital to sustaining an innovative workforce, yet how factors interact has not been comprehensively studied.

Recognizing innovative work behavior as the output of a complex system of factors guided this study’s literature search that identified over one hundred individual, team, and organizational factors influencing innovative behavior, interviews of engineers to learn what factors are essential in their work environment, and Delphi survey to rank factors, …

Control And Optimization Of Energy Storage System In Power Distribution System, Waqas Ur Rehman

Doctoral Dissertations

"The widespread adoption of electric vehicles (EVs) and transportation electrification is encumbered by two chief barriers: i) the limited driving range of EVs in the market today and ii) inadequate fast-charging infrastructure for long-distance trips. Extreme fast charging (XFC) technology can recharge EVs in less than 10 minutes for 200 miles range. Firstly, a novel robust optimization-based mixed integer linear programming model is proposed to size a battery energy storage system (BESS) and PV system in an XFCS. In this part, it is assumed that the sizing and location of the XFCS are known. Secondly, the aforesaid assumption is relaxed, …

Low-Shrinkage Fiber-Reinforced Concrete For Infrastructure Construction And Rehabilitation, Jingjie Wei

Doctoral Dissertations

"The aim of this study is to develop two classes of low-shrinkage high-performance concrete (HPC): fiber-reinforced super workable concrete (FR-SWC) for infrastructure construction and fiber-reinforced self-consolidating concrete (FR-SCC) for repair applications. HPC with excess content of shrinkage mitigation materials (SMMs), including shrinkage-reducing admixture (SRA), superabsorbent polymer (SAP), and expansive agent (EA) has a detrimental effect on mechanical performance. These classes of HPC were optimized to reduce shrinkage, enhance mechanical properties, and improve durability. The effect of fiber type (macro synthetic fiber, MSF; 5D steel fiber, 5D; 80% 3D + 20% short steel fibers; STST), SMMs, and plastic viscosity on bond …

Contextualizing Renewable Energy Adoption: An Examination Of The Role Of Community Choice Aggregation, Ankit Agarwal

Doctoral Dissertations

"The rapid expansion of renewable energy generation in the U.S., both through distributed and utility-scale facilities, is largely driven by top-down policy measures and the growing engagement of residential consumers on both individual and community levels. Previous studies on motives behind residential renewable energy adoption have examined procurement options in isolation and within a static context, primarily focused on intrinsic attributes like economic incentives, emission reductions, and peer popularity. This research introduces a novel context, assessing renewable procurement options in the presence of Community Choice Aggregation (CCA), a more prevalent and accessible alternative. This dissertation makes four pivotal contributions, offering …

The Science Of Gravitational-Wave Sources And Beyond Compact Binary Coalescences, Yanyan Zheng

Doctoral Dissertations

"This work focuses on the field of gravitational-wave astronomy by extending the scope of detectable sources beyond compact binary coalescences, All the gravitational-wave detections so far come from compact binary coalescences. Focusing on core-collapse supernovae as promising sources for short gravitational-wave transients, this work reports optically targeted searches for gravitational-wave emitted by core-collapse supernovae during the third observing run of the LIGO and Virgo detectors. It also predicts the search sensitivity for the ongoing fourth and forthcoming fifth observing runs. Moreover, the work introduces a novel computational framework for testing the spatial distribution of binary black hole sources, allowing for …

Material Models For Simulation Of Steel Hot Rolling Process Using Experimentally Determined Properties At Elevated Temperatures And Strain Rates, Siva Sai Krishna Dasari

Doctoral Dissertations

"Hot rolling is one of the most important and complex process that includes large material deformation, different contact conditions, complex geometries and different temperature gradients along with micro structural changes such as viscoplasticity, dynamic recrystallization, and static softening. In the present work, the viscoplasticity, damage evolution, static softening and void closure of alloyed metal during hot rolling process was numerically investigated. Gleeble^TM hot compression and double hit tests were performed to provide experimental stress-strain curves at recrystallization temperatures and at different strain rates. Johnson-Cook viscoplastic model was calibrated using experimental stress-strain curves. Static softening model was developed at varying …

Deep Learning Techniques For Image Segmentation In Dermoscopic Skin Cancer Images, Norsang Lama

Doctoral Dissertations

"Melanoma is recognized as the most lethal type of skin cancer, responsible for a significant proportion of skin cancer-related deaths. However, early detection of melanoma is essential for successful treatment outcomes. Computer-aided skin cancer diagnosis tools can save lives by enabling earlier detection of skin cancer. Image segmentation is a crucial step in computer-aided diagnosis as it allows the detection of critical features or regions in an image. Thus, an accurate image segmentation method is necessary to create a more precise computer-aided diagnostic tool for skin cancer diagnosis. This dissertation includes investigating and developing deep learning techniques to improve image …

Improvements In Biomedical Image Analysis With Computational Intelligence And Data Fusion Techniques, Akanksha Maurya

Doctoral Dissertations

"An estimated 2 million new cases of basal cell carcinoma (BCC) are diagnosed each year in the United States, making it one of the most common skin cancers. Earlier detection of these cancers enables less invasive biopsies. Clinical detection consists of a preliminary visual observation of these skin lesions by an experienced dermatologist making it a specialized task highly dependent on their time, availability, and resources. Hence, there is a need for automating this process that can assist healthcare staff. In recent years, deep learning (DL) has been used extensively and successfully to diagnose different cancers in dermoscopic images. Telangiectasia …

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 …

Applications Of Computational Intelligence And Data Fusion Techniques For Biomedical Images, Anand Krishnadas Nambisan

Doctoral Dissertations

"The realm of melanoma diagnosis has been significantly advanced by deep learning (DL) techniques, yet the current approaches are not without limitations, including missed diagnoses and the challenge of interpreting these "black box" models. The research is comprised of three studies, each contributing uniquely towards advancing melanoma detection accuracy and interpretability. The first study focuses on improving the detection of specific dermoscopic structures through a deep learning-based segmentation approach, while the second study builds upon this by employing a fusion technique that combines traditional image features with advanced deep learning models. This method significantly improves melanoma detection, particularly in recall …

Processing-Microstructure-Properties Relationships In Additively Manufactured Zrb2-Sic Ceramics, Marharyta Lakusta

Doctoral Dissertations

"The study explores the pressure less sintering (PS) and chemical compatibility of ZrB₂-30 vol.%SiC produced by additive manufacturing (AM) with CO₂. The oxidation kinetics and scale microstructures were compared for ZrB₂-SiC made by hot pressing (HP) and by AM coupled with PS. All specimens exhibited parabolic oxidation kinetics. The difference in oxidation behavior becomes evident at temperatures of 1100-1400°C (200-900h). Oxidation rates increased as grain size increased. Similar oxide scale morphologies were observed in both CO₂ and air, with an outer borosilicate layer and an inner porous ZrO₂ layer containing partially oxidized …

Investigating Detonation Parameters Through The Plate Dent Test: A Novel Approach For Characterizing Detonation Curvature And Thickness, Emily Michelle Johnson

Doctoral Dissertations

Detonation is the driving factor behind how an explosive, used in an array of applications, performs. Understanding and measuring detonation parameters of an explosive is key in explosive charge design and application. Currently, determining parameters is costly as the instrumentation needed is expensive in terms of price, maintenance, and personnel. This research examines two methods of determining detonation parameters through measurement of secondary material response to the detonation wave in an effort to provide an alternate, simple, and inexpensive method of measurement. The first of these studies focuses on the Gurney Model and demonstrates that the model's accuracy was diminished …

High Viscosity Friction Reducer Evaluation At High Temperature And High Tds Environments, Ghith Ali Ahmed Biheri

Doctoral Dissertations

"In unconventional reservoirs, proppant transport during hydraulic fracturing treatments could be successful when the proppant is placed further within the reservoir's fracture networks. This could increase the reservoir formation conductivities and improve the productivity of the wells. This job of improving the reservoir conductivity by distributing and transporting proppant can be conducted by reliable fracture fluids with excellent fluid rheology (e.g., viscosity and elasticity). However, several challenges, including the high temperatures and the presence of high TDS in produced water, may limit the capability of fracture fluids to transport proppant. Additionally, the use of fracture fluid has raised fears regarding …