Engineering Commons^™

A Human-Centered Framework For Oncological Healthcare System Modeling Applied To Mobile Radiation Delivery, Alex Price

Doctoral Dissertations

"Healthcare systems engineering is challenging due to the complexity, geographic expansiveness, inertial properties, and the heterogeneous sub-systems, with varying vested interests. Additionally, humans comprise many of the forms and functions, and are independent, with resistance and uncertainty in their decision-making that adds complexity. Human-centered systems modeling approaches are therefore needed to capture this unique aspect of a healthcare system and to enhance understanding of emergent healthcare properties. This dissertation focuses on integrating systems modeling within healthcare and emphasizes the importance of incorporating human decision-making. Moreover, the incorporation of a human-centered approach yields particularly valuable insights into the decision-making processes that …

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 …

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 …

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 …

Additive Manufacturing Of Steel And Aluminum Structures: Modeling And Experiments, Manoj Kumar Reddy Rangapuram

Doctoral Dissertations

"Additive manufacturing (AM) is defined as the process of joining materials to make objects from three-dimensional model data. Complex geometries can be easily manufactured compared to conventional subtractive methods with more freedom and flexibility in the design process. As the demand for AM process increased, it has become critical to understand the process and various parameters that constitute in affecting the quality of the manufactured part. Conducting experiments can be time intensive and costly to optimize a process. Modeling can be used as an aid to optimize, examine, and predict the process outcome.

The objective of this study is (i) …

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 …

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 …

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 …

Semiconductor Physics Based Signal Integrity Analysis For 3d Ic, Ze Sun

Doctoral Dissertations

"Three-dimensional integrated circuits (3DICs) are becoming increasingly popular in high-speed electrical systems. 3DICs are made by stacking multiple dies vertically and connecting them with through-silicon vias (TSVs). In this dissertation, three studies were carried out to model the performance of 3DICs in extreme working conditions and the signal integrity (SI) performance of 3DICs.

First, an in-house Monte Carlo particle simulator was developed to characterize extreme working conditions (ESD/EMP) for ICs at the microscopic level instead of the macroscopic level. The ability of the simulator was demonstrated by modeling a voltage regulator diode under forward and reverse bias. The diode simulation …

Development Of Uas And Geophysical Techniques For Agriculture And Environmental Site Characterization, Yunyi Guan

Doctoral Dissertations

"Soil properties are critical for agricultural management. Geophysical techniques such as ground penetrating radar (GPR) and electromagnetic induction have been used to measure soil properties for agricultural applications. However, their measurements are only acquired along select traverses within a field, and the data processing can be time-consuming, the instruments can also be expensive. Unmanned aerial vehicles (UAVs) are a recent advancement used for precision agriculture. Compared with geophysical data, UAVs have higher resolution and wider coverage and can quickly collect data across the whole field. The operation is also relatively simpler with a more economical acquisition cost. This research investigates …

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 …

Modeling And Analysis Of Dc-Dc Converters For Power Distribution Networks Design, Junho Joo

Doctoral Dissertations

"Accurate modeling of power distribution networks (PDN) including voltage regulator module (VRM) is critical for high-performance digital systems including low- to high-power applications such as laptops and mobile platforms. As a consolidated end-to-end power source, PDN can be divided into several parts: the VRM to regulate the external voltage source, printed circuit board (PCB) PDN, package PDN, and on-chip PDN. A transient current drawn from the on-die circuitry will produce an instantaneous voltage drop at the bump. The time domain behavior of such a drop and the subsequent recovery is called voltage droop which is strongly associated with the VRM …

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 …

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 …

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 …

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 …

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 …

Exploring Seismic Anisotropy In The Crust And Mantle Of The Tibetan Plateau And Analyzing Seismic Velocity Variations In Yellowstone, Cong Shen

Doctoral Dissertations

"Seismology is a scientific discipline that utilizes seismic waves to investigate the deep structures within the Earth's interior, which are otherwise inaccessible to direct observation by humans. These seismic waves can be categorized into two types: body waves and surface waves, each with distinct propagation modes and behaviors, carrying valuable information about their travel paths. The first paper concentrates on the analysis and inversion of body waves produced by large seismic events. It employs shear wave splitting and receiver function methods to explore the geodynamic structure of the south-central Tibetan Plateau, near the plate boundary. The investigation covers the depth …

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 …

The Development Of Hard Materials And Fibrous Monolith Composites For Friction Stir Welding, Paul Michael Brune

Doctoral Dissertations

"This research focuses on the development of hard materials and fibrous monolith composites for the purpose of adding to current friction stir welding tool technology. Well studied hard material systems, such as WC-Co, were incorporated and evaluated as cell materials for fibrous monolith composites with ductile cell boundaries of Co, W, and Mo. The indentation behavior of the WC-Co and WC-Co-cBN composites indicated possible crack deflection at the cell/cell boundary interface. Cylindrical pin friction stir welding tools were developed for each of the three fibrous monolith material systems. Welding was achieved on AA1100 aluminum, 260 brass, and AISI 1018 steel …

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, …

Paleoecological And Paleoclimatic Reconstructions Based On Holocene Sediment Cores, Lake Izabal, Eastern Guatemala, Erdoo Mongol

Doctoral Dissertations

"The Maya Region in Central America is characterized by pronounced discrepancies in precipitation, resulting in high precipitation gradients that support large-scale differences in vegetation across the region. Several lake deposits and other paleoclimate archives in the region have been studied to reconstruct past climates and palaeoecological conditions. However, actual data from proxy records have not been qualitatively and quantitatively utilized to interpret the behavior of the vegetation in moister areas within the Maya Region, such as the Lake Izabal Basin (LIB). The palynomorphs from two sediment cores in the LIB provided a good opportunity to infer the patterns of past …

In Situ Infrared Thermographic Inspection In Additive Manufacturing, Tao Liu

Doctoral Dissertations

"Laser Powder Bed Fusion (LPBF) is a key technique in metal additive manufacturing and has undergone extensive research over the past few decades. It enables the fabrication of complex geometries directly from digital design models. The solidification process in LPBF is heavily influenced by the characteristics of the powder layer, including its thickness and thermal transport properties. Additionally, the performance of the printed part is impacted by the temperature history during solidification and the final residual stress field. While these topics have been the focus of many studies, almost all research has concentrated on ex-situ measurement and testing. These ex-situ …

Topography Of The 410 And 660 Km Discontinuities Beneath The Tibetan Plateau And Adjacent Areas, Zexin Miao

Doctoral Dissertations

"The Tibetan Plateau represents the ongoing geotectonic aftermath of a continental collision initiated approximately 65 million years ago. Despite numerous seismological studies, controversies remain regarding the structure, evolution, and dynamics of the crust and mantle beneath Tibetan Plateau. In this study, we used teleseismic broadband data to investigate the topography of the mantle transition zone (MTZ) discontinuities. A total of ~655,000 receiver functions from 735 stations was utilized to image the 410 and 660 km discontinuities bordering the MTZ. Combining the observed and velocity corrected results, several areas in the central Tibet exhibit a typical d410 and an anomalously deep …

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 …

Deep Reinforcement Learning Based Strategies For Inverter Dominated Microgrids, Oroghene Oboreh-Snapps

Doctoral Dissertations

The integration of inverter-based distributed generators (IBDGs) in modern power systems has ushered in a new era of renewable energy utilization, prompting the rise of Microgrid (MG) architectures. Nevertheless, as IBDG penetration increases, a host of challenges surface. Foremost among these challenges are issues related to frequency stability stemming from the inherent lack of inertia in IBDGs, and inaccurate sharing of reactive and active power, particularly evident in parallel IBDG networks with mismatched feeder impedance. This research presents novel solutions to these challenges by adopting deep reinforcement learning (DRL), specifically, the twin delayed deep deterministic policy gradient (TD3) algorithm, to …