Digital Commons Network^™

Convective-Diffusive Transport In Krogh Cylinders: A Model For Pharmacokinetics, Xianjie Qiu

Doctoral Dissertations

"Drug delivery to inside of the tumor is the important problem. The dynamics of drug delivery is presented here. Previously and particularly for directed delivery, a stirred tank model has been used, which appears to have worked well when compared to experiments. However, the stirred tank models do not include all the mass transfer resistances and towards that end we have used a distributed system called Krogh cylinder. This study focuses on the Krogh cylinder model simulation, both on the fluid flow and the mass transfer. The capillary network is broken down into cylindrical cells, each containing a capillary and …

Investigation Of Packed Bed And Moving Bed Reactors With Benchmarking Using Advanced Measurement And Computational Techniques, Binbin Qi

Doctoral Dissertations

"Trickle bed reactors (TBR), as typical packed bed reactors (PBR), are widely used in various fields. Very limited information regarding the flow behaviors, hydrodynamic, and mathematical models in extrudate catalyst shapes, such as cylinders, trilobes, and quadrilobes, can be found in literatures because the major focus was on spherical shape. Therefore, a hybrid pressure drops and liquid holdup phenomenological model for extrudate catalyst shapes was developed based on two-phase volume averaged equations, which showed high accuracy against experimental data. The maldistribution and dynamic liquid holdup were investigated in quadrilobe catalyst using gamma-ray computed tomography. A pseudo-3D empirical model was developed …

Modeling Time Series With Conditional Heteroscedastic Structure, Ratnayake Mudiyanselage Isuru Panduka Ratnayake

Doctoral Dissertations

"Models with a conditional heteroscedastic variance structure play a vital role in many applications, including modeling financial volatility. In this dissertation several existing formulations, motivated by the Generalized Autoregressive Conditional Heteroscedastic model, are further generalized to provide more effective modeling of price range data well as count data. First, the Conditional Autoregressive Range (CARR) model is generalized by introducing a composite range-based multiplicative component formulation named the Composite CARR model. This formulation enables a more effective modeling of the long and short-term volatility components present in price range data. It treats the long-term volatility as a stochastic component that in …

Modeling And Analyzing Parasitic Parameters In High Frequency Converters, Mohamad Saleh Sanjari Nia

Doctoral Dissertations

"This research focuses on electromagnetic interference (EMI) / electromagnetic compatibility (EMC) design and analysis in power electronics systems. To limit the EMI under the standards, different methods and strategies are investigated. Parasitic parameters of high frequency (HF) transformer are analyzed using a novel analytical method, finite element method (FEM), and experimental measurements for different structures and windings arrangements. Also, the magnetic field, electric field, electric displacement, and electric potential distribution are simulated and analyzed. Moreover, a high voltage system is considered and analyzed to improve the EMC. The EMI propagation paths are analyzed. The EMI noise level of the system …

Integrating Snp Data And Imputation Methods Into The Dna Methylation Analysis Framework, Yuqing Su

Doctoral Dissertations

"DNA methylation is a widely studied epigenetic modification that can influence the expression and regulation of functional genes, especially those related to aging, cancer and other diseases. The common goal of methylation studies is to find differences in methylation levels between samples collected under different conditions. Differences can be detected at the site level, but regulated methylation targets are most commonly clustered into short regions. Thus, identifying differentially methylated regions (DMRs) between different groups is of prime interest. Despite advanced technology that enables measuring methylation genome-wide, misinterpretations in the readings can arise due to the existence of single nucleotide polymorphisms …

Crustal And Upper Mantle Structure Beneath The Southeastern United States From Joint Inversion Of Rayleigh Wave Dispersion And Receiver Functions, Qiuyue Yang

Doctoral Dissertations

"In spite of numerous geophysical investigations have been conducted in southeastern United States, the structure and evolution of the crust and lithospheric mantle remain controversial due the thick sedimentary covers atop the crust of the coastal plains there. In this study, we use data from 186 broadband seismic stations belonging to the USArray Transportable Array to construct a 3-D shear wave velocity model for the southeastern United States for the top 180 km by a joint inversion of Rayleigh wave phase velocity dispersion and receiver functions. Our results show a clear spatial correspondence with major surficial geological features. A prominent …

A Fuzzy Clustering Methodology To Analyze Interfaces And Assess Integration Risks In Large-Scale Systems, Josh Henry Goldschmid

Doctoral Dissertations

“Interface analysis and integration risk assessment for a large-scale, complex system is a difficult systems engineering task, but critical to the success of engineering systems with extraordinary capabilities. When dealing with large-scale systems there is little time for data gathering and often the analysis can be overwhelmed by unknowns and sometimes important factors are not measurable because of the complexities of the interconnections within the system. This research examines the significance of interface analysis and management, identifies weaknesses in literature on risk assessment for a complex system, and exploits the benefits of soft computing approaches in the interface analysis in …

Emi Characterization For Power Supplies And Machine Learning Based Modeling In Emc/Si, Jiayi He

Doctoral Dissertations

"Signal integrity (SI) and electromagnetic interference (EMI) are essential for consumer electronics and high-speed server applications. It is necessary to do EMI and SI modeling at the design stage. In this research, several modeling approaches for EMI and SI problems are proposed. By using measurement-based modeling method, the mechanism of conducted emissions (CE) on ac to dc power supplies in an LED TV is analyzed. A system-level transient simulation model is built to predict the conducted emission (CE). To characterize the equivalent dipole moment sources in RFI and EMI problems, a dipole source reconstruction method based on machine learning techniques …

Gis And Remote Sensing Groundwater Potentiality Investigation Of Gulu District, Uganda Using Synthetic Aperture Radar And Magnetic Geophysics, Rachel Ann Jones

Doctoral Dissertations

“Developing countries have few resources for ground-based hydrological investigations to determine optimal placement of boreholes for community water access. Remote sensing data are available at a variety of resolutions and sense different parameters, and are useful inputs for hydrologic models, but these data are rarely obtainable in developing countries with the parameters or resolutions necessary for hydrologic applications. This research seeks to use and improve existing remote sensing and GIS techniques to identify areas of optimal water supply in locations with limited geologic or hydrologic information, such as Gulu District, Uganda. Fusing different remotely sensed data sets can produce higher …

An Investigation On The Regulation Of The Tweak–Fn14–Nf-Kb Pathway, Jawahar Khetan

Doctoral Dissertations

“Dysregulation of inflammatory pathways is strongly implicated in cancers and autoimmune diseases. The most consequential of these pathways involves the nuclear translocation of NF-kB, a transcription factor that induces the transcription of multiple proteins associated with cell survival, inflammation, proliferation and death. It is activated when the fibroblast growth factor-inducible 14 kDa protein (Fn14), a trimeric receptor recruits its ligand, TWEAK. Studies have shown that Fn14 is over-expressed in many tumors, the aggressiveness of which is often correlated with the degree of upregulation. Furthermore, TWEAK-Fn14 activation has been shown to result in persistent NF-kB activation. Using a mechanistic model of …

Contributions To The Performance Of Thin Film Capacitors For High Reliability Applications, Daniel Krueger

Doctoral Dissertations

"Capacitors are critical devices in microelectronic assemblies that must be incorporated into electronic systems through a variety of ways such as integrated or discrete devices. This work has developed new thin film capacitors deposited directly onto multichip module or printed circuit board surfaces to benefit from closer integration that enhances system performance for use in high reliability applications. The capacitors serve as filters or provide tuning and energy storage functions. Unexpected performance was observed during development that included low adhesion of the films to the substrates, higher effective dielectric constants than reported in literature, and low yields. Three publications resulted …

Development Of Tripodal And Bipodal Ligand Frameworks And First-Row Transition Metal Reagents For Selective C-N Bond Construction Methodologies, Anshika Kalra

Doctoral Dissertations

"We present a family of anionic Mn(II) reagents supported by trisphenylamido- amlne frameworks that offer guidance with regards to ligand selection for developing C—N bond construction methodologies (extensively used in the synthesis of petrochemicals, household chemicals) through nitrene- transfer chemistry. We subsequently extend the study to include the corresponding Fe(II), Co(II), and Ni(II) reagents, to gain insights in their comparative reactivity/selectivity patterns. Attenuated levels of electrophilicity of anionic complexes proved to be more suitable for discriminating aromatic from aliphatic olefins for aziridination purposes, especially for Mn(II) complexes. However, in the case of Co(II) reagents, we observe that additional stereoelectronic parameters …

Proper Orthogonal Decomposition: New Approximation Theory And A New Computational Approach, Sarah Katherine Locke

Doctoral Dissertations

“Proper orthogonal decomposition (POD) projection errors and error bounds for POD reduced order models of partial differential equations have been studied by many. In this research we obtain new results regarding POD data approximation theory and present a new difference quotient (DQ) approach for computing the POD modes of the data.

First, we improve on earlier results concerning POD projection errors by extending to a more general framework that allows for non-orthogonal POD projections and seminorms. We obtain new exact error formulas and convergence results for POD data approximation errors, and also prove new pointwise convergence results and error bounds …

Improving The Data Quality In Gravitation-Wave Detectors By Mitigating Transient Noise Artifacts, Kentaro Mogushi

Doctoral Dissertations

“The existence of gravitational waves (GWs), small perturbations in spacetime produced by accelerating massive objects was first predicted in 1916 as solutions of Einstein’s Theory of General Relativity (Einstein, 1916). Detecting and analyzing GWs produced by sources allows us to probe astrophysical phenomena.

The era of GW astronomy began from the first direct detection of the coalescence of a binary black hole in 2015 by the collaboration of the advanced Laser Interferometer Gravitational-wave Observatory (LIGO) (Aasi et al., 2015) and advanced Virgo (Abbott et al., 2016a). Since 2015, LIGO-Virgo detected about 50 confident transient events of GW signals (Abbott et …

Analysis Of The Primary Volatile Compositions In The Oort Cloud And Jupiter-Family Comets Towards The Goal Of Understanding Their Origin And Diversity, Mohammad Saki

Doctoral Dissertations

“Knowledge of the initial conditions present in the early solar nebula is required to understand the evolution and its current volatile content. Comets were some of the first objects to accrete in the solar nebula. They are among the most pristine (primitive) remnants of the solar system formation, and their present-day volatile composition likely reflects the composition and conditions where (and when) they formed. Therefore, they are fossils of the solar system formation. High-resolution near-infrared spectroscopy is a valuable tool for sampling the parent volatile (i.e., ices subliming directly from the nucleus) composition of comets via analysis of fluorescence emission …

Reveal Wind Loading Of Tornadoes And Hurricanes On Civil Structures Towards Hazard-Resistant Design, Ryan Honerkamp

Doctoral Dissertations

"Extreme winds impacting civil structures lead to death and destruction in all regions of the world. Specifically, tornadoes and hurricanes impact communities with severe devastation. On average, 1200 tornadoes occur in the United States every year. Tornadoes occur predominantly in the Central and Southeastern United States, accounting for an annual $1 billion in economic losses, 1500 injuries, and 90 deaths. The Joplin, MO Tornado in 2011 killed 161 people, injured more than 1000, destroyed more than 8000 structures, and caused $2.8 billion of property loss. Hurricanes occur predominantly on the United States East coast regions and along the coast of …

Computational Studies Of Carbon Nanocluster Solidification, Chathuri Chandani Silva

Doctoral Dissertations

“A subset of micron-size meteoritic carbon particles formed in red giant atmospheres show a core-rim structure, likely condensed from a vapor phase into super-cooled carbon droplets that nucleated graphene sheets (~40Å) on randomly oriented 5-atom loops during solidification, followed by coating with a graphite rim. Similar particles form during slow cooling of carbon vapor in the lab.

Here we investigate the nucleation and growth of carbon rings and graphene sheets using density functional theory (DFT). Our objectives: (1). explore different computational techniques in DFT-VASP for various carbon structures and compare the results with literature, (2). investigate the nucleation and growth …

Information-Based Methods And Models For Particle Flow Filtering, Kari Catherine Ward

Doctoral Dissertations

"Recursive estimation methodologies, such as Kalman and Bayesian filters, typically require models of some kind to perform the estimation. This filtering process seeks to improve knowledge surrounding some quantities of interest, or states, over time by incorporation of imperfect observations. The models required pertain to the state dynamics, sensors from which measurements are obtained, and probabilistic models of the underlying stochastic processes. In addition to any number of necessary models, real-world application of a filter is normally accompanied by at least one, if not several, techniques to promote better performance. These methods vary in purpose from expanding the kinds of …

Mantle Flow Systems Associated With Slab Subduction And Absolute Plate Motion In Alaska Constrained By Shear Wave Splitting Analyses, Yuchen Yang

Doctoral Dissertations

"Alaska has long been recognized as a geologically complex region with a sharp contrast in tectonic activity between southern and northern Alaska. While the former is characterized by the subduction of the geometrically varying Pacific-Yakutat plate beneath the North American plate, the latter has a mostly stable cratonic setting. To investigate the mantle flow fields beneath Alaska and understand the influence of the subduction process on regional mantle dynamics, a total of 2790 pairs of well-defined teleseismic shear wave splitting (SWS) measurements recorded from 379 stations are obtained and analyzed. In addition, 247 pairs of SWS results from local earthquake …

Count Data Time Series Models And Their Applications, Yi Zhang

Doctoral Dissertations

“Due to fast developments of advanced sensors, count data sets have become ubiquitous in many fields. Modeling and forecasting such time series have generated great interest. Modeling can shed light on the behavior of the count series and to see how they are related to other factors such as the environmental conditions under which the data are generated. In this research, three approaches to modeling such count data are proposed.

First, a periodic autoregressive conditional Poisson (PACP) model is proposed as a natural generalization of the autoregressive conditional Poisson (ACP) model. By allowing for cyclical variations in the parameters of …

The Pilot Knob Magnetite, Pilot Knob Hematite, And Shepherd Mountain Iron Oxide Deposits In Southeast Missouri -- Local Expressions Of A Magmatic-Hydrothermal Plumbing System?, Bolorchimeg N. Tunnell

Doctoral Dissertations

“The Southeast Missouri Iron Metallogenic Province in the Midwestern USA contains seven major and several minor IOA/IOCG-type deposits, all of which are spatially associated with the early Mesoproterozoic (1.50-1.44 Ga) magmatism in the St. Francois Mountains terrane. This Ph.D. project focuses on the Pilot Knob deposits, i.e., the deeper largely massive Pilot Knob Magnetite (PKM) and the shallower Pilot Knob Hematite (PKH) deposits, and the Shepherd Mountain deposit that are located less than 2.1 km distance from one another. The first precise age for the formation of the PKM ore is constrained at 1438±5.8 Ma using apatite U-Pb method. Petrographic …

Complete Experiments On Multi-Photon Ionizations Of Ultra-Cold And Polarized Atoms, Bishnu Prasad Acharya

Doctoral Dissertations

“Fundamental atomic processes such as collision-induced ionization are of relevance in many scientific fields. Describing these reactions can still pose a substantial challenge due to the well-known “few-body problem”, which entails that there is no analytical solution of the equations of motion for systems of more the 2 mutually interacting particle. Novel experimental tools and advancements in theorical methods enable to obtain detailed information on atomic dynamics providing insight into both, the phase as well as the amplitude of the quantum-mechanical wave functions of the particles. In this project, we developed experimental techniques studying multi-photon ionization of lithium in femto-second …

Semi-Empirical Modeling Of Liquid Carbon's Containerless Solidification, Philip C. Chrostoski

Doctoral Dissertations

“Elemental carbon has important structural diversity, ranging from nanotubes through graphite to diamond. Previous studies of micron-size core/rim carbon spheres extracted from primitive meteorites suggest they formed around such stars via the solidification of condensed carbon-vapor droplets, followed by gas-to-solid carbon coating to form the graphite rims. Similar core/rim particles result from the slow cooling of carbon vapor in the lab. The long-range carbon bond-order potential was used to computationally study liquid-like carbon in (1.8 g/cm³) periodic boundary (tiled-cube supercell) and containerless (isolated cluster) settings. Relaxations via conjugate-gradient and simulated-annealing nucleation and growth simulations using molecular dynamics were …

Cooperative Navigation Of Small Satellites In The Deep Space Environment, Jill Christine Davis

Doctoral Dissertations

“The continued development of small satellites (SmallSats) has made them an increasingly viable mission alternative to traditional monolithic spacecraft. Constellations, swarms, and formations of these small spacecraft have the potential to fill unique gaps in the space systems architecture, while reducing overall mission costs and increasing mission redundancy. Cooperative navigation between spacecraft within swarms and formations is critical to mission success, but poses many challenges for SmallSats due to their size, mass, power, and computing constraints. While Earth orbiting missions can rely on GNSS data for high-accuracy inertial and relative navigation, deep space missions require new navigation techniques. In this …

Multimodal Neuroscience Data Modeling And Inference, Sima Azizi

Doctoral Dissertations

“Mathematical models can be combined with deep learning and machine learning methods to provide new insights in neuroscience. The field of neuroscience is characterized by rich datasets that include fluid biomarkers, EEG signals, and advanced neuroimages. Recent advances in natural language processing have led to the opportunity to gain additional insights from rapidly growing text databases as well as electronic health records. In this research, we focus on applying computational intelligence methods to the analysis of three different complex data sources: blood levels of disease biomarkers, EEG signals from schizophrenic patients, and disease phenotypes encoded in electronic health records. First, …

Reduced Calibration Uncertainties For The Global Network Of Gravitational-Wave Observatories And The Impact On Sky Localization Of Burst-Like Sources, Dripta Bhattacharjee

Doctoral Dissertations

The Advanced Laser Interferometer Gravitational-wave Observatory (LIGO) is a science facility in the United States devoted to the observation of gravitational waves (GWs). It comprises two kilometer-scale laser interferometers. It is a part of a global ground-based GW detector network that also includes Virgo in Italy and KAGRA in Japan. Calibration of the LIGO detectors is achieved using displacement fiducials generated by radiation pressure based systems called Photon Calibrators (Pcals). The first part of this research described here details the developments implemented during the third LIGO-Virgo-KAGRA (LVK) observation run, O3, in the propagation of laser power calibration via transfer standards …

Mining Haul Road Defect Detection -- Advancement In Automated Road Extent And Response Calibration For Improved Maintenance, Alexander David Douglas

Doctoral Dissertations

Mine haul roads degrade rapidly due to extremely heavy loads on sub optimal construction materials. This research tests two methods of defect detection to determine limitations to current technology: optical detection and vehicle vibration response. Optical defect detection was found to have the least significant limitations for surface defect detection and vehicle vibration response modeling has the least significant limitations for subsurface defects. This research proposes novel methods to eliminate the critical limitations of both technologies.

Unmanned Aerial Vehicles (UAV) equipped with GPS and a high-resolution camera is used to create a 3-D point cloud using a structure-from-motion algorithm. This …

Collaborative Planning In The Construction Industry: A Holistic Framework For Assessing Collaborative Planning Practices And Predicting Project Performance, Amr Elsayegh

Doctoral Dissertations

"The fragmentation of the construction industry prompted developing novel methods such as collaborative planning, lean construction, advancements in technology, integrated project delivery, and relational contracting. Current research focused on specific facets of collaborative planning without presenting a comprehensive analysis of its factors. As such, the goal of this research is to develop a holistic framework that studies and evaluates collaborative planning practices in construction projects. This research offers significant addition to the body of knowledge through various theoretical and practical contributions. In relation to that, this research developed a comprehensive framework by (1) identifying a comprehensive list of factors influencing …

Instrumentation, Modeling, And Sound Metamodeling Foundations For Complex Hybrid Systems, Natasha Amelia Jarus

Doctoral Dissertations

Many of our critical infrastructures, from power grids to water distribution networks, are complex hybrid systems that use software to control their non-trivial physical dynamics. These systems must be able to capably serve their purpose, while also being reliable, dependable, safe, secure, and efficient. Representation and analysis of these features requires the creation of several distinct models. These models may encode design goals or be derived from collected instrumentation data, reflecting both how a system ought to operate and how it does operate. It is essential to ensure that all of these models consistently and accurately describe the same system. …

Relating Detonation Parameters To The Detonation Synthesis Of Nanomaterials, Martin Langenderfer

Doctoral Dissertations

“This research investigates the physical and chemical processes that contribute to the detonation synthesis of silicon carbide nanoparticles. Bulk production of SiC nanoparticles through detonation is possible due to pressures achieved over 20 GPa and temperatures over 2000 K as well as quenching rates in excess of 13 billion K/second. These conditions catalyze reaction and bottom-up molecular growth while retaining particles < 100 nm in diameter. In this work, detonation synthesis of SiC was demonstrated by incorporation of polycarbosilane, an SiC precursor material, into an RDX/TNT explosive matrix prior to detonation. Detonation Synthesis of SiC was also accomplished by reacting elemental silicon with carbon liberated by the detonation of negatively oxygen balanced TNT. Hydrodynamic simulation of a 60:40 mass ratio RDX/TNT detonation created conditions thermodynamically suitable to produce cubic silicon carbide within the first 500 nanoseconds after the passage of the detonation wave while carbon remains chemically reactive for molecular formation. Simulations and experimental tests indicated that loading configuration and impedance mismatch of the precursor additives used in detonation synthesis results in conditions in the additives that exceed the accepted detonation pressure of the explosive by greater than three times. Finally, a full factorial experimental design showed increasing silicon concentration, reducing silicon size, and reducing oxygen balance by adjusting the ratio of RDX to TNT decreased the explosives detonation pressure by 20% and increased the soot yield and concentration of SiC observed in the detonation products by 82% and 442% respectively”--Abstract, page iv.