Digital Commons Network^™

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 …

Pdn Modeling For High-Speed Multilayer Pcb Boards And Decap Optimization Using Machine Learning Techniques, Ling Zhang

Doctoral Dissertations

"In power distribution networks (PDN), there are two main challenges nowadays. One challenge is how to efficiently model and calculate the impedance for arbitrary-shape and multi-layer PDN systems. The second challenge is the optimization of decoupling capacitors in the pre-layout stage. This dissertation proposes novel solutions to these two challenges. To tackle the first challenge, a boundary element method (BEM) is utilized to calculate the quasi-static inductances between vertical vias for arbitrary-shape planes. Then a specialized circuit solver is developed to solve the equivalent circuit of inductances and capacitances for multi-layer PDN structures. Also, a contour integral method (CIM) is …

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 …

Quantum Inspired Concepts In Decision Making, Qizi Zhang

Doctoral Dissertations

"In this study, several new applications of quantum-inspired techniques are presented to advance the state of the art in decision making. In the first part, a quantum boost scheme for multiple-model filters based on extended Grover’s algorithm is presented for fault detection and parameter estimation. The quantum boost scheme accelerates the convergence of the posterior probabilities in the multiple-model filter. Stability proofs for the quantum boost scheme is presented and its performance is analyzed using benchmark examples. In the second part, the scope of application is extended to modeling human decision making. The open quantum system cognition model is applied …

Receiver Function Imaging Of The 410 And 660 Km Discontinuities And Seismic Azimuthal Anisotropy Revealed By Shear Wave Splitting Beneath The Australian Continent, Kailun Ba

Doctoral Dissertations

"The Australian continent is composed the of Precambrian cratons in the west and Phanerozolc orogens in the east. Despite numerous seismological studies, controversies remain regarding the structure, evolution, and dynamics of the crust and mantle beneath Australia. In this study, we used two techniques, receiver functions and shear wave splitting analyses, to investigate the topography of the mantle transition zone (MTZ) discontinuities and mantle seismic azimuthal anisotropy, respectively. We utilized P-to-S receiver functions to map the 410 and 660 km discontinuities bordering the MTZ. The discontinuity depths obtained show a systematic apparent uplifting for both discontinuities in central and western …

Novel Transformer With Variable Leakage And Magnetizing Inductances, Angshuman Sharma, Jonathan W. Kimball

Electrical and Computer Engineering Faculty Research & Creative Works

This paper introduces the concept of a novel variable inductance transformer (VIT) whose leakage and magnetizing inductances can be varied dynamically and independently to aid the advancement of research in isolated power electronic converters. In this transformer, the leakage inductance can be varied by varying the length of overlap between the primary and secondary windings, while the magnetizing inductance can be varied by varying the air gap between the core legs. Individual controls for the two inductances ensure that one can be varied independent of the other, as needed to satisfy different power conversion objectives. In this paper, the analytical …

Using Gated Recurrent Units For Selective Harmonic Current Mitigation-Pwm In Grid-Tied Cascaded H-Bridge Converters, Morteza Dabbaghjamanesh, Amirhossein Moeini, Jonathan Kimball, Jie Zhang

Electrical and Computer Engineering Faculty Research & Creative Works

Grid-tied converters become more popular for electric vehicle, renewable energy, and energy storage systems applications. Different modulation techniques such as low-frequency (e.g., selective harmonic elimination-PWM, selective harmonic mitigation-PWM, and selective harmonic current mitigation-PWM (SHCM-PWM)) and high-frequency modulation techniques (e.g., phase shift-PWM and space vector modulation) are used in the literature for grid-tied converters. Low-frequency modulation techniques have a high-efficiency due to the low-switching power losses. One of the main challenges of low-frequency modulation techniques such as SHCM-PWM is how to implement the proposed technique in real-time, due to the transcendental Fourier equations of SHCM-PWM. In this paper, a deep learning …

A Time-Domain Computing-In-Memory Micro Using Ring Oscillator, Yixuan He, Minsu Choi, Kyung Ki Kim, Yong Bin Kim

Electrical and Computer Engineering Faculty Research & Creative Works

This paper proposes a novel time-domain computing-in-memory core that implements XNOR-And-Accumulate (XAC) of XNOR network in 8T SRAM cell. This new technique uses an inverter-based ring oscillator to generate periodic waves whose period represents the accumulation result of the input XNOR values. The circuit is built and simulated using PTM16_HP 16nm CMOS model with a 0.7V power supply. The results show correct functionality, a large signal margin and 463 TOPS/W efficiency. With further exploration, the time-domain computation could be a new candidate for in-memory computing since it has its own superiorities in comparison to mixed-signal or digital methods.

Investigation Of Post-Acid Stimulation Impacts On Well Performance Using Fracture Modeling And Reservoir Simulation In A Jurassic Carbonate Reservoir, Muaath Alansari

Masters Theses

"Well stimulation (well fracturing) became an essential tool in the Oil and Gas industry to unlock the potential of unconventional reservoirs all over the world and especially in the Middle East. In Kuwait, well stimulation is obligatory when dealing with deep Jurassic carbonate reservoirs. Thus, the well fracture designing process plays a very critical role in determining the success of the stimulation job and the improvement of the recovery.

Several wells stimulated with 20% HCL have shown wide variations in both short and long term well production performance. The research aims to investigate and identify the possible reasons causing these …

Development Of Complex Lattice Cell In Benchmark Model Of Particle Bed Critical System, Elijah Chamberlain Lutz

Masters Theses

“Criticality safety benchmark evaluations require the creation of models that most accurately represent the experiment being evaluated. In some cases this can be relatively trivial with experiments containing rather simple or standard geometry. In others, such as packed bed systems, this becomes unique and a more difficult process. The importance of accurate modeling of packed bed systems for the use of criticality safety benchmark evaluations was looked at. Four models were created of various complexities and accuracy. First the multi-particle bed, consisting of a fuel particle (UC_1.7 kernel with C shell) and two filler particles (Zircaloy-4 and C + …

Multiple-Site Fatigue Cracking Methodology To Assess Structural Integrity Of Aircraft Riveted Panels, Haroldo Chacon

Masters Theses

“Multiple Site Damage (MSD) is the most common source of Widespread Fatigue Damage (WFD) affecting structural integrity of aging aircraft fleets. Therefore, an understanding of its progression, the development of methods to prevent the onset, and the maintenance procedures precluding WFD are important to improve aircraft fleet longevity. A reliable and efficient numerical methodology to perform detailed Multiple Site Damage assessment in riveted structural joints was developed. A probabilistic methodology was employed in conjunction with Monte Carlo simulation technique; the fatigue initiation life at every potential crack initiation site was determined and initial damage scenarios were generated. Probabilistic crack growth …

Neural Network Supervised And Reinforcement Learning For Neurological, Diagnostic, And Modeling Problems, Donald Wunsch Iii

Masters Theses

“As the medical world becomes increasingly intertwined with the tech sphere, machine learning on medical datasets and mathematical models becomes an attractive application. This research looks at the predictive capabilities of neural networks and other machine learning algorithms, and assesses the validity of several feature selection strategies to reduce the negative effects of high dataset dimensionality. Our results indicate that several feature selection methods can maintain high validation and test accuracy on classification tasks, with neural networks performing best, for both single class and multi-class classification applications. This research also evaluates a proof-of-concept application of a deep-Q-learning network (DQN) to …

Factors Affecting Covid-19 Pandemic, Linrui Han

Masters Theses

“COVID-19 has affected our daily lives in many aspects, such as work, healthcare, education, business, and social. With the quick spread of this new coronavirus, many countries quickly fell into a pandemic control and management mode. It has been more than one year since the discovery of COVID-19, but until now, COVID-19 is still affecting our lives and our daily operations. The research consists of two papers focusing on different factors affecting the COVID-19 pandemic. The first paper studies the effect of ICT and healthcare expenditures on the COVID-19 management and control. The second paper focuses on the impact of …

Variational Inference For Morphological Modification To 3d Geometry : An Application To The Support Generation For Metal Additive Manufacturing, Mugdha Swanand Joshi

Masters Theses

"A key issue in metal additive manufacturing (AM) processes is the optimization of support geometry. Correct selection of support strategy can reduce build time, improve surface finish, reduce support removal time, and maximize build success. Strategies used to design support structure are time consuming and need skilled personnel. In this research we have deployed a deep generative model capable of making morphological modifications to the part. However, it is not similar to topology optimization where the aim is to reduce or eliminate support structure. The proposed model can make necessary changes to the part in order to transform it into …

Design And Development Of A Variable Resistance Hand Exerciser Using A Compliant Mechanism, Jyothi Komatireddy

Masters Theses

"Rehabilitation exercise plays a vital role in recovering from an injury or illness condition by improving flexibility and restoring muscle strength. If not done correctly, exercising can cause more damage to the health condition than in healing. Understanding the muscle’s resistance level while performing an exercise helps design the exercising equipment not to overstrain the muscle during operation. This research presents a methodology to develop a variable-resistance hand exerciser by using a compliant cam-follower mechanism. The proposed design comprised a compliant follower and a rigid cam. The rigid cam is synthesized using the human hand force-deflection profile as an input …

Quality-Of-Service Architecture For Cloud Computing Networking, Ken R. Owens Jr., Steve Eugene Watkins

Electrical and Computer Engineering Faculty Research & Creative Works

Quality-of-service (QoS) performance is an important consideration for real-time and high-priority traffic on internet protocol (IP) networks. Service differentiation can provide a more efficient and customer-oriented internet. The “best-effort” internet models in use today cannot provide guarantees or service differentiation for end-to-end individual and aggregate data flows. Hardware-based models and software-based models do not completely address the total service-enabled solution. We propose a hybrid architecture that combines software and hardware features to handle network traffic with diverse QoS requirements. Since cloud providers leverage IP networks today, the model is based on a systems engineering approach that uses cloud computing technologies. …

A Simulation Model For Optimal Bidding Decisions, Rayan H. Assaad, Muaz O. Ahmed, Islam H. El-Adaway, Amr Elsayegh

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

The lowest bid approach is the most used technique in the US construction procurement environment since competitive bidding is a legal requirement in the public sector. Despite that many research studies were directed to help contractors in taking different bidding decisions, there is still insufficient research efforts that equipped contractors with decision-support tools to decide on optimal bid values. Hence, this paper takes previous research works a step further by developing a simulation model that can be adopted to determine the bid decision that would result in winning more projects. To this end, a methodology composed of multiple steps was …

Aerothermal Uncertainty Quantification Of Deployable Entry Technologies Using Multi-Fidelity Modeling, Mario Santos, Serhat Hosder, Thomas K. West

Mechanical and Aerospace Engineering Faculty Research & Creative Works

The objective of this work was to investigate the use of a co-Kriging based multi-fidelity modeling approach with a Monte Carlo uncertainty quantification analyses of surface heating on hypersonic inflatable aerodynamic decelerator vehicles and adaptable, deployable entry placement technology vehicles in Mars entry. A previously developed co-Kriging based multi-fidelity modeling approach was used to model the laminar and turbulent convective and radiative heat fluxes along the vehicle. Monte Carlo analyses of surface heat load for nine different vehicle nose radii was performed for both vehicles, assuming the same thermal protection system is used for both vehicles. The maximum heat loads …

A Convolutional Neural Network Model Based On Multiscale Structural Similarity For The Prediction Of Flow Fields, Yifu An, Xiaosong Du, Joaquim R.R.A. Martins

Mechanical and Aerospace Engineering Faculty Research & Creative Works

We have seen the emerging applications of deep neural networks for flow field predictions in the past few years. Most of the efforts rely on the increased complexity of the model itself or take advantage of novel network architectures, such as convolutional neural networks (CNN). However, reaching low prediction error cannot guarantee the quality of the predicted flow fields in terms of the perceived visual quality. This work introduces the multi-scale structural similarity (MS-SSIM) index method for flow field prediction. First, we train CNN models using the commonly used root mean squared error (RMSE) loss function as the reference. Then …

Prediction Of Equivalent Liquid Permeability From Gas Permeability Measurements: A Recurrent Neural Network Approach, Husam Alkinani, Abo Taleb Al-Hameedi, Shari Dunn-Norman

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

One of the most vital reservoir properties is permeability. It is usually measured using core samples with two major measurement methods: using gas or using liquid. The purpose of this work is to use a data-driven recurrent neural network model to estimate the equivalent liquid permeability based on gas permeability. By using this model, the equivalent liquid permeability can be predicted for the permeability of core samples with rich clay minerals measured using gas (or any core sample that is measured using gas). This will give an alternative way to the currently used method (Klinkenberg method). Core sample data measurements …

Minimizing Lost Circulation Non-Productive Time Using Expected Monetary Value And Decision Tree Analysis, Husam Hasan Alkinani, Abo Taleb Tuama Al-Hameedi, Shari Dunn-Norman

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Lost circulation and problems related to drilling present a major challenge for the drilling industry. Each year, billions are spent to treat these problems. There is not a single solution to lost circulation because of the complexity and kind of formations susceptible to this issue. Lost circulation treatment data for the Shuaiba formation (induced fractured formation) were gathered from drilled wells in Southern Iraq (over 2000). Treatments have been grouped according to the volume of mud loss as complete, severe, and partial loss remedies. Detailed costs and probabilities calculations were conducted. The costs of three types of loss treatments (partial, …

Impact Of Rheology Models On Horizontal Well Polymer Flooding In A Heavy Oil Reservoir On Alaska North Slope: A Simulation Study, Jianqiao Leng, Mingzhen Wei, Baojun Bai, Randall S. Seright, Yin Zhang, David Cercone, Samson Ning

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Polymer rheology can have either a positive or a negative effect on polymer flooding performance under varied circumstances. Many researchers have studied the effect of polymer rheology in a vertical well, but no field scale studies have been conducted to investigate whether polymer rheology is beneficial to polymer flooding in heavy oil reservoirs developed by horizontal wells. In this paper, we conducted a numerical simulation study to examine the effect of HPAM polymer rheology on a polymer flooding pilot, which is the first-ever project conducted on a heavy oil reservoir from Alaska North Slope (ANS) developed by horizontal wells. Three …

First Ever Polymer Flood Field Pilot To Enhance The Recovery Of Heavy Oils On Alaska's North Slope Pushing Ahead One Year Later, Abhijit Dandekar, Baojun Bai, John Barnes, Dave Cercone, Jared Ciferno, Reid Edwards, Samson Ning, Walbert Schulpen, Randy Seright, Brent Sheets, Dongmei Wang, Yin Zhang

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

In June 2018 the team embarked on an ambitious project to address the slow development pace of Alaska's 20+ billion barrels heavy oil resource via the first ever polymer flood pilot. Following the successful commencement of the pilot in August 2018, the field demonstration, supporting laboratory experiments and numerical simulation have steadily progressed. A significant amount of valuable data and lessons learned have been collected and are reported in this paper. The ongoing pilot and the research activities is making headway toward the primary objective of validating the use of polymer flooding for extracting heavy oil in Alaska's challenging environment. …

Efficient Route Selection For Drone-Based Delivery Under Time-Varying Dynamics, Arindam Khanda, Federico Coro, Francesco Betti Sorbelli, Cristina M. Pinotti, Sajal K. Das

Computer Science Faculty Research & Creative Works

The use of drones can be a valuable solution for the problem of delivering goods for many reasons. In fact, they can be efficiently employed in time-critical situations when there is a traffic jam on the roads, to serve customers in hard-to-reach places, or simply to expand the business. However, due to limited battery capacities and the fact that drones can serve a single customer at a time, a drone-based delivery system (DBDS) aims to minimize the drones' energy usage for completing a route from the depot to the customer and go back to the depot for new deliveries. In …

Inspire Newsletter Fall 2021, Missouri University Of Science And Technology. Inspire - University Transportation Center

INSPIRE Newsletters

No abstract provided.

An Experimental Study Investigating The Impact Of Miscible And Immiscible Nitrogen Injection On Asphaltene Instability In Nano Shale Pore Structure, Mukhtar Elturki, Abdulmohsin Imqam

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Miscible gas injection has become the most used enhanced oil recovery (EOR) method in the oil and gas industry. The deposition and precipitation of asphaltene during the gas injection process is one of the problems during the oil production process. The asphaltene can deposit and plug the pores, which reduces the permeability in a reservoir; thus, decreasing the oil recovery and increasing the production costs. This research investigates the nitrogen (N2) miscible and immiscible pressure injections on asphaltene instability in shale pore structures. First, a slim tube was used to determine the minimum miscibility pressure (MMP) of N2 to ensure …

Will Carbon Dioxide Injection In Shale Reservoirs Produce From The Shale Matrix, Natural Fractures, Or Hydraulic Fractures?, Sherif Fakher, Youssef Elgahawy, Hesham Abdelaal, Abdulmohsin Imqam

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Enhanced oil recovery (EOR) in shale reservoirs has been recently shown to increase oil recovery significantly from this unconventional oil and gas source. One of the most studied EOR methods in shale reservoirs is gas injection, with a focus on carbon Dioxide (CO₂) mainly due to the ability to both enhance oil recovery and store the CO₂ in the formation. Even though several shale plays have reported an increase in oil recovery using CO₂ injection, in some cases this method failed severely. This research attempts to investigate the ability of the CO₂ to mobilize crude …

Protection Of Modern Distribution Systems, Fahd Amin Hariri

Doctoral Dissertations

“Motivated by the potential for improvements in the electric distribution system’s protection schemes, this work examined the challenges facing protection schemes due to the integration of Distributed Generators (DGs). Traditional protection schemes for radial distribution systems were designed based on the unidirectional power flow from the source down to the loads. Protective devices typically use are overcurrent relays, autoreclosers, fuses, and circuit breakers. However, these protective schemes may no longer be sufficient to ensure correct operation in the new era of distribution systems integrated by DGs. This research investigated the impact of DGs that might mislead the protection schemes 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 …