Digital Commons Network^™

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 …

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.

Dynamic Behavior And Interactions Of Ferrofluid Droplets Under Magnetic Fields In Low Reynolds Number Flows, Md Rifat Hassan

Doctoral Dissertations

Digital microfluidics in combination with emulsion microfluidics are crucial building blocks of droplet-based microfluidics, which are prevalent in a wide variety of industrial and biomedical applications, including polymer processing, food production, drug delivery, inkjet printing, and cell-based assays. Therefore, understanding the dynamics and interactions of droplets as well as the interactions between the droplets and solid surfaces are of great importance in order to improve the performance or product in these applications.

Recently, several studies in the literature have demonstrated the potential of magnetic fields in controlling the behavior of droplets in microscale; however, the fundamental mechanism behind the interesting …

Robustness Against Attacks And Uncertainties In Smart Cyber-Physical Systems, Prithwiraj Roy

Doctoral Dissertations

Cyber-Physical Systems (CPS) are sensing, processing, and communicating platforms, embedded with physical devices that provide real-time monitoring and control. Security challenges in CPS necessitate solutions that are robust against attacks and uncertainties and provide a seamless operation, especially when used in real-time applications to monitor and secure critical infrastructures. CPS mainly consists of a physical component for sensing or monitoring and a cyber component for processing and communicating. The quality of interactions between physical and cyber systems has direct impacts on the system’s performance and reliability.

CPS plays a major role in smart services and applications within a smart living …

Identification Of Neuromarkers Using Structural And Functional Neuroimaging, Sreevalsan Sanathanan Menon

Doctoral Dissertations

"One of the grand challenges in science is understanding the human brain. Recent advances in magnetic resonance imaging have opened unmatched opportunities to demystify neural circuitry. In this research, the spatially and temporally complex neuroimaging data were used to identify neuromarkers that aids in quantifying a brain’s health. In the first part, a comparison of static and dynamic functional connectivities was made to study their efficacies in identifying intrinsic individual connectivity patterns. Results show that the intrinsic individual connectivity pattern can be used as a ‘fingerprint’ to distinguish among and identify subjects and their biological sex and is more accurately …

Advanced Battery Modeling For Interfacial Phenomena And Optimal Charging, Yaqi Zhu

Doctoral Dissertations

"Lithium-ion batteries are one of the most promising energy storage systems for portable devices, transportation, and renewable grids. To meet the increasing requirements of these applications, higher energy density and areal capacity, long cycle life, fast charging rate and enhanced safety for lithium-ion battery (LIBs) are urgently needed. To solve these challenges, the relevant physics at different length scale need to be understood. However, experimental study is time consuming and limited in small scale’s study. Modeling techniques provide us powerful tools to get a deep understanding of the relevant physics and find optimal solutions. This work focuses on studying the …

Infrastructure Systems Modeling Using Data Visualization And Trend Extraction, Jacob Marshal Hale

Doctoral Dissertations

“Current infrastructure systems modeling literature lacks frameworks that integrate data visualization and trend extraction needed for complex systems decision making and planning. Critical infrastructures such as transportation and energy systems contain interdependencies that cannot be properly characterized without considering data visualization and trend extraction.

This dissertation presents two case analyses to showcase the effectiveness and improvements that can be made using these techniques. Case one examines flood management and mitigation of disruption impacts using geospatial characteristics as part of data visualization. Case two incorporates trend analysis and sustainability assessment into energy portfolio transitions.

Four distinct contributions are made in this …

Innovative Modeling And Management Of Infrastructure Systems, Engineering And Construction Operations, And Offsite Construction Technology Using Computational Data Analytics, Rayan Hassane Assaad

Doctoral Dissertations

“The construction industry has been facing considerable challenges due to the inadequacy of the traditional methods in executing, managing, and modeling infrastructure and construction projects. While many techniques have been developed to improve the decision-making process in the industry, there is no evidence of sufficient and continuous improvements in the industry’s adoption and implementation of innovative techniques such as new management approaches, modern modeling methods, and emerging computational data analytics. To this end, the goal of this research is to address some of the recent challenges faced in the industry with a focus on infrastructure asset management, construction engineering and …

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 …

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 …

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 …

Spatial Variations Of Teleseismic P-Wave Attenuation And Scattering Beneath The Southeastern United States And The Malawi And Luangwa Rift Zones In East Africa, Ashutosh Shrivastava

Doctoral Dissertations

"Seismic attenuation is an important physical parameter for characterizing subsurface morphology and the thermal structure of the Earth’s crust and mantle. In this study, teleseismic P-wave amplitude spectra are used to examine the seismic attenuation beneath the southeastern United States and the Malawi and Luangwa rift zones in east African. The resulting seismic attenuation parameters (Δt*) reveal a systematic contrast between the Appalachian Mountains and the Gulf of Mexico Coastal Plain exhibiting high and low attenuation, respectively. Spatial coherency analysis of the Δt* observations suggests that the center of the low-attenuation layer is located within the uppermost mantle at about …

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 …

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 …

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 …

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 …

Swill-Tac: Skill-Oriented Dynamic Task Allocation With Willingness For Complex Job In Crowdsourcing, Riya Samanta, Soumya K. Ghosh, Sajal K. Das

Computer Science Faculty Research & Creative Works

Allocating tasks to the best-fit candidates is a classical problem in crowdsourcing (CS). Most of the existing approaches assume that the task and candidate knowledge is known in advance and ignore the effect of enrolled candidates' willingness on the CS system's selection decision. For instance, an unwilling candidate assigned to a task may quit without completing it, thus depreciating the utility of the CS platform. In practice, a task or candidate may arrive or leave the CS system dynamically. Moreover, a complex task may be broken into smaller sub-tasks, each requiring a variety of computations and expertise. To overcome these …

Your 'Attention' Deserves Attention: A Self-Diversified Multi-Channel Attention For Facial Action Analysis, Xiaotian Li, Zhihua Li, Huiyuan Yang, Geran Zhao, Lijun Yin

Computer Science Faculty Research & Creative Works

Visual attention has been extensively studied for learning fine-grained features in both facial expression recognition (FER) and Action Unit (AU) detection. A broad range of previous research has explored how to use attention modules to localize detailed facial parts (e, g. facial action units), learn discriminative features, and learn inter-class correlation. However, few related works pay attention to the robustness of the attention module itself. Through experiments, we found neural attention maps initialized with different feature maps yield diverse representations when learning to attend the identical Region of Interest (ROI). In other words, similar to general feature learning, the representational …

Critical Behavior In Evolutionary And Population Dynamics, Stephen Walter Ordway

Doctoral Dissertations

“This study is an exploration of phase transition behavior in evolutionary and population dynamics, and techniques for predicting population changes, across the disciplines of physics, biology, and computer science. Under the looming threat of climate change, it is imperative to understand the dynamics of populations under environmental stress and to identify early warning signals of population decline. These issues are explored here in (1) a computational model of evolutionary dynamics, (2) an experimental system of decaying populations under environmental stress, and (3) a machine learning approach to predict population changes based on environmental factors. Through the lens of critical phase …

Optimal Bidding Strategy For Physical Market Participants With Virtual Bidding Capability In Day-Ahead Electricity Markets, Hossein Mehdipourpicha, Rui Bo

Electrical and Computer Engineering Faculty Research & Creative Works

Virtual bidding provides a mechanism for financial players to participate in wholesale day-ahead (DA) electricity markets. The price difference between DA and real-time (RT) markets creates financial arbitrage opportunities for financial players. Physical market participants (MP), referred to as participants with physical assets, can also take advantage of virtual bidding but in a different way, which is to further amplify the value of their physical assets. Therefore, this work proposes a model for such physical MPs to maximize the profits. This model employs a bi-level optimization approach, where the upper-level subproblem maximizes the total profit from both physical generations and …

Values Of Trust In Ai In Autonomous Driving Vehicles, Ru Lian

Masters Theses

“Automation with artificial intelligence technology is an emerging field and is widely used in various industries. With the increasing autonomy, learning, and adaptability of intelligent machines such as self-driving cars, it is difficult to regard them as simple tools in human hands. At the same time, a series of problems and challenges such as predictability, interpretability, and causality arise. Trust in self-driving technology will impact the adoption and utilization of autonomous driving technology. A qualitative research methodology, Value-Focused Thinking, is used to identify the values of trust in autonomous driving vehicles and analyze the relationship between these values”--Abstract, page iii.

Projectile Generator Design For Underground Coal Mine Seal Testing, Ethan Allan Steward

Masters Theses

"Underground coal mines have several dangers, one of the most hazardous of which is the possibility of an explosion caused by the ignition of methane gas. To reduce ventilation costs, coal mines have the option to close off abandoned areas that are no longer active with structural seals to keep an explosion from propagating into working areas of the mine. Though seals have been designed to resist the overpressure, none have been evaluated for their resistance to the impact of heavy objects. Underground explosions produce high velocity gasses that, traveling through mine openings, may propel objects in the mine at …

Airbnbs In The Rural Midwest: Optimizing Listing Content For User’S Decision-Making Processes, Mary Catherine Kosacki

Masters Theses

This research examines the effectiveness of rural Airbnb listing content in influencing user decision-making. The peer-to-peer economy has been rapidly growing over the past decade, providing new opportunities for individuals to offer goods and services to other individuals through corporate platforms. Specifically, the Airbnb platform has rapidly grown, becoming the largest online platform for peer-to-peer property rentals, and one of the largest companies in the peer-to-peer sector of the economy. Previous research on the Airbnb platform has focused primarily on urban areas; however, Airbnbs have a proportionally large impact on local economies in rural areas.

Several methods were employed to …

Biochemical Assay Invariant Attestation For The Security Of Cyber-Physical Digital Microfluidic Biochips, Fredrick Eugene Love Ii

Masters Theses

“Due to the devastating global impact that infectious diseases have had, especially in developing countries, the demand for access to adequate resources to combat sickness continues to be a heavy burden. Reliable and affordable diagnostics is a vital first line of defense in fighting outbreaks and providing accurate treatment. Digital microfluidics biochips capable of running multiple diagnostic tests on a single platform are an emerging technology that are increasingly being evaluated as a viable platform for rapid diagnosis and point-of-care field deployment. Although these systems offer many benefits, processing errors are inherent. Therefore, cyber-physical digital biochips are being investigated that …

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. …

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

INSPIRE Newsletters

No abstract provided.

Fabrication, Characterization And Environmental Monitoring Of Polymer-Based Materials For Biomedical And Structural Applications, Mousumi Bose

Doctoral Dissertations

"Polymers are versatile materials utilized for variety of applications. In biomedical field, luminescence quenching based optical oxygen sensors encapsulated in polymeric substances are gaining attention for early detection of surface wounds associated with tissue oxygen. A simple and low-cost fabrication technique was developed to produce sensor arrays for continuous two-dimensional oxygen tension measurement. Sensor patch along with smart phone-based readout technique is being evaluated as a smart bandage.

The environmental concerns and limited petroleum supply demand for replacing petroleum-based polymers with renewable bio-based sources while maintaining comparable properties. A sustainable and green approach was adopted to synthesize soy polyol-derived rigid …

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 …

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 …