WorldCat Identities

University of Georgia College of Engineering

Overview
Works: 76 works in 77 publications in 1 language and 80 library holdings
Genres: Academic theses 
Classifications: HD8039.T7,
Publication Timeline
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Most widely held works by University of Georgia
2016 Georgia Department of Transportation employee survey results by University of Georgia( Book )

2 editions published in 2017 in English and held by 5 WorldCat member libraries worldwide

Single-cell analysis on the biological clock using microfluidic droplets by Zhaojie Deng( )

1 edition published in 2017 in English and held by 1 WorldCat member library worldwide

Single-cell analysis has become crucial for uncovering the underlying mechanism for cell heterogeneity. Different biological questions pose different challenges for single-cell analysis. In order to answer questions like, whether a single-cell has a biological clock and how the clocks synchronize among cells to overcome the heterogeneity, continuous long-term measurement on large numbers of single-cells is required. However traditional measurement techniques usually involve measurement on millions of cells. My dissertation addresses these challenges by developing a microfluidic droplet platform capable of measuring the biological clock on>1000 Neurospora crassa single-cells for up to 10 days. The results show that in Neurospora crassa a single cell has the three major properties of a biological clock: a circadian oscillator, light entertainment, and temperature compensation and that single-cells synchronize their biological clock with each other possibly through quorum sensing
Exploring novel inorganic antimicrobial nanostructures : synthesis, characterization, and properties by Lu Zhu( )

1 edition published in 2018 in English and held by 1 WorldCat member library worldwide

A study on self-assembly and structural analysis of protofilaments by Divya Jakkam( )

1 edition published in 2018 in English and held by 1 WorldCat member library worldwide

Microtubules are polymers made of the protein tubulin and play a significant role in various cell functions as they are present in the cytoskeleton of most eukaryotic cells. They have a highly dynamic structure and are formed by the self assembly of the protein tubulin, with the aid of different microtubule associated proteins. Self-assembly is the formation of an organized structure from a series of processes. In this thesis, we seek to observe the formation of a pattern when spherical units which are assumed as tubulins are excited externally by an electrodynamic exciter. The angles of contact which are determined from these experimental results are compared with simulations in virtual reality using a game engine software called Unity. We perform a mechanical structural analysis on the protofilaments, based on the configurations derived from experiments, and study the relationship between different stresses and strains and also, study the variation of stresses relative to the curvature in the protofilament. The mode shapes of these protofilaments are also studied by performing a free-free modal vibrational analysis
A precision UV-Wet chemical oxidation dissolved organic carbon analyzer by Yuxi Liao( )

1 edition published in 2017 in English and held by 1 WorldCat member library worldwide

This study is aimed at the development of a high-precision (sub-Molar) dissolved organic carbon (DOC) analyzer for aquatic samples. The prototype analyzer uses ultraviolet and wet chemical oxidation (UV-WCO) aided with heat to oxidize DOC contents in samples. The oxidized DOC in the form of CO2 is sparged from the solution at a defined flow rate and can be precisely determined through the use of a non-dispersive infrared (NDIR) gas analyzer. This prototype aims to improve on existing instruments by having sub-uM precision, near-continuous sample injection, and compatibility with analysis on board ships. It has potential applications for studies of DOC consumption and production by various mechanisms including but not limited to microbial respiration/carbon fixation, photochemical oxidation, and the mixing of water masses. The prototype was constructed and optimized to improve oxidation efficiency and precision. This prototype did not meet the sub-uM goal due to several factors affecting oxidation efficiency and signal stability. If the stability issues can be addressed and oxidation efficiency increased to 100% the desired precision could be achieved
Assessing water body ecological indicators using time series analysis and physics-based modeling approaches. by Natalia Valeryevna Bhattacharjee( )

1 edition published in 2017 in English and held by 1 WorldCat member library worldwide

This dissertation goal is to present a comprehensive time series analysis along with a physics-based model of a stream that can yield expanded ecological data over time which can be further studied with time series analysis. The time series component was primarily developed using available data from a windrow composting operation and runoff collection pond. Descriptive time series analysis (spectral analysis) and detailed recurrent neural network modeling (which requires training and validation data) were performed. Physical stream models and subsequent environmental flow analysis models were developed as aids for water resource management in the Ocmulgee and the Middle Oconee Rivers where we develop a platform useful for evaluating trade-offs between ecological impacts and economic development. We then selected one of the four environmental flow conditions for time series analysis. The methodology and approach set in this work may be adapted to inform environmental flow analyses in other study sites
Coupled fluid models of smoothed particle hydrodynamics and finite difference method for simulating dynamic penguin huddles by Wen Gu( )

1 edition published in 2018 in English and held by 1 WorldCat member library worldwide

A coupled numeric model of finite difference method (FDM) and smoothed particle hydrodynamic (SPH) is utilized for the simulation of dynamic penguin huddles. In this coupled fluid model, the full Navier-Stokes equations are used to solve a wind field using a finite difference method and simultaneously model penguin huddling through a smoothed particle hydrodynamics method. The FDM method is a common Eulerian numerical approach based on application of a local Taylor expansion and is used to estimate wind flowing in two dimensions around complex and dynamic huddle shape on a rectangular computational grid. The SPH method is a mesh-free Lagrangian method driven by local interactions between neighboring fluid particles and their environment allowing particles to act as free ranging "penguins" unconstrained by a computational grid. These coupled fluid numerical models are recomputed simultaneously as the huddle evolves over time to update individual particle positions, redefine the fluid properties of the developing huddle (i.e., shape and density), and redefine the wind field flowing through and around the dynamic huddle. This study shows the ability of a coupled model to predict the dynamic properties of penguin huddles, to quantify biometrics of individual particle "penguins" and to attempt an explanation of communal penguin huddling behavior as observed in nature
Impact performance of recycled tire chip and fiber reinforced cementitious composites for use in concrete by Victor Lopez( )

1 edition published in 2018 in English and held by 1 WorldCat member library worldwide

The ultimate aim of this study was to maximize the energy dissipation capacity of rubberized fiber reinforced concrete (FRC) mixtures subjected to impact forces for the purpose of improving the impact resilience of GDOT safety barriers and other applications. The first part of this study involved small-scale testing of preliminary mixtures to optimize compressive strength, modulus of rupture, and impact resilience using a fixed percentage of tire chip replacement of the coarse aggregate and varying volume fractions of steel, polypropylene, and polyvinyl alcohol fibers. Rubberized FRC beams were then tested under static loads to maximize the static energy dissipation potential of steel fiber inclusion at varying tensile steel reinforcement ratios. The final part of this study involved performing scaled drop-weight impact tests and results confirmed that rubberized FRCs exhibit significantly improved energy dissipation capacity and impact resilience, particularly with 1.0% steel fiber addition and 20% tire chip replacement
Evaluation of the Nest Learning thermostat in a multifamily apartment setting by Christopher J McHugh( )

1 edition published in 2017 in English and held by 1 WorldCat member library worldwide

Since 2011, the Nest Learning thermostat, utilizing proprietary occupancy scheduling algorithms and sensors, has transformed the residential and small-commercial programmable thermostat market into a smart thermostat market. Due to usability and design challenges, a majority of people who have programmable thermostats do not properly operate them, often times leading to lower potential energy savings and even higher energy consumption than conventional non-programmable thermostats. Compared to previous thermostats however, the Nest thermostat is designed to learn its occupants' schedules and develop a heating and cooling schedule to best meet its occupants' thermal comfort needs, bridging the usability and functionality gap that exists with previous programmable thermostats. While most thermostat research is focused on single family homes, this study was conducted using a multifamily apartment complex, where occupants were not responsible for their bills. This study emphasizes the importance of using smart thermostats correctly to realize expected energy savings, and how even a "smart" thermostat can fail to save energy if its features are not used
The relationship between cooling temperature setpoints and building energy consumption : a case study at the University of Georgia by Tara Nicole Sharpton( )

1 edition published in 2019 in English and held by 1 WorldCat member library worldwide

Buildings account for roughly 40% of total energy consumption in the U.S. and roughly half of this is for indoor space cooling and heating. Anthropogenic greenhouse gas emissions (GHGs) are becoming a rising concern due to the onset of climate change and global warming. In order to mitigate against GHGs, namely CO2, the impact of effective cooling temperature setpoint increase on building energy consumption is explored. The corresponding impact on utility costs, emissions, and thermal comfort is determined. Results found that increasing cooling temperature setpoints to Results found that increaing cooling temperature setpoints to 74F (23.3°C) and 76F (24.4°C) from normal operating conditions of 73°F (22.8°C)during the cooling season can reduce chilled water consumption for space cooling at representative campus buildings by 19% to 40% respectively. This emphasizes the large opportunity that exists in temperature setpoint control to improve energy efficiency of buildings and mitigate CO2 emissions that occur from energy consumption by buildings
Effects of asphalt mixture characteristics on dynamic modulus and fatigue performance by Robert Austin Etheridge( )

1 edition published in 2018 in English and held by 1 WorldCat member library worldwide

This thesis presents results from an experimental study on the dynamic modulus and fatigue testing of hot mix asphalts (HMA) commonly used in Georgia. Seventeen mixtures with varying aggregate sources, gradations, binder types, and asphalt contents were used to 1) expand the Georgia department of transportation's (GDOT) material input library for dynamic modulus and 2) recommend a test method that predicts realistic strain levels and better fatigue cracking prediction for fatigue performance. The effects of HMA mixture properties on dynamic modulus testing indicate that gradation, binder type, and reclaimed asphalt pavement (RAP) greatly affected moduli. To evaluate fatigue performance of HMA mixtures, three different fatigue tests were used in this study: Cyclic direct tension test based on simplified viscoelastic continuum damage (S-VECD) model, Semicircle Bend Test (SCB), and modified overlay test (OT). The findings from these tests suggest gradation and binder type significantly impact pavement performance
An investigation of distresses found in concrete and asphalt pavements for Georgia forensic guide recommendation by Catherine Johnson( )

1 edition published in 2016 in English and held by 1 WorldCat member library worldwide

This thesis presents the recommendation for whether the Georgia Department of Transportation (GDOT) should adopt the National Cooperative Highway Research Program (NCHRP) Report 747 (Guide for Conducting Forensic Investigations of Highway Pavements) as a guide to conduct forensic investigations. The evaluation of three pavement types using the NCHRP 747 guide is completed: Jointed Plain Concrete (JPC), Continuously Reinforced Concrete (CRC), and Hot Mix Asphalt (HMA). Each type consisted of an evaluation of two sites in "good/fair" and "poor" conditions. Non-destructive testing was performed using a Ground Penetration Radar (GPR) and Falling Weight Deflectometer (FWD). Destructive and on-site field testing were performed consistently with the recommendations of the guide. Laboratory tests were conducted to determine material properties and combined with traffic data to form conclusions about the causes of pavement distress. It is recommended from this study that the GDOT adopts the NCHRP Report 747 for use in Georgia
Multiscale modeling of fracture mechanism in cementitious composites using the peridynamic method and enhancement in its implementation by Amin Yaghoobi( )

1 edition published in 2017 in English and held by 1 WorldCat member library worldwide

In the present dissertation, a multiscale meshless framework based on peridynamic theory is developed to study fracture behavior of cementitious composite materials. The most general form, non-ordinary state-based peridynamics (NOSBPD) is implemented as a promising computational tool in fracture analysis while using classical constitutive equations. The NOSBPD is successfully implemented for finite strain material. The dynamic relaxation method is also adopted to obtain quasi-static solution of the system of peridynamic equations. Furthermore, a higher-order approximation method is introduced to control the spurious deformation mode conventionally found in the NOSBPD formulation. This dissertation considers two major efforts in fracture modeling of heterogeneous cementitious composite materials. First, a framework is proposed to predict the response of fiber reinforced concrete (FRC) structures. This approach includes a semi-discrete method in modeling the fiber reinforcement. Second, a mesoscale modeling of concrete members is proposed in which heterogeneous concrete material is represented by four phases (cementitious matrix, coarse aggregates, interfacial transition zone and air voids) in the NOSBPD framework. A statistical study is provided to comprise the effect of random distributions of constituent materials. Finally, two approaches are considered to decrease the computational cost in NOSBPD simulations. The first approach accounts for symmetry boundary conditions in a peridynamic body. The present formulation introduces constraints which allow modeling of local symmetry conditions. Furthermore, in the second approach, the NOSBPD is coupled with the finite element method (FEM). The coupling method enables using peridynamics at discontinuities such as cracks, while using more efficient finite elements for the surrounding body. These two methods effectively reduce the solution time while maintaining accuracy. The validity of the proposed approaches is studied through various examples, and they are found successful and worthwhile for fracture analysis of brittle materials
Resilience of the Middle Oconee River to anthropomorphic watershed impacts and precipitation extremes by Emad Abdullahi Ahmed( )

1 edition published in 2019 in English and held by 1 WorldCat member library worldwide

Increase in population and economic development combined with climate change modifies the river system both by changing the watershed characteristic and the hydrologic regime. These lead to altered flow patterns, poor water quality, and destruction of aquatic habitat if it is not appropriately managed. To effectively manage the precious resource, it is vital to understand and consider the combined impact of climate and land-use changes to the river flow. In this project, ArcSWAT was used to model the flow in the Middle Oconee River with three different climate projection models. A Land Transformation Model projected possible land-use changes in the study area. The projected flow shows a slight increase for GISS and MIROC5 models and a decrease for CanESM2. Projected land-use changes indicated a decrease in flow. By 2050, all three models suggest the need to be planning now for alternative water sources in order to achieve the desired basin resilience
Utilization of large-scale rolling wheel tester to investigate the stress reduction in pavement layers due to the use of geosynthetic materials by Jason Christopher Wright( )

1 edition published in 2018 in English and held by 1 WorldCat member library worldwide

This study investigates the behavior of geosynthetic-reinforced pavement foundation systems through large-scale rolling-wheel tests performed with problematic subgrade soils in north Georgia. Sixteen large-scale specimens were constructed with twelve including geosynthetic reinforcement. Subgrade soils were compacted either at optimum moisture content or a moisture content higher than optimum to produce a lower California Bearing Ratio. Both an extruded biaxial geogrid and woven geotextile were placed at various locations to investigate the optimal placement location for the different subgrade conditions. Pressure sensors were installed near the bottom of the aggregate base layer and near the top of subgrade layer to monitor the vertical stress variations within the pavement system during rolling-wheel trafficking. The vertical pressure at the bottom of aggregate base and top of subgrade decreased on average approximately 15.3% and 18.8%, respectively. The results indicate which geosynthetic type, and geosynthetic placement provides the highest pressure reduction for each subgrade condition
Data-driven learning-based identification and control of linear parameter-varying systems by Syed Zeeshan Rizvi( )

1 edition published in 2016 in English and held by 1 WorldCat member library worldwide

This dissertation proposes algorithms for data-driven nonparametric identification, model reduction, and control synthesis of linear parameter-varying (LPV) models in the state-space form. We make use of kernelized machine learning (ML) and multivariate analysis (MVA) tools to develop model reduction techniques that reduce the scheduling dependency in LPV state-space (LPV-SS) models, thereby reducing exponentially, the computation complexity of LPV controller synthesis. Further, we formulate a regularized least squares support vector machine (LS-SVM)-based algorithm to identify LPV-SS models using inputs, outputs, states, and scheduling variables measurements. The technique is further extended to an instrumental variable support vector machine (IV-SVM) approach that is able to identify LPV-SS models under generic noise conditions, including cases where noise not only is colored, but is also correlated with the scheduling variables. The proposed technique seeks to obtain an unbiased estimator of the scheduling dependency functions in the face of noise-induced bias. In case the state variables are not directly measurable, a kernelized canonical correlation analysis (CCA)-based routine is proposed to estimate the states from past and future inputs, outputs, and scheduling variables measurements. This provides a non-unique estimate of the states up to a similarity transform. Once the states are estimated, previously-proposed LS-SVM-based algorithm is used in tandem with the estimated states to identify an LPV-SS model. All techniques proposed in this work exploit the use of the so-called kernel trick, giving extra degrees of freedom to choose different kernel functions and tune their associated hyper-parameters. Different applications including a robotic manipulator and chemical process models are used to verify the different algorithms developed as part of this dissertation
Methods for predicting flow-induced vibrations in bellows expansion joints by Stephen Lane Higgins( )

1 edition published in 2017 in English and held by 1 WorldCat member library worldwide

Bellows expansion joints are a specialty corrugated pipe fixture that serve critical purposes in aeronautics, space, defense and industrial applications. Their corrugated design makes bellows joints susceptible to a high-amplitude, flow-induced vibration phenomenon that can compromise the structural integrity of the joint. The current empirically-based method used by NASA to assess flow-induced vibration in bellows joints was developed in the early 1980s. This historical method is discussed here with a new nondimensional analysis that provides a simpler way to apply the model and examine its output. Presently, new bellows designs are beyond the empirical basis of this historical method, underscoring the need for more modern methods that are computationally efficient and physically insightful. To this end, a physics based, coupled oscillator model of bellows flow-induced vibration is developed. A comparison of the model output to experimental bellows response is presented and discussed
Operation and maintenance of a high-speed water tunnel by Haynes Curtis( )

1 edition published in 2018 in English and held by 1 WorldCat member library worldwide

The University of Georgia (UGA) High-Speed Water Tunnel (HSWT) has been in op- eration since July 2017. While existing literature provided much of the information needed to design the HSWT, literature covering the operation and maintenance of such a facility is sparse. To conduct experiments in a water tunnel requires unique tools and techniques that are not always intuitive. This thesis documents the development of foundational tools, equipment, and procedures necessary for the operation and maintenance of a high-speed water tunnel, and will serve as a reference and guide to those working with similar facilities. This thesis consists of four main sections including operational safety, experimental support devices, instrumentation, and maintenance
Light sheet microscopy incorporating adaptive optics by Keelan Michael Lawrence( )

1 edition published in 2018 in English and held by 1 WorldCat member library worldwide

When imaging deep into biological samples in Light Sheet Microscopy, refractive index variations within the sample, as well as differences between the sample, immersion medium, and sample holder distort the optical wavefront causing a loss of resolution and a decrease of the signal to noise ratio of the image. By implementing Adaptive Optics in a light sheet system, optical aberrations can be corrected and resolution can be increased despite the wavefront distortions cause by the organism. Adaptive Optics systems operate by sensing the wavefront of the incident light and then correcting the distortions in the wavefront with a modulation element. In this paper, we cover the design and implementation of an Adaptive Optics system composed of a deformable mirror and Shack-Hartmann Wavefront Sensor for the measurement and correction of wavefront aberrations caused by zebrafish (D. rerio) larvae during live imaging with Light Sheet Microscopy
A three carbon source feeding strategy for hyaluronic acid production in recombinant escherichia coli by Donaldson Joseph Armento( )

1 edition published in 2017 in English and held by 1 WorldCat member library worldwide

The primary goal of this research was to improve hyaluronic acid production in recombinant E. coli. Hyaluronic acid (HA) is a biopolymer found throughout the human body that has a number of medical applications. A codon optimized hasA gene from Streptococcus zooepidemicus was cloned into wild-type and mutant E. coli MG 1655 strains to allow for HA production. The mutant strains lacked pgi (MEC367), nagB (MEC700), or both genes (MEC526). These genes were selectively knocked out in order to minimize metabolic competition to hyaluronic acid production. The strains were then screened for HA production in shake flasks using 50 mL defined media containing single carbon sources: glucose, fructose, and n-acetylglucosamine, as well as combinations of two or three carbon sources. Four carbon source/strain combinations were then selected to be used in 1-L batch fermentations. MEC 526 grown on 95 mM glucose and 5 mM NAG achieved the highest HA titer of 35.8 mg/L from the 1-L batch fermentation. Utilizing multiple carbon sources improved HA production in all strains. Additionally, MEC 526 which contained both knockouts had higher HA production than the wild-type strain in all experiments
 
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