Engineering Commons^™

Steam Reheat In Nuclear Power Plants, Paul John Marotta

Doctoral Dissertations

In this work, reheating steam from a commercial nuclear power plant is explored in order to increase efficiency and power output. A thermal source in the form of a High Temperature Gas Reactor (HTGR) is considered. Engineering challenges include proof-of-principle, reactor sizing, evaluation, and feasibility.

The proposed thermodynamic process modifications have been evaluated for a range of inlet steam quality conditions. The evaluation of the steam tube dimensions and number of optimal tubes have been calculated utilizing the so-called Log Mean Temperature Difference method. Subsequently, the performance of the steam tubes was further analyzed within a water vapor and liquid …

Control Design And Filtering For Wireless Networked Systems, Xiao Ma

Doctoral Dissertations

This dissertation is concerned with estimation and control over wireless networked systems. Several problems are addressed, including estimator design over packet loss links, control and estimation over cognitive radio systems, modeling and prediction of wireless sensor networks (WSNs), and localization with the Theater Positioning System (TPS). The first problem addressed is the state estimation of a discrete-time system through a packet loss link modeled by a Bernoulli random variable. The optimal filter is derived by employing exact hybrid filtering. The performance of the optimal filter is illustrated by numerical simulations. Next, we consider the problem of estimation and control over …

Electric Vehicles In China: Emissions, Health Impacts, And Equity, Shuguang Ji

Doctoral Dissertations

E-bikes in China are the single largest adoption of alternative fuel vehicles in history, with more than 100 million e-bikes purchased in the past decade and vehicle ownership about 2× [time] larger for e-bikes as for conventional cars; e-cars sales, too, are rapidly growing. Electric vehicles (EVs) in China are being considered as a strategy to improve air quality, energy efficiency, and reduce health impacts due to transport emissions. Because EVs have different pollution sources, namely electric generating units (EGUs), quantitative analysis for health impacts requires understanding the exposure efficiency of related pollution sources. In this dissertation, EVs will be …

A Low-Power, Highly Stabilized Three-Electrode Potentiostat Using Subthreshold Techniques, Melika Roknsharifi

Doctoral Dissertations

Implantable micro- and nano- sensors and implantable microdevices (IMDs) have demonstrated potential for monitoring various physiological parameters such as glucose, lactate, CO₂ [carbon dioxide], pH, etc. Potentiostats are essential components of electrochemical sensors such as glucose monitoring devices for diabetic patients. Diabetes is a metabolic disorder associated with insufficient production or inefficient utilization of insulin. The most important role of this enzyme is to regulate the metabolic breakdown of glucose generating the necessary energy for human activities. Diabetic patients typically monitor their blood glucose levels by pricking a fingertip with a lancing device and applying the blood to a …

Investigating The Prediction Of High Resolution Heat Waves And Extreme Precipitation And The Impact Of Heat Waves On Air Quality In U.S. In The 21st Century, Yang Gao

Doctoral Dissertations

In this study, the perennial problem of scale is addressed with an updated set of modeling tools that include global climate, atmospheric chemistry simulation, mesoscale weather, and air quality simulations. The evaluation of coupled model performance across geographic scales and the assessment of local scale climate change impacts under a fossil fuel intensive climate change scenario Representative Concentration Pathway (RCP 8.5) was achieved by linking the global climate model Community Earth System Model (CESM), with the regional climate model Weather Research and Forecasting (WRF) Model. This study is the first evaluation of dynamical downscaling using WRF on a 4km by …

Exploring Computational Chemistry On Emerging Architectures, David Dewayne Jenkins

Doctoral Dissertations

Emerging architectures, such as next generation microprocessors, graphics processing units, and Intel MIC cards, are being used with increased popularity in high performance computing. Each of these architectures has advantages over previous generations of architectures including performance, programmability, and power efficiency. With the ever-increasing performance of these architectures, scientific computing applications are able to attack larger, more complicated problems. However, since applications perform differently on each of the architectures, it is difficult to determine the best tool for the job. This dissertation makes the following contributions to computer engineering and computational science. First, this work implements the computational chemistry variational …

Techniques For Wireless Channel Modeling In Harsh Environments, Phani Teja Kuruganti

Doctoral Dissertations

With the rapid growth in the networked environments for different industrial, scientific and defense applications, there is a vital need to assure the user or application a certain level of Quality of Service (QoS). Environments like the industrial environment are particularly harsh with interference from metal structures (as found in the manufacturing sector), interference generated during wireless propagation, and multipath fading of the radio frequency (RF) signal all invite novel mitigation techniques. The challenge of achieving the benefits like improved energy efficiency using wireless is closely coupled with maintaining network QoS requirements. Assessment and management of QoS needs to occur, …

A Highly Integrated Gate Driver With 100% Duty Cycle Capability And High Output Current Drive For Wide-Bandgap Power Switches In Extreme Environments, Robert Lee Greenwell

Doctoral Dissertations

High-temperature integrated circuits fill a need in applications where there are obvious benefits to reduced thermal management or where circuitry is placed away from temperature extremes. Examples of these applications include aerospace, automotive, power generation, and well-logging. This work focuses on the automotive applications, in which the growing demand for hybrid electric vehicles (HEVs), plug-in hybrid electric vehicles (PHEVs), and fuel cell vehicles (FCVs) has increased the need for high-temperature electronics that can operate at the extreme ambient temperatures that exist under the hood, which can be in excess of 150°C. Silicon carbide (SiC) and other wide-bandgap power switches that …

Computer Modeling And Signal Analysis Of Cardiovascular Physiology, Henian Xia

Doctoral Dissertations

This dissertation aims to study cardiovascular physiology from the cellular level to the whole heart level to the body level using numerical approaches.

A mathematical model was developed to describe electromechanical interaction in the heart. The model integrates cardio-electrophysiology and cardiac mechanics through excitation-induced contraction and deformation-induced currents. A finite element based parallel simulation scheme was developed to investigate coupled electrical and mechanical functions. The developed model and numerical scheme were utilized to study cardiovascular dynamics at cellular, tissue and organ levels. The influence of ion channel blockade on cardiac alternans was investigated. It was found that the channel blocker …

Optimization And Learning In Energy Efficient Cognitive Radio System, Kun Zheng

Doctoral Dissertations

Energy efficiency and spectrum efficiency are two biggest concerns for wireless communication. The constrained power supply is always a bottleneck to the modern mobility communication system. Meanwhile, spectrum resource is extremely limited but seriously underutilized.

Cognitive radio (CR) as a promising approach could alleviate the spectrum underutilization and increase the quality of service. In contrast to traditional wireless communication systems, a distinguishing feature of cognitive radio systems is that the cognitive radios, which are typically equipped with powerful computation machinery, are capable of sensing the spectrum environment and making intelligent decisions. Moreover, the cognitive radio systems differ from traditional wireless …

Parallel For Loops On Heterogeneous Resources, Frederick Edward Weber

Doctoral Dissertations

In recent years, Graphics Processing Units (GPUs) have piqued the interest of researchers in scientific computing. Their immense floating point throughput and massive parallelism make them ideal for not just graphical applications, but many general algorithms as well. Load balancing applications and taking advantage of all computational resources in a machine is a difficult challenge, especially when the resources are heterogeneous. This dissertation presents the clUtil library, which vastly simplifies developing OpenCL applications for heterogeneous systems. The core focus of this dissertation lies in clUtil's ParallelFor construct and our novel PINA scheduler which can efficiently load balance work onto multiple …

Quaternionic Attitude Estimation With Inertial Measuring Unit For Robotic And Human Body Motion Tracking Using Sequential Monte Carlo Methods With Hyper-Dimensional Spherical Distributions, Gary To

Doctoral Dissertations

This dissertation examined the inertial tracking technology for robotics and human tracking applications. This is a multi-discipline research that builds on the embedded system engineering, Bayesian estimation theory, software engineering, directional statistics, and biomedical engineering.

A discussion of the orientation tracking representations and fundamentals of attitude estimation are presented briefly to outline the some of the issues in each approach. In addition, a discussion regarding to inertial tracking sensors gives an insight to the basic science and limitations in each of the sensing components.

An initial experiment was conducted with existing inertial tracker to study the feasibility of using this …

Understanding Size Effects In Small Scale Deformation: A Statistical Perspective, Sudharshan Phani Pardhasaradhi

Doctoral Dissertations

Recent experimental observations of micro-compression / tension tests indicate that as the size of test specimen decreases the yield strength increases. This raises a fundamental question: Why is smaller stronger? Is there a fundamental relationship between the size of a specimen and its intrinsic strength? This simple question pushes the limit of the current understanding of the physical mechanisms underlying material deformation, especially at small scales. In order to explain the experimental observations of the strength of small specimens containing a limited number of dislocations, a simple statistical model is developed. Two different types of randomness are introduced, viz., randomness …

A Charge-Recycling Scheme And Ultra Low Voltage Self-Startup Charge Pump For Highly Energy Efficient Mixed Signal Systems-On-A-Chip, Chandradevi Ulaganathan

Doctoral Dissertations

The advent of battery operated sensor-based electronic systems has provided a pressing need to design energy-efficient, ultra-low power integrated circuits as a means to improve the battery lifetime. This dissertation describes a scheme to lower the power requirement of a digital circuit through the use of charge-recycling and dynamic supply-voltage scaling techniques. The novel charge-recycling scheme proposed in this research demonstrates the feasibility of operating digital circuits using the charge scavenged from the leakage and dynamic load currents inherent to digital design. The proposed scheme efficiently gathers the “ground-bound” charge into storage capacitor banks. This reclaimed charge is then subsequently …

Optimization Of Transcurium Isotope Production In The High Flux Isotope Reactor, Susan Hogle

Doctoral Dissertations

The Radiochemical Engineering Development Center at Oak Ridge National Laboratory is the world's leader in production of californium-252. This and other heavy actinides are produced by irradiation of mixed curium/americium targets in the High Flux Isotope Reactor. Due to the strong dependence of isotopic cross sections upon incoming neutron energy, the efficiency with which an isotope is transmuted is highly dependent upon the neutron flux energy spectrum and intensities. There are certain energy ranges in which the rate of fissions in feedstock materials can be minimized relative to the rate of (n,γ) absorptions. This work shows that by perturbing the …

Kernel-Assisted And Topology-Aware Mpi Collective Communication Among Multicore Or Many-Core Clusters, Teng Ma

Doctoral Dissertations

Multicore or many-core clusters have become the most prominent form of High Performance Computing (HPC) systems. Hardware complexity and hierarchies not only exist in the inter-node layer, i.e., hierarchical networks, but also exist in internals of multicore compute nodes, e.g., Non Uniform Memory Accesses (NUMA), network-style interconnect, and memory and shared cache hierarchies.

Message Passing Interface (MPI), the most widely adopted in the HPC communities, suffers from decreased performance and portability due to increased hardware complexity of multiple levels. We identified three critical issues specific to collective communication: The first problem arises from the gap between logical collective topologies and …

Data Mining And Machine Learning Applications Of Wide-Area Measurement Data In Electric Power Systems, Penn Norris Markham

Doctoral Dissertations

Wide-area measurement systems (WAMS) are quickly becoming an important part of modern power system operation. By utilizing the Global Positioning System, WAMS offer highly accurate time-synchronized measurements that can reveal previously unobtainable insights into the grid’s status. An example WAMS is the Frequency Monitoring Network (FNET), which utilizes a large number of Internet-connected low-cost Frequency Disturbance Recorders (FDRs) that are installed at the distribution level.

The large amounts of data collected by FNET and other WAMS present unique opportunities for data mining and machine learning applications, yet these techniques have only recently been applied in this domain. The research presented …

Extending Structural Learning Paradigms For High-Dimensional Machine Learning And Analysis, Christopher Todd Symons

Doctoral Dissertations

Structure-based machine-learning techniques are frequently used in extensions of supervised learning, such as active, semi-supervised, multi-modal, and multi-task learning. A common step in many successful methods is a structure-discovery process that is made possible through the addition of new information, which can be user feedback, unlabeled data, data from similar tasks, alternate views of the problem, etc. Learning paradigms developed in the above-mentioned fields have led to some extremely flexible, scalable, and successful multivariate analysis approaches. This success and flexibility offer opportunities to expand the use of machine learning paradigms to more complex analyses. In particular, while information is often …

Development Of Patient Specific Predictive Treatment Margins To Account For Prostate Motion During Treatment Using Real-Time Intra Fraction Tracking, Michael Edward Howard

Doctoral Dissertations

Radiation therapy for prostate cancer has evolved over time. Intra-fractional motion of the prostate has been a clinical limitation in dose delivery. Reduced margins can lead to less toxicity to critical structures and an overall reduction in the risk of secondary cancers. Three models have been developed to predict prostate margins based on the first five fractions of treatment.

An 8^th order polynomial model is utilized with the 95% and 99% predictive lines indicating margins. This approach is applied to 24 patients. The maximum values as indicated by the predictive lines are used as the margins for the patient. …

Dynamic Task Execution On Shared And Distributed Memory Architectures, Asim Yarkhan

Doctoral Dissertations

Multicore architectures with high core counts have come to dominate the world of high performance computing, from shared memory machines to the largest distributed memory clusters. The multicore route to increased performance has a simpler design and better power efficiency than the traditional approach of increasing processor frequencies. But, standard programming techniques are not well adapted to this change in computer architecture design.

In this work, we study the use of dynamic runtime environments executing data driven applications as a solution to programming multicore architectures. The goals of our runtime environments are productivity, scalability and performance. We demonstrate productivity by …

Stiffness-Driven Design And Interface Debonding Study Of Frp Sandwich Structures For Bridges, Wenchao Song

Doctoral Dissertations

Bridge decks entirely made of fiber reinforced polymer (FRP) materials are a potential solution to fast construction in bridge engineering. This study mainly focuses on the stiffness-driven design of FRP decks for short-span slab bridges and the interface debonding of an FRP sandwich structure with honeycomb cores. As is evidenced by the analytical and experimental results in this study, these two topics are closely related to the application of FRP materials in bridge deck construction. The design verification of an FRP slab bridge showed that its design should be controlled by stiffness rather than strength. The tests of the FRP …

Structure And Dynamics Of High Temperature Superconductors, Jennifer Lynn Niedziela

Doctoral Dissertations

High temperature superconductivity in iron based compounds has presented a series of complex problems to condensed matter physics since being discovered in 2008. The stalwart basis of condensed matter physics is the “strength in numbers" aspect of crystalline periodicity. Perfect crystalline periodicity has made possible the reduction of the questions of structural and electronic properties to single dimensions, increasing the tractability of these problems. Nevertheless, modern complex materials stretch these assumptions to their limits, and it is at this point where our work starts. Using neutron and x-ray scattering, we have conducted a series of studies on the structural disorder …

Development Of A Novel Technique For Predicting Tumor Response In Adaptive Radiation Therapy, Rebecca Marie Seibert

Doctoral Dissertations

This dissertation concentrates on the introduction of Predictive Adaptive Radiation Therapy (PART) as a potential method to improve cancer treatment. PART is a novel technique that utilizes volumetric image-guided radiation therapy treatment (IGRT) data to actively predict the tumor response to therapy and estimate clinical outcomes during the course of treatment. To implement PART, a patient database containing IGRT image data for 40 lesions obtained from patients who were imaged and treated with helical tomotherapy was constructed. The data was then modeled using locally weighted regression. This model predicts future tumor volumes and masses and the associated confidence intervals based …

Validation Of Weak Form Thermal Analysis Algorithms Supporting Thermal Signature Generation, Elton Lewis Freeman

Masters Theses

Extremization of a weak form for the continuum energy conservation principle differential equation naturally implements fluid convection and radiation as flux Robin boundary conditions associated with unsteady heat transfer. Combining a spatial semi-discretization via finite element trial space basis functions with time-accurate integration generates a totally node-based algebraic statement for computing. Closure for gray body radiation is a newly derived node-based radiosity formulation generating piecewise discontinuous solutions, while that for natural-forced-mixed convection heat transfer is extracted from the literature. Algorithm performance, mathematically predicted by asymptotic convergence theory, is subsequently validated with data obtained in 24 hour diurnal field experiments for …

Heat Transfer Analysis Via Rate Based Sensors, Jake Erik Plewa

Masters Theses

This work presents an integrated rate-based sensor and method for resolving the surface heat flux of a fundamental inverse heat conduction problem without numerical regularization or differentiation in a semi-infinite geometry that additionally accounts for thermocouple delay due to its intrinsic time constant. The sensor uses well-designed analog filters to directly regularize raw voltage data to eliminate the need for numerical regularization methods. The sensor can also be used in a series of well-designed voltage-rate interfaces that directly measure the voltages from in-depth thermocouples, which are used in conjunction with the thermocouple calibration curve to provide higher-time derivatives of the …

Estimates Of Glacier Mass Loss And Contribution To Streamflow: Wind River Range (Wyoming, Usa), Jeffrey Allen Marks

Masters Theses

The Wind River Range is a continuous mountain range approximately 160 km in length in west-central Wyoming. The Wind River Range is host to roughly 680 snow and ice bodies with 63 of these considered glaciers including seven of the ten largest glaciers in the American Rocky Mountains. The presence of glaciers results in meltwater contributions to streamflow during the late summer (July, August, and September – JAS) when snowmelt is decreasing, temperatures are high, precipitation is low, and irrigation demand continues. Most studies indicate that the glaciers in the Wind River Range have been retreating since the 1850’s, the …

Lignin Yield Maximization Of Lignocellulosic Biomass By Taguchi Robust Product Design Using Organosolv Fractionation, Anton Friedrich Astner

Masters Theses

Lignin, a byproduct of the organosolv pretreatment process using lignocellulosic biomass from switchgrass (Panicum virgatum) and tulip poplar (Liriodendron tulipifera) is currently being explored for its potential use in the production of value-added chemicals and biobased polymers. Pretreatment is one of the most expensive processing steps in cellulosic biomass conversion. Optimization of the process is one of the major goals of the biomass-toethanol conversion process. Taguchi Robust Product Design (TRPD) provides an effective engineering experimental design method for optimizing a system and designing products that are robust to process variations. Given the results of several preliminary …

Utilization Of Rainwater As A Supplementary Water Source For Cooling Tower Makeup: A Sustainability Strategy For Potable Water Use Reduction, Elizabeth Stassun Costello

Masters Theses

The use of rainwater as a supplementary water source for cooling water makeup was explored in an effort to reduce the potable water demand of theUniversityofTennessee’sKnoxvillecampus. A water quality analysis involving the measurement of parameters relevant to cooling tower operation was conducted on tap water currently used for makeup supply and rainwater collected from the roof of a campus building. In anticipation of limited rainwater supplies due to issues of catchment surface area, collection efficiency, storage capacity, and climatic conditions, blends of rainwater and tap water were also analyzed. The dissolved solids concentration of the rainwater was significantly lower than …

Impacts Of Beetle Kill On Modeled Streamflow Response In The North Platte River Basin, Jordan Andrew Rudolph

Masters Theses

A beetle epidemic has been sweeping its way across the western United States and into portions of southern Canada that has caused millions of acres of forests to ultimately die. This beetle outbreak, that many have come to know simply as “beetle kill”, has caused many scientists to feel that such dramatic changes in land cover could potentially alter the hydrology throughout much of the West. One of the most important hydrological processes that beetle kill has the potential to impact is streamflow. This paper attempts to evaluate the hydrological impacts on streamflow from land cover change due to beetle …

Predicting Enzyme Targets For Optimization Of Metabolic Networks Under Uncertainty, David Christopher Flowers

Masters Theses

Recently, ensemble modeling was applied to metabolic networks for the sake of predicting the effects of genetic manipulations on the observed phenotype of the system. The ensemble of models is generated from experimental wild-type flux data and screened using phenotypic data from gene overexpression and knockout experiments, leaving predictive models. The need for data from multiple genetic perturbation experiments is an inherent limitation to this approach. In this investigation, ensemble modeling is used alongside elementary mode analysis to attempt to predict those enzymatic perturbations that are most likely to result in an increase in a target yield and a target …