ETDs: Virginia Tech Electronic Theses and Dissertationshttp://hdl.handle.net/10919/55342018-09-23T11:12:58Z2018-09-23T11:12:58ZFully Distributed Multi-parameter Sensors Based on Acoustic Fiber Bragg GratingsHu, Dihttp://hdl.handle.net/10919/851122018-09-23T07:06:56Z2017-03-31T00:00:00ZHu, Di
2017-03-31T00:00:00ZA fully distributed multi-parameter acoustic sensing technology is proposed. Current fully distributed sensing techniques are exclusively based on intrinsic scatterings in optical fibers. They demonstrate long sensing span, but their limited applicable parameters (temperature and strain) and costly interrogation systems have prevented their widespread applications.
A novel concept of acoustic fiber Bragg grating (AFBG) is conceived with inspiration from optical fiber Bragg grating (FBG). This AFBG structure exploits periodic spatial perturbations on an elongated waveguide to sense variations in the spectrum of an acoustic wave. It achieves ten times higher sensitivity than the traditional time-of-flight measurement system using acoustic pulses. A fast interrogation method is developed to avoid frequency scan, reducing both the system response time (from 3min to <1ms) and total cost.
Since acoustic wave propagates with low attenuation along varieties of solid materials (metal, silica, sapphire, etc.), AFBG can be fabricated on a number of waveguides and to sense multiple parameters. Sub-millimeter metal wire and optical fiber based AFBGs have been demonstrated experimentally for effective temperature (25~700 degC) and corrosion sensing. A hollow borosilicate tube is demonstrated for simultaneous temperature (25~200 degC) and pressure (15~75 psi) sensing using two types of acoustic modes. Furthermore, a continuous 0.6 m AFBG is employed for distributed temperature sensing up to 500 degC and to accurately locate the 0.18 m long heated section.
Sensing parameters, sensitivity and range of an AFBG can be tuned to fit a specific application by selecting acoustic waveguides with different materials and/or geometries. Therefore, AFBG is a fully distributed sensing technology with tremendous potentiality.Novel Multilevel Converter for Variable-Speed Medium Voltage Switched Reluctance Motor DrivesShehada, Ahmedhttp://hdl.handle.net/10919/851112018-09-23T07:06:52Z2017-03-31T00:00:00ZShehada, Ahmed
2017-03-31T00:00:00ZA novel multilevel converter that is especially suited for high speed multi-megawatt switched reluctance motor drives operating at the medium voltage level is presented. The drive is capable of variable speed, four-quadrant operation. Each phase leg of the converter contains an arbitrary number of cascaded cells connected in series with the phase winding. Each cell contains a half-bridge chopper connected to a capacitor. The converter is named the cascaded chopper cell converter. The modular nature of the converter with the ability to add redundant cells makes it very reliable, which is a key requirement for medium voltage drive applications. A comprehensive control algorithm that overcomes the challenges of balancing and controlling cell capacitor voltages is also proposed. A suitable startup algorithm to limit startup current and switching losses, as well as ensure that cell capacitor voltages remain controlled at startup, is suggested. Details of the drive design such as component sizing and control parameter selection are also discussed. A detailed simulation model is developed and explained, and simulation results are provided for primary validation. Operation with standard current and speed control is first simulated. Then a scheme that gives way to a controller that operates the drive in single-pulse mode is developed and presented. This single-pulse control scheme controls the turn-on and turn-off angles, as well as the energization voltage level, in order to obtain high efficiency. Practical considerations related to the drive such as reliability, efficiency, and cost considerations are also discussed. Finally, a detailed comparison of the proposed converter to another competing converter is performed. Besides its scalability to high voltages and powers, the reliability and efficiency of the proposed converter makes it also a candidate for sub-megawatt applications requiring minimum downtime, or any application where high efficiency or improved performance is required.
A small part of this work is also dedicated to brushless dc machines. Control methods for a new converter for brushless dc machines are proposed and verified via simulation. The main advantage of this converter with the proposed control is that it allows exact control of torque or speed up to twice the rated speed, without resorting to current phase advancing or other flux-weakening techniques.Modeling and Analysis of Non-Linear Dependencies using Copulas, with Applications to Machine LearningKarra, Kiranhttp://hdl.handle.net/10919/851102018-09-23T07:06:48Z2018-09-21T00:00:00ZKarra, Kiran
2018-09-21T00:00:00ZMany machine learning (ML) techniques rely on probability, random variables, and stochastic
modeling. Although statistics pervades this field, there is a large disconnect between the copula
modeling and the machine learning communities. Copulas are stochastic models that capture the
full dependence structure between random variables and allow flexible modeling of multivariate
joint distributions. Elidan was the first to recognize this disconnect, and introduced copula based
models to the ML community that demonstrated magnitudes of order better performance than the
non copula-based models Elidan [2013]. However, the limitation of these is that they are only
applicable for continuous random variables and real world data is often naturally modeled jointly
as continuous and discrete. This report details our work in bridging this gap of modeling and
analyzing data that is jointly continuous and discrete using copulas.
Our first research contribution details modeling of jointly continuous and discrete random variables
using the copula framework with Bayesian networks, termed Hybrid Copula Bayesian Networks
(HCBN) [Karra and Mili, 2016], a continuation of Elidan�[BULLET]s work on Copula Bayesian Networks
Elidan [2010]. In this work, we extend the theorems proved by Ne�[BULLET]slehov�[BULLET]a [2007] from bivariate
to multivariate copulas with discrete and continuous marginal distributions. Using the multivariate
copula with discrete and continuous marginal distributions as a theoretical basis, we construct an
HCBN that can model all possible permutations of discrete and continuous random variables for
parent and child nodes, unlike the popular conditional linear Gaussian network model. Finally, we
demonstrate on numerous synthetic datasets and a real life dataset that our HCBN compares favorably,
from a modeling and flexibility viewpoint, to other hybrid models including the conditional
linear Gaussian and the mixture of truncated exponentials models.
Our second research contribution then deals with the analysis side, and discusses how one may
use copulas for exploratory data analysis. To this end, we introduce a nonparametric copulabased
index for detecting the strength and monotonicity structure of linear and nonlinear statistical
dependence between pairs of random variables or stochastic signals. Our index, termed Copula
Index for Detecting Dependence and Monotonicity (CIM), satisfies several desirable properties of
measures of association, including R�[BULLET]enyi�[BULLET]s properties, the data processing inequality (DPI), and
consequently self-equitability. Synthetic data simulations reveal that the statistical power of CIM
compares favorably to other state-of-the-art measures of association that are proven to satisfy the
DPI. Simulation results with real-world data reveal CIM�[BULLET]s unique ability to detect the monotonicity
structure among stochastic signals to find interesting dependencies in large datasets. Additionally,
simulations show that CIM shows favorable performance to estimators of mutual information when
discovering Markov network structure.
Our third research contribution deals with how to assess an estimator�[BULLET]s performance, in the scenario
where multiple estimates of the strength of association between random variables need to be
rank ordered. More specifically, we introduce a new property of estimators of the strength of statistical
association, which helps characterize how well an estimator will perform in scenarios where
dependencies between continuous and discrete random variables need to be rank ordered. The
new property, termed the estimator response curve, is easily computable and provides a marginal
distribution agnostic way to assess an estimator�[BULLET]s performance. It overcomes notable drawbacks
of current metrics of assessment, including statistical power, bias, and consistency. We utilize the
estimator response curve to test various measures of the strength of association that satisfy the data
processing inequality (DPI), and show that the CIM estimator�[BULLET]s performance compares favorably
to kNN, vME, AP, and HMI estimators of mutual information. The estimators which were identified
to be suboptimal, according to the estimator response curve, perform worse than the more
optimal estimators when tested with real-world data from four different areas of science, all with
varying dimensionalities and sizes.The Eye of the StairYang, Che-Hanhttp://hdl.handle.net/10919/851092018-09-23T07:06:46Z2018-09-21T00:00:00ZYang, Che-Han
2018-09-21T00:00:00ZThis project began with the measurement of the exterior stair at the East addition of Campbell Hall on the campus of the University of Virginia. The project continued with the design of nine different autonomous stairs, and nine stairs as buildings.
Stairs are one of the most basic and complex elements of architecture. Stairs interconnect to all aspects of a building. Through ascension and descension our existence is modified.
The �[BULLET]eye of the stair�[BULLET] looks up and down into the well. It is like the �[BULLET]eye of the storm�[BULLET], which allows us to see things calmly while everything outside the storm�[BULLET]s eye is in motion. Through looking into the eye of the stair we see a stair�[BULLET]s eye view.Mechanism of CASK-linked ophthalmological disordersLiang, Chenhttp://hdl.handle.net/10919/851082018-09-23T07:06:39Z2018-09-21T00:00:00ZLiang, Chen
2018-09-21T00:00:00ZCalcium/calmodulin-dependent serine protein kinase (CASK) is a membrane-associated guanylate kinase (MAGUK) family protein, which is encoded by a gene of identical name present on the X chromosome. CASK may participate in presynaptic scaffolding, gene expression regulation, and cell junction formation. CASK is essential for survival in mammals. Heterozygous mutations in the CASK gene (in females) produce X-linked intellectual disability (XLID) and mental retardation and microcephaly with pontine and cerebellar hypoplasia (MICPCH, OMIM# 300749). CASK mutations are also frequently associated with optic nerve hypoplasia (ONH) which is the most common cause of childhood blindness in developed countries. Some patients with mutations in CASK have been also diagnosed with optic nerve atrophy (ONA) and glaucoma. We have used floxed CASK (CASKfloxed), CASK heterozygous knockout (CASK(+/-)), CASK neuronal knockout (CASKNKO) and tamoxifen inducible CASK knockout (CASKiKO) mouse models to investigate the mechanism and pathology of CASK-linked ONH. Our observations indicate that ONH occurs with 100% penetrance in CASK(+/-) mice, which also displayed microcephaly and disproportionate cerebellar hypoplasia. Further, we found that CASK-linked ONH is a complex developmental neuropathology with some degenerative components. Cellular pathologies include loss of retinal ganglion cells (RGC), astrogliosis, axonopathy, and synaptopathy. The onset of ONH is late in development, observed only around the early postnatal stage in mice reaching the plateau phase by three weeks of birth. The developmental nature of the disorder is confirmed by deleting CASK after maturity since CASKiKO mice did not produce any obvious optic nerve pathology. Strikingly the CASKfloxed mice expressing ~49% level of CASK did not manifest ONH despite displaying a slightly smaller brain and cerebellar hypoplasia indicating that ONH may not simply be an extension of microcephaly. We discovered that deleting CASK in neurons produced lethality before the onset of adulthood. The CASKNKO mice exhibited delayed myelination of the optic nerve. Overall this work suggests that CASK is critical for neuronal maturation and CASK-linked ONH is a pervasive developmental disorder of the subcortical visual pathway. Finally, in a side project, I also described a new methodology of targeting neurons using receptor-mediated endocytosis which would help target retinal neurons for therapeutic purposes in the future.Free Vibration of Bi-directional Functionally Graded Material Circular Beams using Shear Deformation Theory employing Logarithmic Function of RadiusFariborz, Jamshidhttp://hdl.handle.net/10919/851072018-09-23T07:06:36Z2018-09-21T00:00:00ZFariborz, Jamshid
2018-09-21T00:00:00ZCurved beams such as arches find ubiquitous applications in civil, mechanical and aerospace engineering, e.g., stiffened floors, fuselage, railway compartments, and wind turbine blades. The analysis of free vibrations of curved structures plays a critical role in their design to avoid transient loads with dominant frequencies close to their natural frequencies.
One way to increase their areas of applications and possibly make them lighter without sacrificing strength is to make them of Functionally Graded Materials (FGMs) that are composites with continuously varying material properties in one or more directions.
In this thesis, we study free vibrations of FGM circular beams by using a logarithmic shear deformation theory that incorporates through-the-thickness logarithmic variation of the circumferential displacement, and does not require a shear correction factor. The radial displacement of a point is assumed to depend only upon its angular position. Thus the beam theory can be regarded as a generalization of the Timoshenko beam theory. Equations governing transient deformations of the beam are derived by using Hamilton�[BULLET]s principle. Assuming a time harmonic variation of the displacements, and by utilizing the generalized differential quadrature method (GDQM) the free vibration problem is reduced to solving an algebraic eigenvalue problem whose solution provides frequencies and the corresponding mode shapes. Results are presented for different spatial variations of the material properties, boundary conditions, and the aspect ratio. It is found that the radial and the circumferential gradation of material properties maintains their natural frequency within that of the homogeneous beam comprised of a constituent of the FGM beam. Furthermore, keeping every other variable fixed, the change in the beam opening angle results in very close frequencies of the first two modes of vibration, a phenomenon usually called mode transition.Development of Predictive Vehicle Control System using Driving Environment Data for Autonomous Vehicles and Advanced Driver Assistance SystemsKang, Yong Sukhttp://hdl.handle.net/10919/851062018-09-23T07:06:33Z2018-09-21T00:00:00ZKang, Yong Suk
2018-09-21T00:00:00ZIn the field of modern automotive engineering, many researchers are focusing on the development of advanced vehicle control systems such as autonomous vehicle systems and Advanced Driver Assistance Systems (ADAS). Furthermore, Driver Assistance Systems (DAS) such as cruise control, Anti-Lock Braking Systems (ABS), and Electronic Stability Control (ESC) have become widely popular in the automotive industry. Therefore, vehicle control research attracts attention from both academia and industry, and has been an active area of vehicle research for over 30 years, resulting in impressive DAS contributions. Although current vehicle control systems have improved vehicle safety and performance, there is room for improvement for dealing with various situations.
The objective of the research is to develop a predictive vehicle control system for improving vehicle safety and performance for autonomous vehicles and ADAS. In order to improve the vehicle control system, the proposed system utilizes information about the upcoming local driving environment such as terrain roughness, elevation grade, bank angle, curvature, and friction. The local driving environment is measured in advance with a terrain measurement system to provide terrain data. Furthermore, in order to obtain the information about road conditions that cannot be measured in advance, this work begins by analyzing the response measurements of a preceding vehicle. The response measurements of a preceding vehicle are acquired through Vehicle-to-Vehicle (V2V) or Vehicle-to-Infrastructure (V2I) communication. The identification method analyzes the response measurements of a preceding vehicle to estimate road data. The estimated road data or the pre-measured road data is used as the upcoming driving environment information for the developed vehicle control system. The metric that objectively quantifies vehicle performance, the Performance Margin, is developed to accomplish the control objectives in an efficient manner. The metric is used as a control reference input and continuously estimated to predict current and future vehicle performance. Next, the predictive control algorithm is developed based on the upcoming driving environment and the performance metric. The developed system predicts future vehicle dynamics states using the upcoming driving environment and the Performance Margin. If the algorithm detects the risks of future vehicle dynamics, the control system intervenes between the driver�[BULLET]s input commands based on estimated future vehicle states. The developed control system maintains vehicle handling capabilities based on the results of the prediction by regulating the metric into an acceptable range. By these processes, the developed control system ensures that the vehicle maintains stability consistently, and improves vehicle performance for the near future even if there are undesirable and unexpected driving circumstances. To implement and evaluate the integrated systems of this work, the real-time driving simulator, which uses precise real-world driving environment data, has been developed for advanced high computational vehicle control systems. The developed vehicle control system is implemented in the driving simulator, and the results show that the proposed system is a clear improvement on autonomous vehicle systems and ADAS.Threshold of RefugePark, Sangyoonhttp://hdl.handle.net/10919/851052018-09-23T07:06:22Z2018-09-21T00:00:00ZPark, Sangyoon
2018-09-21T00:00:00ZFrom every carving and dislodged mass, there is memory left in void. As refugees, the Rohingya resettling in the United States have been displaced out of time and place. This project proposal aims to reconnect persons to place and community. Surrounded on all sides by remnant chestnut oak forest, the �[BULLET]rock oak�[BULLET] of the Appalachian, this establishment of subsidized multi-family resettlement housing, a mosque, and a Rohingya cultural center serves as the rock foundation from which to stabilize the chaos of the unknown. While memory embraces cultural identity, growth embraces new connections - defining a platform of past and future. Roof farms and open circulation plans visualize the seasons. The cropped grass field opens between the three buildings on the complex. They face each other across a green field - conversing in rows of tall oaks and stone brick colonnades in a gradient of public to private space. Children race the setting sunlight down steps and a communal dinner is served. For these wanderers, this is the threshold of refuge.Average Link Rate Analysis over Finite Time Horizon in a Wireless NetworkBodepudi, Sai Nisanthhttp://hdl.handle.net/10919/851042018-09-22T07:08:14Z2017-03-30T00:00:00ZBodepudi, Sai Nisanth
2017-03-30T00:00:00ZInstantaneous and ergodic rates are two of the most commonly used metrics to characterize throughput of wireless networks. Roughly speaking, the former characterizes the rate achievable in a given time slot, whereas the latter is useful in characterizing average rate achievable over a long time period. Clearly, the reality often lies somewhere in between these two extremes. Consequently, in this work, we define and characterize a more realistic N-slot average rate (achievable rate averaged over N time slots). This N-slot average rate metric refines the popular notion of ergodic rate, which is defined under the assumption that a user experiences a complete ensemble of channel and interference conditions in the current session (not always realistic, especially for short-lived sessions).
The proposed metric is used to study the performance of typical nodes in both ad hoc and downlink cellular networks. The ad hoc network is modeled as a Poisson bipolar network with a fixed distance between each transmitter and its intended receiver. The cellular network is also modeled as a homogeneous Poisson point process. For both these setups, we use tools from stochastic geometry to derive the distribution of N-slot average rate in the following three cases: (i) rate across N time slots is completely correlated, (ii) rate across N time slots is independent and identically distributed, and (iii) rate across N time slots is partially correlated. While the reality is close to third case, the exact characterization of the first two extreme cases exposes certain important design insights.The Relationship between the Attitude toward Mathematics and the Frequency of Classroom Observations of Mathematics Lessons by Elementary School AdministratorsSullivan, Molly Lynnhttp://hdl.handle.net/10919/851032018-09-22T07:08:12Z2017-03-30T00:00:00ZSullivan, Molly Lynn
2017-03-30T00:00:00ZThe purpose of this study was to explore the relationship between the attitude toward mathematics, including related mathematics anxiety, and the frequency of classroom observations of mathematics lessons by elementary school administrators. This study considered Approach-Avoidance Motivation as part of the conceptual framework guiding the research. Approach-avoidance motivation refers to a person�[BULLET]s approach of tasks that are pleasant or enjoyable and avoidance of tasks that are disliked or not enjoyable. This research sought to answer the questions:
1. What is the academic background in mathematics of elementary school administrators?
2. What is the attitude toward mathematics of elementary school administrators?
3. What is the frequency of classroom observations of mathematics lessons by elementary school administrators?
4. What, if any, is the relationship between the attitude toward mathematics, including related mathematics anxiety, and the frequency of classroom observations of mathematics lessons by elementary school administrators?
The participants in this study included elementary school principals and assistant principals in one school division in Virginia. Data were collected to investigate the mathematics background, attitude toward mathematics, and frequency of classroom observations of mathematics lessons by elementary school administrators. This study also examined the possible relationship between the attitude toward mathematics, including related mathematics anxiety, and the frequency of classroom observations of mathematics lessons.
The attitude toward mathematics, including related mathematics anxiety, was found to have no relationship with the frequency of both formal and informal classroom observations of mathematics lessons conducted. The sample population data indicated positive attitudes toward mathematics and low levels of mathematics anxiety, which conflicts with some previous research (Dorward and Hadley, 2011; Hembree, 1990). The mathematics background of participants was found to be limited in the number of mathematics courses completed and teaching licensure endorsements specific to mathematics instruction. The findings provide educational leaders with relevant research related to attitude toward mathematics and the instructional leadership practice of observing mathematics classrooms. Central office and school leaders could benefit from explicit expectations relating to the observation of mathematics lessons in schools.
Keywords: mathematics attitude, mathematics anxiety, elementary teachers and mathematics anxiety, elementary principal leadership and mathematics, principal observations