Engineering Commons^™

Characterization Of Fiber Bragg Grating Based, Geometry-Dependent, Magnetostrictive Composite Sensors, Edward Lynch

Theses and Dissertations

Optical sensors based on geometry dependent magnetostrictive composite, having potential applications in current sensing and magnetic field sensing are modeled and evaluated experimentally with an emphasis on their thermal immunity from thermal disturbances. Two sensor geometries composed of a fiber Bragg grating (FBG) embedded in a shaped Terfenol-D/epoxy composite material, which were previously prototyped and tested for magnetic field response, were investigated. When sensing magnetic fields or currents, the primary function of the magnetostrictive composite geometry is to modulate the magnetic flux such that a magnetostrictive strain gradient is induced on the embedded FBG. Simulations and thermal experiments reveal the …

Design And Optimization Of A Modular Dc-Dc Power Converter For Medium Voltage Shipboard Applications, Seyed Rasoul Hosseini

Theses and Dissertations

Power electronic converters rated for medium voltage direct current (MVDC) are promising for electrification of future ships. In shipboard electrification, due to limitation of space, energy and technical maintenance, the high-power density, high efficiency and modularity of the power electronic converters are desired. Utilizing power modules made from wide band gap (WBG) semiconductors like silicon carbide (SiC) and high frequency power transformer (HFPT) can be beneficial for obtaining the high-power density, high efficiency and isolation that is required for the power electronic converters. To provide power for the low voltage (LV) DC loads, a conversion of the power from MVDC …

Design And Analysis Of Fully-Electronic Magnet-Free Non-Reciprocal Metamaterial, Swadesh Poddar

Theses and Dissertations

Reciprocity is a fundamental and very important characteristics of the vast majority of electronic devices, and requires that signals travel in both forward and reverse directions in the same manner. Similarly, electromagnetic non-reciprocity or one way wave propagation, implies that the field created by a source at an observation point is not the same when source and observation points are interchanged. Non-reciprocal devices such as isolators, circulators, phase shifters, polarizers,

switches, tunable resonators, tunable filters, and gyrators enable new applications from radio frequencies to optical frequencies. However, non-reciprocity has been implemented in the past using ferrites in the presence of …

Graphical Convolution Network Based Semi-Supervised Methods For Detecting Pmu Data Manipulation Attacks, Wenyu Wang

Theses and Dissertations

With the integration of information and communications technologies (ICTs) into the power grid, electricity infrastructures are gradually transformed towards smart grid and power systems become more open to and accessible from outside networks. With ubiquitous sensors, computers and communication networks, modern power systems have become complicated cyber-physical systems. The cyber security issues and the impact of potential attacks on the smart grid have become an important issue. Among these attacks, false data injection attack (FDIA) becomes a growing concern because of its varied types and impacts. Several detection algorithms have been developed in the last few years, which were model-based, …

Detection Of Stealthy False Data Injection Attacks Against State Estimation In Electric Power Grids Using Deep Learning Techniques, Qingyu Ge

Theses and Dissertations

Since communication technologies are being integrated into smart grid, its vulnerability to false data injection is increasing. State estimation is a critical component which is used for monitoring the operation of power grid. However, a tailored attack could circumvent bad data detection of the state estimation, thus disturb the stability of the grid. Such attacks are called stealthy false data injection attacks (FDIAs). This thesis proposed a prediction-based detector using deep learning techniques to detect injected measurements. The proposed detector adopts both Convolutional Neural Networks and Recurrent Neural Networks, making full use of the spatial-temporal correlations in the measurement data. …

Health Condition Assessment Of Multi-Chip Igbt Module With Magnetic Flux Density, Xueni Ding

Theses and Dissertations

To achieve efficient conversion and flexible control of electronic energy, insulated gate bipolar transistor (IGBT) power modules as the dominant power semiconductor devices are increasingly applied in many areas such as electric drives, hybrid electric vehicles, railways, and renewable energy systems. It is known that IGBTs are the most vulnerable components in power converter systems. To achieve high power density and high current capability, several IGBT chips are connected in parallel as a multi-chip IGBT module, which makes the power modules less reliable due to a more complex structure. The lowered reliability of IGBT modules will not only cause safety …

Modulation And Control Techniques For Performance Improvement Of Micro Grid Tie Inverters, Zeljko Jankovic

Theses and Dissertations

The concept of microgrids is a new building block of smart grid that acts as a single controllable entity which allows reliable interconnection of distributed energy resources and loads and provides alternative way of their integration into power system. Due to its specifics, microgrids require different control strategies and dynamics of regulation as compared to ones used in conventional utility grids. All types of power converters used in microgrid share commonalities which potentially affect high frequency modes of microgrid in same manner. There are numerous unique design requirements imposed on microgrid tie inverters, which are dictated by the nature of …

The Hybridization Of A Graphene And Silicon Carbide Schottky Optoelectronic Device By The Incorporation Of A Lead Sulfide Quantum Dot Film, Joshua Letton

Theses and Dissertations

The work that follows examines the impact of lead sulfide quantum dots on a native epitaxial graphene (EG) SiC Schottky device, resulting in a hybrid optoelectronic device which presents a possible avenue towards a novel hybrid carbide-based Schottky solar cell. The active (n-type SiC) and contact (graphene) layers for the Schottky junction of the device were grown epitaxially using a novel technique incorporating tetrafluorosilane (TFS) as a precursor gas. The bare EG/SiC device was characterized based on its I-V behavior in dark and under illumination for both forward and reverse bias conditions. The initial characterization demonstrated the expected Schottky diode …

Monte Carlo Tree Search Applied To A Modified Pursuit/Evasion Scotland Yard Game With Rendezvous Spaceflight Operation Applications, Joshua A. Daughtery

Theses and Dissertations

This thesis takes the Scotland Yard board game and modifies its rules to mimic important aspects of space in order to facilitate the creation of artificial intelligence for space asset pursuit/evasion scenarios. Space has become a physical warfighting domain. To combat threats, an understanding of the tactics, techniques, and procedures must be captured and studied. Games and simulations are effective tools to capture data lacking historical context. Artificial intelligence and machine learning models can use simulations to develop proper defensive and offensive tactics, techniques, and procedures capable of protecting systems against potential threats. Monte Carlo Tree Search is a bandit-based …

A Hardware-In-The-Loop Platform For Dc Protection, Mark Vygoder

Theses and Dissertations

With the proliferation of power electronics, dc-based power distribution systems can be realized; however, dc electrical protection remains a significant barrier to mass implementation dc power distribution. Controller Hardware-in-the-loop (CHiL) simulation enables moving up technology readiness levels (TRL) quickly. This work presents an end-to-end solution for dc protection CHiL for early design exploration and verification for dc protection, allowing for the rapid development of dc protection schemes for both Line-to-Line (LL) and Line-to-Ground (LG) faults. The approach combines using Latency Based Linear Multistep Compound (LB-LMC), a real-time simulation method for power electronic, and National Instruments (NI) FPGA hardware to enable …

Power Electronic Architecture For Multi-Vehicle Extreme Fast Charging Stations, Nicholas Hoeft

Theses and Dissertations

Electric vehicles (EV) are quickly gaining popularity but limited driving range and a lack of fast charging infrastructure are preventing widespread use when compared with gas powered vehicles. This gave rise to the concept of multi-vehicle extreme fast charging (XFC) stations. Extreme fast charging imposes challenges in the forms of power delivery, battery management, and energy dispatch. The extreme load demand must be handled in such a way that users may receive a timely charge with minimal impacts on the electric grid. Power electronics are implemented to address these challenges with highly power dense and efficient solutions. This work explores …

Quantitative Optical Imaging Of Metabolic And Structural Biomarkers In Rodent Injury Models, Shima Mehrvar

Theses and Dissertations

The assessment of organ metabolic function using optical imaging techniques is an overgrowing field of disease diagnosis. The broad research objective of my PhD thesis is to detect quantitative biomarkers by developing and applying optical imaging and image processing tools to animal models of human diseases. To achieve this goal, I have designed and implemented an optical imaging instrument called in vivo fluorescence imager to study wound healing progress. I have also developed a 3-dimensional (3D) vascular segmentation technique that uses intrinsic fluorescence images of whole organs.

Intrinsic fluorophores (autofluorescence signals) provide information about the status of cellular bioenergetics in …

Medical Image Segmentation With Deep Learning, Chuanbo Wang

Theses and Dissertations

Medical imaging is the technique and process of creating visual representations of the body of a patient for clinical analysis and medical intervention. Healthcare professionals rely heavily on medical images and image documentation for proper diagnosis and treatment. However, manual interpretation and analysis of medical images is time-consuming, and inaccurate when the interpreter is not well-trained. Fully automatic segmentation of the region of interest from medical images have been researched for years to enhance the efficiency and accuracy of understanding such images. With the advance of deep learning, various neural network models have gained great success in semantic segmentation and …

Near Real-Time Zigbee Device Discrimination Using Cb-Dna Features, Yousuke Z. Matsui

Theses and Dissertations

Currently, Low-Rate Wireless Personal Area Networks (LR-WPAN) based on the Institute of Electrical and Electronics Engineers (IEEE) 802.15.4 standard are at risk due to open-source tools which allow bad actors to exploit unauthorized network access through various cyberattacks by falsifying bit-level credentials. This research investigates implementing a Radio Frequency (RF) air monitor to perform Near RealTime (NRT) discrimination of Zigbee devices using the IEEE 802.15.4 standard. The air monitor employed a Multiple Discriminant Analysis/Euclidean Distance classifier to discriminate Zigbee devices based upon Constellation-Based Distinct Native Attribute (CB-DNA) fingerprints. Through the use of CB-DNA fingerprints, Physical Layer (PHY) characteristics unique to …

A Non-Destructive Evaluation Application Using Software Defined Radios And Bandwidth Expansion, Nicholas J. O'Brien

Theses and Dissertations

The development of low-complexity, lightweight and low-cost Non-Destructive Evaluation (NDE) equipment for microwave device testing is desirable from a maintenance efficiency and operational availability perspective. Current NDE equipment tends to be custom-designed, cumbersome and expensive. Software Defined Radio (SDR) technology, and a bandwidth expansion technique that exploits a priori transmit signal knowledge and auto-correlation provides a solution. This research investigated the reconstruction of simultaneous SDR receiver instantaneous bandwidth (sub-band) collections using single, dual and multiple SDR receivers. The adjacent sub-bands, collectively spanning a transmit signal bandwidth were auto-correlated with a replica transmit signal to restore frequency and phase offsets. The …

Characterization And Sensitivity Analysis Of 6 Meter Cassegrain Antenna, James L. Harris

Theses and Dissertations

This paper will characterize a 6 meter in diameter cassegrain antenna. The cassegrain antenna is a special form of a dual reflector antenna which uses a main reflector following a parabolic curve and a sub reflector which follows a hyperbolic curve. Cassegrain style antennas have multiple parameters which can be tuned to achieve specific design goals. Performing a sensitivity analysis will establish relationships between design parameters, directivity, side lobe levels, and effects of strut geometry. The initial design parameters will be assumed based on typical values. Results from the sensitivity analysis will be used to provide a performance band for …

Development Of A Drone-Mounted Wireless Attack Platform, Nathan V. Barker

Theses and Dissertations

The commercial drone market has grown rapidly due to the increasing utility and capabilities of drones. This new found popularity has made it possible for inexpensive drones capable of impressive carry capacities and flight times to reach the consumer market. These new features also offer an invaluable resource to wireless hackers. Capitalizing on their mobility, a wireless hacker can equip a drone with hacking tools to surpass physical security (e.g. fences) with relative ease and reach wireless networks. This research seeks to experimentally evaluate the ability of a drone-mounted wireless attack platform equipped with a directional antenna to conduct wireless …

Improved Ground-Based Monocular Visual Odometry Estimation Using Inertially-Aided Convolutional Neural Networks, Josiah D. Watson

Theses and Dissertations

While Convolutional Neural Networks (CNNs) can estimate frame-to-frame (F2F) motion even with monocular images, additional inputs can improve Visual Odometry (VO) predictions. In this thesis, a FlowNetS-based [1] CNN architecture estimates VO using sequential images from the KITTI Odometry dataset [2]. For each of three output types (full six degrees of freedom (6-DoF), Cartesian translation, and transitional scale), a baseline network with only image pair input is compared with a nearly identical architecture that is also given an additional rotation estimate such as from an Inertial Navigation System (INS). The inertially-aided networks show an order of magnitude improvement over the …