Engineering Commons^™

Resonant Acoustic Wave Assisted Spin-Transfer-Torque Switching Of Nanomagnets, Austin R. Roe

Theses and Dissertations

We studied the possibility of achieving an order of magnitude reduction in the energy dissipation needed to write bits in perpendicular magnetic tunnel junctions (p-MTJs) by simulating the magnetization dynamics under a combination of resonant surface acoustic waves (r-SAW) and spin-transfer-torque (STT). The magnetization dynamics were simulated using the Landau-Lifshitz-Gilbert equation under macrospin assumption with the inclusion of thermal noise. We studied such r-SAW assisted STT switching of nanomagnets for both in-plane elliptical and circular perpendicular magnetic anisotropy (PMA) nanomagnets and show that while thermal noise affects switching probability in in-plane nanomagnets, the PMA nanomagnets are relatively robust to the …

Electric Load Forecasting Using Long Short-Term Memory Algorithm, Tianshu Yang

Theses and Dissertations

Abstract

Power system load forecasting refers to the study or uses a mathematical method to process

past and future loads systematically, taking into account important system operating

characteristics, capacity expansion decisions, natural conditions, and social impacts, to

meet specific accuracy requirements. Dependence of this, determine the load value at a

specific moment in the future. Improving the level of load forecasting technology is

conducive to the planned power management, which is conducive to rationally arranging

the grid operation mode and unit maintenance plan, and is conducive to formulating

reasonable power supply construction plans and facilitating power improvement, and

improve the …

Optically Transparent Antennas And Filters For Smart City Communication, Ryan B. Green

Theses and Dissertations

Incremental usage of mobile devices demand a new generation of wireless networks (5G) to provide faster data rates, more reliable coverage, monitor city infrastructure usage, and increase network capacity. The frequencies proposed for the upcoming 5G network would result in shorter broadcast distances and network dead zones, countered by incorporating transparent antennas into glass high rises. Transparent antennas possess, however a major challenge: low gain. This lower gain can be countered by means of employing antennas in an antenna array, boosting the gain and even giving the array the ability to beam form for the upcoming 5G network. The 5G …

Load Scheduling With Maximum Demand And Time Of Use Pricing For Microgrids, Hayder O. Alwan

Theses and Dissertations

Several demand side management (DSM) techniques and algorithms have been used in the literature. These algorithms show that by adopting DSM and Time-of-Use (TOU) price tariffs; electricity cost significantly decreases, and optimal load scheduling is achieved. However, the purpose of the DSM is to not only lower the electricity cost, but also to avoid the peak load even if the electricity prices low. To address this concern, this dissertation starts with a brief literature review on the existing DSM algorithms and schemes. These algorithms can be suitable for Direct Load Control (DLC) schemes, Demand Response (DR), and load scheduling strategies. …

The Application Of Index Based, Region Segmentation, And Deep Learning Approaches To Sensor Fusion For Vegetation Detection, David L. Stone

Theses and Dissertations

This thesis investigates the application of index based, region segmentation, and deep learning methods to the sensor fusion of omnidirectional (O-D) Infrared (IR) sensors, Kinnect sensors, and O-D vision sensors to increase the level of intelligent perception for unmanned robotic platforms. The goals of this work is first to provide a more robust calibration approach and improve the calibration of low resolution and noisy IR O-D cameras. Then our goal was to explore the best approach to sensor fusion for vegetation detection. We looked at index based, region segmentation, and deep learning methods and compared them with a goal of …

Multi-Column Neural Networks And Sparse Coding Novel Techniques In Machine Learning, Ammar O. Hoori

Theses and Dissertations

Accurate and fast machine learning (ML) algorithms are highly vital in artificial intelligence (AI) applications. In complex dataset problems, traditional ML methods such as radial basis function neural network (RBFN), sparse coding (SC) using dictionary learning, and particle swarm optimization (PSO) provide trivial results, large structure, slow training, and/or slow testing. This dissertation introduces four novel ML techniques: the multi-column RBFN network (MCRN), the projected dictionary learning algorithm (PDL) and the multi-column adaptive and non-adaptive particle swarm optimization techniques (MC-APSO and MC-PSO). These novel techniques provide efficient alternatives for traditional ML techniques. Compared to traditional ML techniques, the novel ML …

Secure State Estimation In The Presence Of False Information Injection Attacks, Maitham Alsalman

Theses and Dissertations

In this dissertation, we first investigate the problem of source location estimation in wireless sensor networks (WSNs) based on quantized data in the presence of false information attacks. Using a Gaussian mixture to model the possible attacks, we develop a maximum likelihood estimator (MLE) to estimate the source location. The Cramer-Rao lower bound (CRLB) for this estimation problem is also derived.

Then, the assumption that the fusion center does not have the knowledge of the attack probability and the attack noise power investigated. We assume that the attack probability and power are random variables which follow certain uniform distributions. We …

Sensor Placement For Damage Localization In Sensor Networks, Fereshteh Firouzi

Theses and Dissertations

The objective of this thesis is to formulate and solve the sensor placement problem for damage localization in a sensor network. A Bayesian estimation problem is formulated with the time-of-flight (ToF) measurements. In this model, ToF of lamb waves, which are generated and received by piezoelectric sensors, is the total time for each wave to be transmitted, reflected by the target, and received by the sensor. The ToF of the scattered lamb wave has characteristic information about the target location. By using the measurement model and prior information, the target location is estimated in a centralized sensor network with a …

Straintronic Nanomagnetic Devices For Non-Boolean Computing, Md Ahsanul Abeed

Theses and Dissertations

Nanomagnetic devices have been projected as an alternative to transistor-based switching devices due to their non-volatility and potentially superior energy-efficiency. The energy efficiency is enhanced by the use of straintronics which involves the application of a voltage to a piezoelectric layer to generate a strain which is ultimately transferred to an elastically coupled magnetostrictive nanomaget, causing magnetization rotation. The low energy dissipation and non-volatility characteristics make straintronic nanomagnets very attractive for both Boolean and non-Boolean computing applications. There was relatively little research on straintronic switching in devices built with real nanomagnets that invariably have defects and imperfections, or their adaptation …

Energy Efficient Spintronic Device For Neuromorphic Computation, Md Ali Azam

Theses and Dissertations

Future computing will require significant development in new computing device paradigms. This is motivated by CMOS devices reaching their technological limits, the need for non-Von Neumann architectures as well as the energy constraints of wearable technologies and embedded processors. The first device proposal, an energy-efficient voltage-controlled domain wall device for implementing an artificial neuron and synapse is analyzed using micromagnetic modeling. By controlling the domain wall motion utilizing spin transfer or spin orbit torques in association with voltage generated strain control of perpendicular magnetic anisotropy in the presence of Dzyaloshinskii-Moriya interaction (DMI), different positions of the domain wall are realized …

Fabrication And Simulation Of Nanomagnetic Devices For Information Processing, Justine L. Drobitch

Theses and Dissertations

Nanomagnetic devices are highly energy efficient and non-volatile. Because of these two attributes, they are potential replacements to many currently used information processing technologies, and they have already been implemented in many different applications. This dissertation covers a study of nanomagnetic devices and their applications in various technologies for information processing – from simulating and analyzing the mechanisms behind the operation of the devices, to experimental investigations encompassing magnetic film growth for device components to nanomagnetic device fabrication and measurement of their performance.

Theoretical sections of this dissertation include simulation-based modeling of perpendicular magnetic anisotropy magnetic tunnel junctions (p-MTJ) and …

Modeling Cascading Failures In Power Systems In The Presence Of Uncertain Wind Generation, Mir Hadi Athari

Theses and Dissertations

One of the biggest threats to the power systems as critical infrastructures is large-scale blackouts resulting from cascading failures (CF) in the grid. The ongoing shift in energy portfolio due to ever-increasing penetration of renewable energy sources (RES) may drive the electric grid closer to its operational limits and introduce a large amount of uncertainty coming from their stochastic nature. One worrisome change is the increase in CFs.

The CF simulation models in the literature do not allow consideration of RES penetration in studying the grid vulnerability. In this dissertation, we have developed tools and models to evaluate the impact …