UMD Theses and Dissertations
Permanent URI for this collectionhttp://hdl.handle.net/1903/3
New submissions to the thesis/dissertation collections are added automatically as they are received from the Graduate School. Currently, the Graduate School deposits all theses and dissertations from a given semester after the official graduation date. This means that there may be up to a 4 month delay in the appearance of a given thesis/dissertation in DRUM.
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Item Influence of Noise on Response Localizations in Mechanical Oscillator Arrays(2022) Cilenti, Lautaro Daniel; Balachandran, Balakumar; Cameron, Maria; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The dynamics of mechanical systems such as turbomachinery and vibration energy harvesting systems (VEH) consisting of one or multiple cantilever structures is often modeled by arrays of periodically driven coupled nonlinear oscillators. It is known that such systems may have multiple stable vibration steady states. Some of these steady states are localized vibrations that are characterized by high amplitude vibrations of a subset of the system, with the rest of the system being in a state of either low amplitude vibrations or no vibrations. On one hand, these localized vibrations can be detrimental to mechanical integrity of turbomachinery, while on the other hand, the vibrations can be potentially desirable for increasing energy yield in VEHs. Transitions into or out of localized vibrations may occur under the influence of random factors. A combination of experimental and numerical studies has been performed in this dissertation to study the associated transition times and probability of transitions in these mechanical systems. The developments reported here include the following: (i) a numerical methodology based on the Path Integral Method to quantify the probability of transitions due to noise, (ii) a numerical methodology based on the Action Plot Method to quantify the quasipotential and most probable transition paths in nonlinear systems with periodic external excitations, and (iii) experimental evidence and stochastic simulations of the influence of noise on response localizations of rotating macro-scale cantilever structures. The methodology and results discussed in this dissertation provide insights relevant to the stochastic nonlinear dynamics community, and more broadly, designers of mechanical systems to avoid potentially undesirable stochastic nonlinear behavior.Item Coupled Oscillator Arrays: Dynamics and Influence of Noise(2021) Alofi, Abdulrahman Mohammed; Balachandran, Balakumar; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Coupled oscillator arrays can be used to model several natural systems and engineering systems including mechanical systems. In this dissertation work, the influence of noise on the dynamics of coupled mono-stable oscillators arrays is investigated by using numerical and experimental methods. This work is an extension of recent efforts, including those at the University of Maryland, on the use of noise to alter a nonlinear system's response. A chain of coupled oscillators is of interest for this work. This dissertation research is guided by the following questions: i) how can noise be used to create or quench spatial energy localization in a system of coupled, nonlinear oscillators? and ii) how can noise be used to move the energy localization from one oscillator to another? The coupled oscillator systems of interest were harmonically excited and found experimentally and numerically to have a multi-stability region (MR) in the respective frequency response curves. Relative to this region, it has been found that the influence of noise depends highly on the excitation frequency location in the MR. Near either end of the MR, the oscillator responses were found to be sensitive to noise addition in the input and it was observed that the change in system dynamics through movement amongst the stable branches in the deterministic system could be anticipated from the corresponding frequency response curves. The system response is found to be robust to the influence of noise as the excitation frequency is shifted toward the middle of the MR. Also, the effects of noise on different response modes of the coupled oscillators arrays were investigated. A method for predicting the behavior is based on so-called basins of attractions of high dimensional systems. Through the findings of this work, many unique noise influenced phenomena are found, including spatial movement of an energy localization to a neighboring oscillator, response movement gradually up the energy branches, and generation of energy cascades from a localized mode.Item Covariance Localization in Strongly Coupled Data Assimilation(2019) Yoshida, Takuma; Kalnay, Eugenia; Penny, Stephen G; Atmospheric and Oceanic Sciences; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The recent development of accurate coupled models of the Earth system and enhanced computation power have enabled numerical prediction with the coupled models in weather, sub-seasonal, seasonal, and interannual time scales as well as climate projection. In the shorter timescales, the initial condition, or the estimate of the present state of the system, is essential for accurate prediction. Coupled data assimilation (DA) based on an ensemble of forecasts seems to be a promising approach for this state estimate due to its inherent ability to estimate flow-dependent error covariance. Strongly coupled DA tries to incorporate more observations of the other subsystems into an analysis (e.g., ocean observations into the atmospheric analysis) using the coupled error covariances; the covariance is estimated with a finite ensemble, and spurious covariance must be eliminated by localization. Because the coupling strength between subsystems of the Earth is not a simple function of a distance, we develop a better localization strategy than the distance-dependent localization. Based on the estimated benefit of each observation into each analysis variable, we first propose the correlation-cutoff method, where localization of strongly coupled DA is guided by ensemble correlations of an offline DA cycle. The method achieves improved analysis accuracy when tested with a simple coupled model of the atmosphere and ocean. As a related topic, error growth and predictability of a coupled dynamical system with multiple timescales are explored using a simple chaotic model of the atmosphere and ocean. A discontinuous response of the attractor's characteristics to the coupling strength is reported. The characteristic of global atmosphere-ocean coupled error correlation is investigated using two sets of ensemble DA systems. This knowledge is essential for effectively implementing global strongly coupled atmosphere-ocean DA. We report and discuss common and uncommon features, and the importance of ocean model resolution is stressed. Finally, the correlation-cutoff method is realized for global atmosphere-ocean strongly coupled DA with neural networks. The combination of static information provided by the neural networks and flow-dependent error covariance estimated by the ensemble improves the atmospheric analysis in our proof-of-concept experiment. The neural networks' ability to reproduce the error statistics, computation cost in a DA system, as well as analysis quality are evaluated.Item Microwave Photos in High Impedance Transmission line: Dispersion, Disorder and Localization(2017) Mehta, Nitish Jitendrakumar; Murphy, Thomas E; Manucharyan, Vladimir E; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)In this thesis we will describe the theoretical and experimental studies of a TEM on-chip superconducting transmission line with a wave impedance as high as 20 $\mathrm{k}\Omega$, phase and group velocity of waves simultaneously reduced by a factor of 100 in a broad range of frequencies from 0 to about 10 $\mathrm{GHz}$. A conventional microwave coaxial transmission line gets its inductance and capacitance from magnetic and electric fields stored in the space between its inner and outer conductors. This in turn limits its impedance to around 50 $\Omega$ and group velocity of waves very close to the speed of light in vacuum. In this work we are able to increase the impedance by over two orders of magnitude and reduce the group and phase velocity of waves by over two orders of magnitude as well, by constructing a coplanar transmission line out of a pair of long Al/AlOx/Al Josephson tunnel junction chains. A Josephson junction gets its inductance not from the magnetic energy but rather from the much larger kinetic energy of tunneling Cooper pairs, which is unrelated to the electromagnetic properties of vacuum. In this work we present a design of such a transmission line and low-temperature measurement of its dispersion relation. We then study and characterize the disorder present in the circuit parameters of our system and using this, we conclude that for frequencies up to 12 GHz, there is no evidence of Anderson localization of waves, even for chains exceeding 30,000 junctions. Low dissipation and absence of localization make this transmission line ideal for use in various experiments where high impedance can enable strong coupling between light and matter.Item TIME AND LOCATION FORENSICS FOR MULTIMEDIA(2013) Garg, Ravi; Wu, Min; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)In the modern era, a vast quantities of digital information is available in the form of audio, image, video, and other sensor recordings. These recordings may contain metadata describing important information such as the time and the location of recording. As the stored information can be easily modified using readily available digital editing software, determining the authenticity of a recording has utmost importance, especially for critical applications such as law enforcement, journalism, and national and business intelligence. In this dissertation, we study novel environmental signatures induced by power networks, which are known as Electrical Network Frequency (ENF) signals and become embedded in multimedia data at the time of recording. ENF fluctuates slightly over time from its nominal value of 50 Hz/60 Hz. The major trend of fluctuations in the ENF remains consistent across the entire power grid, including when measured at physically distant geographical locations. We investigate the use of ENF signals for a variety of applications such as estimation/verification of time and location of a recording's creation, and develop a theoretical foundation to support ENF based forensic analysis. In the first part of the dissertation, the presence of ENF signals in visual recordings captured in electric powered lighting environments is demonstrated. The source of ENF signals in visual recordings is shown to be the invisible flickering of indoor lighting sources such as fluorescent and incandescent lamps. The techniques to extract ENF signals from recordings demonstrate that a high correlation is observed between the ENF fluctuations obtained from indoor lighting and that from the power mains supply recorded at the same time. Applications of the ENF signal analysis to tampering detection of surveillance video recordings, and forensic binding of the audio and visual track of a video are also discussed. In the following part, an analytical model is developed to gain an understanding of the behavior of ENF signals. It is demonstrated that ENF signals can be modeled using a time-varying autoregressive process. The performance of the proposed model is evaluated for a timestamp verification application. Based on this model, an improved algorithm for ENF matching between a reference signal and a query signal is provided. It is shown that the proposed approach provides an improved matching performance as compared to the case when matching is performed directly on ENF signals. Another application of the proposed model in learning the power grid characteristics is also explicated. These characteristics are learnt by using the modeling parameters as features to train a classifier to determine the creation location of a recording among candidate grid-regions. The last part of the dissertation demonstrates that differences exist between ENF signals recorded in the same grid-region at the same time. These differences can be extracted using a suitable filter mechanism and follow a relationship with the distance between different locations. Based on this observation, two localization protocols are developed to identify the location of a recording within the same grid-region, using ENF signals captured at anchor locations. Localization accuracy of the proposed protocols are then compared. Challenges in using the proposed technique to estimate the creation location of multimedia recordings within the same grid, along with efficient and resilient trilateration strategies in the presence of outliers and malicious anchors, are also discussed.