A. James Clark School of Engineering

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The collections in this community comprise faculty research works, as well as graduate theses and dissertations.

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    DATA-DRIVEN STUDIES OF TRANSIENT EVENTS AND APERIODIC MOTIONS
    (2019) Wang, Rui; Balachandran, Balakumar; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    The era of big data, high-performance computing, and machine learning has witnessed a paradigm shift from physics-based modeling to data-driven modeling across many scientific fields. In this dissertation work, transient events and aperiodic motions of complex nonlinear dynamical system are studied with the aid of a data- driven modeling approach. The goal of the work has been to further the ability for future behavior prediction, state estimation, and control of related behaviors. It is shown that data on extreme waves can be used to carry out stability analysis and ascertain the nature of the transient phenomenon. In addition, it is demonstrated that a low number of soliton elements can be used to realize a rogue wave on the basis of nonlinear interactions amongst the basic elements. The pro- posed nonlinear phase interference model provides an appealing explanation for the formation of ocean extreme wave and related statistics, and a superior reconstruction of the Draupner wave event than that obtained on the basis of linear superposition. Chaotic data, another manifestation of aperiodic motions, which are obtained from prototypical ordinary differential and partial differential systems are considered and a neural machine is realized to predict the corresponding responses based on a limited training set as well to forecast the system behavior. A specific neural architecture, called the inhibitor mechanism, has been designed to enable chaotic time series forecasting. Without this mechanism, even the short-term predictions would be intractable. Both autonomous and non-autonomous dynamical systems have been studied to demonstrate the long-term forecasting possibilities with the de- veloped neural machine. For each dynamical system considered in this dissertation, a long forecasting horizon is achieved with a short historical data set. Furthermore, with the developed neural machine, one can relax the requirement of continuous historical data measurements, thus, providing for a more pragmatic approach than the previous approaches available in the literature. It is expected that the efforts of this dissertation work will lead to a better understanding of the underlying mechanism of transient and aperiodic events in complex systems and useful techniques for forecasting their future occurrences.
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    Role of feed protocol in achieving chaotic mixing of highly filled flow systems during filling the empty cavity
    (2006-03-27) Huang, Yue; Bigio, David I; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Chaotic mixing of highly filled viscous fluids is desired but hardly achieved in the electronic packaging industries. The demand for high reliability found in electronic package attracts more and more researchers to study the properties and distribution of binders and filler particles. These will affect properties such as coefficient of thermal expansion and stiffness. Both of these contribute strongly to reliability. The filler concentration, size distribution and spatial distribution must be examined in a structured manner to understand their effects on final properties. However, most studies deal with filler concentration and size distribution, while very few studies have tied the particle spatial distribution to the properties. It is not enough to just properly control the filler concentration and size distribution. The more uniform filler distribution, the more uniform are local properties, and this can be achieved by well-designed mixing processes. Mixing is very important and in many cases the goodness of the mixing of fillers will affect or determine the properties of the products. In this thesis, the local properties of electronic package and their relations with filler particle distribution are quantified. For the first time, a new feed protocol that can generate chaotic mixing during filling cavity by implementing periodic and aperiodic filling process is presented. Instead of using single gate in the molding process, we have developed a two-gate feeding protocol. A numerical simulation experiment is conducted on a 2-D square cavity to examine the mixing of polymer fluid in low Reynolds number flows. Since there are a vast number of geometries in electronic packages, only cavities with 46 and 49 bumps, which can be treated as solder balls or leadframe, is investigated. Periodic and aperiodic feed protocols resulted in exponential growth of the distance between two adjacent particles, an indication of chaotic mixing. Entropic study shows that the global mixing has been improved 858% compared to single gate feeding. The improved properties and reliability could be foreseen in electronic package.
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    Private Communications with Chaotic Code Division Multiple Access: Performance Analysis and System Design
    (2004-08-04) Hwang, Yeong-Sun; Papadopoulos, Haralabos C; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    In this dissertation we develop a class of pseudochaotic direct-sequence code division multiple access (DS/CDMA) systems that can provide private and reliable communication over wireless channels. These systems exploit the sensitive dependence of chaotic sequences on initial conditions together with the presence of channel noise to provide a substantial gap between the bit error probabilities achievable by intended and unintended receivers. We illustrate how a desired level of private communication can be achieved with a systematic selection of the system parameters. This type of privacy can be readily combined with traditional encryption methods to further ensure the protection of information against eavesdroppers. The systems we propose employ linear modulation of each user's symbol stream on a spreading sequence generated by iterating a distinct initial condition through a pseudochaotic map. We evaluate and compare the uncoded probability of error (Pr(e)) achievable by intended receivers that know the initial condition used to generate the spreading sequence to the associated Pr(e) of unintended receivers that know the modulation scheme but not the initial condition. We identify the map attributes that affect privacy, and construct algorithmic design methods for generating pseudochaotic spreading sequences that successively and substantially degrade the unintended user performance, while yielding intended user performance similar to that of conventional DS/CDMA systems. We develop efficient metrics for quantifying the unintended receiver Pr(e) and prove that it decays at a constant rate of 1/sqrt(SNR) in AWGN and fading channels. In addition, we show that this decaying rate is independent of the available degrees of diversity in fading channels, showing in the process that only intended receivers can harvest the available diversity benefits. Moreover, we illustrate that the pseudochaotic DS/CDMA systems can provide reliable multiuser communication that is inherently resilient to eavesdropping, even in the worst-case scenarios where all receivers in a network except the intended one collude to better eavesdrop on the targeted transmission. We also develop optimized digital implementation methods for generating practical pseudochaotic spreading sequences that preserve the privacy characteristics associated with the underlying chaotic spreading sequences.