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- Genre: Academic theses
- Creators: Tepedelenlioğlu, Cihan
- Creators: Jiang, Hanqing
- Resource Type: Text
Description
Recently, the use of zinc oxide (ZnO) nanowires as an interphase in composite materials has been demonstrated to increase the interfacial shear strength between carbon fiber and an epoxy matrix. In this research work, the strong adhesion between ZnO and carbon fiber is investigated to elucidate the interactions at the interface that result in high interfacial strength. First, molecular dynamics (MD) simulations are performed to calculate the adhesive energy between bare carbon and ZnO. Since the carbon fiber surface has oxygen functional groups, these were modeled and MD simulations showed the preference of ketones to strongly interact with ZnO, however, this was not observed in the case of hydroxyls and carboxylic acid. It was also found that the ketone molecules ability to change orientation facilitated the interactions with the ZnO surface. Experimentally, the atomic force microscope (AFM) was used to measure the adhesive energy between ZnO and carbon through a liftoff test by employing highly oriented pyrolytic graphite (HOPG) substrate and a ZnO covered AFM tip. Oxygen functionalization of the HOPG surface shows the increase of adhesive energy. Additionally, the surface of ZnO was modified to hold a negative charge, which demonstrated an increase in the adhesive energy. This increase in adhesion resulted from increased induction forces given the relatively high polarizability of HOPG and the preservation of the charge on ZnO surface. It was found that the additional negative charge can be preserved on the ZnO surface because there is an energy barrier since carbon and ZnO form a Schottky contact. Other materials with the same ionic properties of ZnO but with higher polarizability also demonstrated good adhesion to carbon. This result substantiates that their induced interaction can be facilitated not only by the polarizability of carbon but by any of the materials at the interface. The versatility to modify the magnitude of the induced interaction between carbon and an ionic material provides a new route to create interfaces with controlled interfacial strength.
ContributorsGalan Vera, Magdian Ulises (Author) / Sodano, Henry A (Thesis advisor) / Jiang, Hanqing (Committee member) / Solanki, Kiran (Committee member) / Oswald, Jay (Committee member) / Speyer, Gil (Committee member) / Arizona State University (Publisher)
Created2013
Description
Practical communication systems are subject to errors due to imperfect time alignment among the communicating nodes. Timing errors can occur in different forms depending on the underlying communication scenario. This doctoral study considers two different classes of asynchronous systems; point-to-point (P2P) communication systems with synchronization errors, and asynchronous cooperative systems. In particular, the focus is on an information theoretic analysis for P2P systems with synchronization errors and developing new signaling solutions for several asynchronous cooperative communication systems. The first part of the dissertation presents several bounds on the capacity of the P2P systems with synchronization errors. First, binary insertion and deletion channels are considered where lower bounds on the mutual information between the input and output sequences are computed for independent uniformly distributed (i.u.d.) inputs. Then, a channel suffering from both synchronization errors and additive noise is considered as a serial concatenation of a synchronization error-only channel and an additive noise channel. It is proved that the capacity of the original channel is lower bounded in terms of the synchronization error-only channel capacity and the parameters of both channels. On a different front, to better characterize the deletion channel capacity, the capacity of three independent deletion channels with different deletion probabilities are related through an inequality resulting in the tightest upper bound on the deletion channel capacity for deletion probabilities larger than 0.65. Furthermore, the first non-trivial upper bound on the 2K-ary input deletion channel capacity is provided by relating the 2K-ary input deletion channel capacity with the binary deletion channel capacity through an inequality. The second part of the dissertation develops two new relaying schemes to alleviate asynchronism issues in cooperative communications. The first one is a single carrier (SC)-based scheme providing a spectrally efficient Alamouti code structure at the receiver under flat fading channel conditions by reducing the overhead needed to overcome the asynchronism and obtain spatial diversity. The second one is an orthogonal frequency division multiplexing (OFDM)-based approach useful for asynchronous cooperative systems experiencing excessive relative delays among the relays under frequency-selective channel conditions to achieve a delay diversity structure at the receiver and extract spatial diversity.
ContributorsRahmati, Mojtaba (Author) / Duman, Tolga M. (Thesis advisor) / Zhang, Junshan (Committee member) / Tepedelenlioğlu, Cihan (Committee member) / Reisslein, Martin (Committee member) / Arizona State University (Publisher)
Created2013
Description
Global Positioning System (GPS) is a navigation system widely used in civilian and military application, but its accuracy is highly impacted with consequential fading, and possible loss of communication due to multipath propagation and high power interferences. This dissertation proposes alternatives to improve the performance of the GPS receivers to obtain a system that can be reliable in critical situations. The basic performance of the GPS receiver consists of receiving the signal with an antenna array, delaying the signal at each antenna element, weighting the delayed replicas, and finally, combining the weighted replicas to estimate the desired signal. Based on these, three modifications are proposed to improve the performance of the system. The first proposed modification is the use of the Least Mean Squares (LMS) algorithm with two variations to decrease the convergence time of the classic LMS while achieving good system stability. The results obtained by the proposed LMS demonstrate that the algorithm can achieve the same stability as the classic LMS using a small step size, and its convergence rate is better than the classic LMS using a large step size. The second proposed modification is to replace the uniform distribution of the time delays (or taps) by an exponential distribution that decreases the bit-error rate (BER) of the system without impacting the computational efficiency of the uniform taps. The results show that, for a BER of 0.001, the system can operate with a 1 to 2 dB lower signal-to-noise ratio (SNR) when an exponential distribution is used rather than a uniform distribution. Finally, the third modification is implemented in the design of the antenna array. In this case, the gain of each microstrip element is enhanced by embedding ferrite rings in the substrate, creating a hybrid substrate. The ferrite rings generates constructive interference between the incident and reflected fields; consequently, the gain of a single microstrip element is enhanced by up to 4 dB. When hybrid substrates are used in microstrip element arrays, a significant enhancement in angle range is achieved for a given reflection coefficient compared to using a conventional substrate.
ContributorsRivera-Albino, Alix (Author) / Balanis, Constantine A (Thesis advisor) / Tepedelenlioğlu, Cihan (Committee member) / Kiaei, Sayfe (Committee member) / Aberle, James T (Committee member) / Arizona State University (Publisher)
Created2013
Description
The processing power and storage capacity of portable devices have improved considerably over the past decade. This has motivated the implementation of sophisticated audio and other signal processing algorithms on such mobile devices. Of particular interest in this thesis is audio/speech processing based on perceptual criteria. Specifically, estimation of parameters from human auditory models, such as auditory patterns and loudness, involves computationally intensive operations which can strain device resources. Hence, strategies for implementing computationally efficient human auditory models for loudness estimation have been studied in this thesis. Existing algorithms for reducing computations in auditory pattern and loudness estimation have been examined and improved algorithms have been proposed to overcome limitations of these methods. In addition, real-time applications such as perceptual loudness estimation and loudness equalization using auditory models have also been implemented. A software implementation of loudness estimation on iOS devices is also reported in this thesis. In addition to the loudness estimation algorithms and software, in this thesis project we also created new illustrations of speech and audio processing concepts for research and education. As a result, a new suite of speech/audio DSP functions was developed and integrated as part of the award-winning educational iOS App 'iJDSP." These functions are described in detail in this thesis. Several enhancements in the architecture of the application have also been introduced for providing the supporting framework for speech/audio processing. Frame-by-frame processing and visualization functionalities have been developed to facilitate speech/audio processing. In addition, facilities for easy sound recording, processing and audio rendering have also been developed to provide students, practitioners and researchers with an enriched DSP simulation tool. Simulations and assessments have been also developed for use in classes and training of practitioners and students.
ContributorsKalyanasundaram, Girish (Author) / Spanias, Andreas S (Thesis advisor) / Tepedelenlioğlu, Cihan (Committee member) / Berisha, Visar (Committee member) / Arizona State University (Publisher)
Created2013
Description
Autonomous vehicle control systems utilize real-time kinematic Global Navigation Satellite Systems (GNSS) receivers to provide a position within two-centimeter of truth. GNSS receivers utilize the satellite signal time of arrival estimates to solve for position; and multipath corrupts the time of arrival estimates with a time-varying bias. Time of arrival estimates are based upon accurate direct sequence spread spectrum (DSSS) code and carrier phase tracking. Current multipath mitigating GNSS solutions include fixed radiation pattern antennas and windowed delay-lock loop code phase discriminators. A new multipath mitigating code tracking algorithm is introduced that utilizes a non-symmetric correlation kernel to reject multipath. Independent parameters provide a means to trade-off code tracking discriminant gain against multipath mitigation performance. The algorithm performance is characterized in terms of multipath phase error bias, phase error estimation variance, tracking range, tracking ambiguity and implementation complexity. The algorithm is suitable for modernized GNSS signals including Binary Phase Shift Keyed (BPSK) and a variety of Binary Offset Keyed (BOC) signals. The algorithm compensates for unbalanced code sequences to ensure a code tracking bias does not result from the use of asymmetric correlation kernels. The algorithm does not require explicit knowledge of the propagation channel model. Design recommendations for selecting the algorithm parameters to mitigate precorrelation filter distortion are also provided.
ContributorsMiller, Steven (Author) / Spanias, Andreas (Thesis advisor) / Tepedelenlioğlu, Cihan (Committee member) / Tsakalis, Konstantinos (Committee member) / Zhang, Junshan (Committee member) / Arizona State University (Publisher)
Created2013
Description
"Sensor Decade" has been labeled on the first decade of the 21st century. Similar to the revolution of micro-computer in 1980s, sensor R&D; developed rapidly during the past 20 years. Hard workings were mainly made to minimize the size of devices with optimal the performance. Efforts to develop the small size devices are mainly concentrated around Micro-electro-mechanical-system (MEMS) technology. MEMS accelerometers are widely published and used in consumer electronics, such as smart phones, gaming consoles, anti-shake camera and vibration detectors. This study represents liquid-state low frequency micro-accelerometer based on molecular electronic transducer (MET), in which inertial mass is not the only but also the conversion of mechanical movement to electric current signal is the main utilization of the ionic liquid. With silicon-based planar micro-fabrication, the device uses a sub-micron liter electrolyte droplet sealed in oil as the sensing body and a MET electrode arrangement which is the anode-cathode-cathode-anode (ACCA) in parallel as the read-out sensing part. In order to sensing the movement of ionic liquid, an imposed electric potential was applied between the anode and the cathode. The electrode reaction, I_3^-+2e^___3I^-, occurs around the cathode which is reverse at the anodes. Obviously, the current magnitude varies with the concentration of ionic liquid, which will be effected by the movement of liquid droplet as the inertial mass. With such structure, the promising performance of the MET device design is to achieve 10.8 V/G (G=9.81 m/s^2) sensitivity at 20 Hz with the bandwidth from 1 Hz to 50 Hz, and a low noise floor of 100 ug/sqrt(Hz) at 20 Hz.
ContributorsLiang, Mengbing (Author) / Yu, Hongyu (Thesis advisor) / Jiang, Hanqing (Committee member) / Kozicki, Micheal (Committee member) / Arizona State University (Publisher)
Created2013
Description
Distributed inference has applications in a wide range of fields such as source localization, target detection, environment monitoring, and healthcare. In this dissertation, distributed inference schemes which use bounded transmit power are considered. The performance of the proposed schemes are studied for a variety of inference problems. In the first part of the dissertation, a distributed detection scheme where the sensors transmit with constant modulus signals over a Gaussian multiple access channel is considered. The deflection coefficient of the proposed scheme is shown to depend on the characteristic function of the sensing noise, and the error exponent for the system is derived using large deviation theory. Optimization of the deflection coefficient and error exponent are considered with respect to a transmission phase parameter for a variety of sensing noise distributions including impulsive ones. The proposed scheme is also favorably compared with existing amplify-and-forward (AF) and detect-and-forward (DF) schemes. The effect of fading is shown to be detrimental to the detection performance and simulations are provided to corroborate the analytical results. The second part of the dissertation studies a distributed inference scheme which uses bounded transmission functions over a Gaussian multiple access channel. The conditions on the transmission functions under which consistent estimation and reliable detection are possible is characterized. For the distributed estimation problem, an estimation scheme that uses bounded transmission functions is proved to be strongly consistent provided that the variance of the noise samples are bounded and that the transmission function is one-to-one. The proposed estimation scheme is compared with the amplify and forward technique and its robustness to impulsive sensing noise distributions is highlighted. It is also shown that bounded transmissions suffer from inconsistent estimates if the sensing noise variance goes to infinity. For the distributed detection problem, similar results are obtained by studying the deflection coefficient. Simulations corroborate our analytical results. In the third part of this dissertation, the problem of estimating the average of samples distributed at the nodes of a sensor network is considered. A distributed average consensus algorithm in which every sensor transmits with bounded peak power is proposed. In the presence of communication noise, it is shown that the nodes reach consensus asymptotically to a finite random variable whose expectation is the desired sample average of the initial observations with a variance that depends on the step size of the algorithm and the variance of the communication noise. The asymptotic performance is characterized by deriving the asymptotic covariance matrix using results from stochastic approximation theory. It is shown that using bounded transmissions results in slower convergence compared to the linear consensus algorithm based on the Laplacian heuristic. Simulations corroborate our analytical findings. Finally, a robust distributed average consensus algorithm in which every sensor performs a nonlinear processing at the receiver is proposed. It is shown that non-linearity at the receiver nodes makes the algorithm robust to a wide range of channel noise distributions including the impulsive ones. It is shown that the nodes reach consensus asymptotically and similar results are obtained as in the case of transmit non-linearity. Simulations corroborate our analytical findings and highlight the robustness of the proposed algorithm.
ContributorsDasarathan, Sivaraman (Author) / Tepedelenlioğlu, Cihan (Thesis advisor) / Papandreou-Suppappola, Antonia (Committee member) / Reisslein, Martin (Committee member) / Goryll, Michael (Committee member) / Arizona State University (Publisher)
Created2013
Description
The field of education has been immensely benefited by major breakthroughs in technology. The arrival of computers and the internet made student-teacher interaction from different parts of the world viable, increasing the reach of the educator to hitherto remote corners of the world. The arrival of mobile phones in the recent past has the potential to provide the next paradigm shift in the way education is conducted. It combines the universal reach and powerful visualization capabilities of the computer with intimacy and portability. Engineering education is a field which can exploit the benefits of mobile devices to enhance learning and spread essential technical know-how to different parts of the world. In this thesis, I present AJDSP, an Android application evolved from JDSP, providing an intuitive and a easy to use environment for signal processing education. AJDSP is a graphical programming laboratory for digital signal processing developed for the Android platform. It is designed to provide utility; both as a supplement to traditional classroom learning and as a tool for self-learning. The architecture of AJDSP is based on the Model-View-Controller paradigm optimized for the Android platform. The extensive set of function modules cover a wide range of basic signal processing areas such as convolution, fast Fourier transform, z transform and filter design. The simple and intuitive user interface inspired from iJDSP is designed to facilitate ease of navigation and to provide the user with an intimate learning environment. Rich visualizations necessary to understand mathematically intensive signal processing algorithms have been incorporated into the software. Interactive demonstrations boosting student understanding of concepts like convolution and the relation between different signal domains have also been developed. A set of detailed assessments to evaluate the application has been conducted for graduate and senior-level undergraduate students.
ContributorsRanganath, Suhas (Author) / Spanias, Andreas (Thesis advisor) / Tepedelenlioğlu, Cihan (Committee member) / Tsakalis, Konstantinos (Committee member) / Arizona State University (Publisher)
Created2013
Description
A principal goal of this dissertation is to study stochastic optimization and real-time scheduling in cyber-physical systems (CPSs) ranging from real-time wireless systems to energy systems to distributed control systems. Under this common theme, this dissertation can be broadly organized into three parts based on the system environments. The first part investigates stochastic optimization in real-time wireless systems, with the focus on the deadline-aware scheduling for real-time traffic. The optimal solution to such scheduling problems requires to explicitly taking into account the coupling in the deadline-aware transmissions and stochastic characteristics of the traffic, which involves a dynamic program that is traditionally known to be intractable or computationally expensive to implement. First, real-time scheduling with adaptive network coding over memoryless channels is studied, and a polynomial-time complexity algorithm is developed to characterize the optimal real-time scheduling. Then, real-time scheduling over Markovian channels is investigated, where channel conditions are time-varying and online channel learning is necessary, and the optimal scheduling policies in different traffic regimes are studied. The second part focuses on the stochastic optimization and real-time scheduling involved in energy systems. First, risk-aware scheduling and dispatch for plug-in electric vehicles (EVs) are studied, aiming to jointly optimize the EV charging cost and the risk of the load mismatch between the forecasted and the actual EV loads, due to the random driving activities of EVs. Then, the integration of wind generation at high penetration levels into bulk power grids is considered. Joint optimization of economic dispatch and interruptible load management is investigated using short-term wind farm generation forecast. The third part studies stochastic optimization in distributed control systems under different network environments. First, distributed spectrum access in cognitive radio networks is investigated by using pricing approach, where primary users (PUs) sell the temporarily unused spectrum and secondary users compete via random access for such spectrum opportunities. The optimal pricing strategy for PUs and the corresponding distributed implementation of spectrum access control are developed to maximize the PU's revenue. Then, a systematic study of the nonconvex utility-based power control problem is presented under the physical interference model in ad-hoc networks. Distributed power control schemes are devised to maximize the system utility, by leveraging the extended duality theory and simulated annealing.
ContributorsYang, Lei (Author) / Zhang, Junshan (Thesis advisor) / Tepedelenlioğlu, Cihan (Committee member) / Xue, Guoliang (Committee member) / Ying, Lei (Committee member) / Arizona State University (Publisher)
Created2012
Description
Woven fabric composite materials are widely used in the construction of aircraft engine fan containment systems, mostly due to their high strength to weight ratios and ease of implementation. The development of a predictive model for fan blade containment would provide great benefit to engine manufactures in shortened development cycle time, less risk in certification and fewer dollars lost to redesign/recertification cycles. A mechanistic user-defined material model subroutine has been developed at Arizona State University (ASU) that captures the behavioral response of these fabrics, namely Kevlar® 49, under ballistic loading. Previously developed finite element models used to validate the consistency of this material model neglected the effects of the physical constraints imposed on the test setup during ballistic testing performed at NASA Glenn Research Center (NASA GRC). Part of this research was to explore the effects of these boundary conditions on the results of the numerical simulations. These effects were found to be negligible in most instances. Other material models for woven fabrics are available in the LS-DYNA finite element code. One of these models, MAT234: MAT_VISCOELASTIC_LOOSE_FABRIC (Ivanov & Tabiei, 2004) was studied and implemented in the finite element simulations of ballistic testing associated with the FAA ASU research. The results from these models are compared to results obtained from the ASU UMAT as part of this research. The results indicate an underestimation in the energy absorption characteristics of the Kevlar 49 fabric containment systems. More investigation needs to be performed in the implementation of MAT234 for Kevlar 49 fabric. Static penetrator testing of Kevlar® 49 fabric was performed at ASU in conjunction with this research. These experiments are designed to mimic the type of loading experienced during fan blade out events. The resulting experimental strains were measured using a non-contact optical strain measurement system (ARAMIS).
ContributorsFein, Jonathan (Author) / Rajan, Subramaniam D. (Thesis advisor) / Mobasher, Barzin (Committee member) / Jiang, Hanqing (Committee member) / Arizona State University (Publisher)
Created2012