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Description
This dissertation proposes a miniature FIR filter that works at microwave frequencies, whose filter response can ideally be digitally programmed. Such a frequency agile device can find applications in cellular communications and wireless networking. The basic concept of the FIR filter utilizes a low loss acoustic waveguide of appropriate geometry that acts as a traveling wave tapped-delay line. The input RF signal is applied by an array of capacitive transducers at various locations on the acoustic waveguide at one end that excites waves of a propagating acoustic mode with varying spatial delays and amplitudes which interfere as they propagate. The output RF signal is picked up at the other end of the waveguide by another array of capacitive transducers. Tuning of the FIR filter coefficients is realized by controlling the DC voltage profile applied to the individual transducers which essentially shapes the overall filter response. Equivalent circuit modeling of the capacitive transducer, acoustic waveguide and transducer-line coupling is presented in this dissertation. A theoretical model for the filter is developed from a general theory of an array of transducers exciting a waveguide and is used to obtain a set of filter design equations. A MATLAB based circuit simulator is developed to simulate the filter responses. Design parameters and simulation results obtained for an example waveguide structure are presented and compared to the values estimated by the theoretical model. A waveguide structure utilizing the Rayleigh-like mode of a ridge is then introduced. A semi-analytical method to obtain propagating elastic modes of such a ridge waveguide etched in an anisotropic crystal is presented. Microfabrication of a filter based on ridges etched in single crystal Silicon is discussed along with details of the challenges faced. Finally, future work and a few alternative designs are presented that can have a better chance of success. Analysis and modeling work to this point has given a good understanding of the working principles, performance tradeoffs and fabrication pitfalls of the proposed device. With the appropriate acoustic waveguide structure, the proposed device could make it possible to realize miniature programmable FIR filters in the GHz range.
ContributorsGalinde, Ameya (Author) / Abbaspour-Tamijani, Abbas (Thesis advisor) / Chae, Junseok (Committee member) / Pan, George (Committee member) / Phillips, Stephen (Committee member) / Arizona State University (Publisher)
Created2013
Description
The effect of earthquake-induced liquefaction on the local void ratio distribution of cohesionless soil is evaluated using x-ray computed tomography (CT) and an advanced image processing software package. Intact, relatively undisturbed specimens of cohesionless soil were recovered before and after liquefaction by freezing and coring soil deposits created by pluviation and by sedimentation through water. Pluviated soil deposits were liquefied in the small geotechnical centrifuge at the University of California at Davis shared-use National Science Foundation (NSF)-supported Network for Earthquake Engineering Simulation (NEES) facility. A soil deposit created by sedimentation through water was liquefied on a small shake table in the Arizona State University geotechnical laboratory. Initial centrifuge tests employed Ottawa 20-30 sand but this material proved to be too coarse to liquefy in the centrifuge. Therefore, subsequent centrifuge tests employed Ottawa F60 sand. The shake table test employed Ottawa 20-30 sand. Recovered cores were stabilized by impregnation with optical grade epoxy and sent to the University of Texas at Austin NSF-supported facility at the University of Texas at Austin for high-resolution CT scanning of geologic media. The local void ratio distribution of a CT-scanned core of Ottawa 20-30 sand evaluated using Avizo® Fire, a commercially available advanced program for image analysis, was compared to the local void ratio distribution established on the same core by analysis of optical images to demonstrate that analysis of the CT scans gave similar results to optical methods. CT scans were subsequently conducted on liquefied and not-liquefied specimens of Ottawa 20-30 sand and Ottawa F60 sand. The resolution of F60 specimens was inadequate to establish the local void ratio distribution. Results of the analysis of the Ottawa 20-30 specimens recovered from the model built for the shake table test showed that liquefaction can substantially influence the variability in local void ratio, increasing the degree of non-homogeneity in the specimen.
ContributorsGutierrez, Angel (Author) / Kavazanjian, Edward (Thesis advisor) / Houston, Sandra (Committee member) / Zapata, Claudia (Committee member) / Arizona State University (Publisher)
Created2013
Description
The rapid advances in wireless communications and networking have given rise to a number of emerging heterogeneous wireless and mobile networks along with novel networking paradigms, including wireless sensor networks, mobile crowdsourcing, and mobile social networking. While offering promising solutions to a wide range of new applications, their widespread adoption and large-scale deployment are often hindered by people's concerns about the security, user privacy, or both. In this dissertation, we aim to address a number of challenging security and privacy issues in heterogeneous wireless and mobile networks in an attempt to foster their widespread adoption. Our contributions are mainly fivefold. First, we introduce a novel secure and loss-resilient code dissemination scheme for wireless sensor networks deployed in hostile and harsh environments. Second, we devise a novel scheme to enable mobile users to detect any inauthentic or unsound location-based top-k query result returned by an untrusted location-based service providers. Third, we develop a novel verifiable privacy-preserving aggregation scheme for people-centric mobile sensing systems. Fourth, we present a suite of privacy-preserving profile matching protocols for proximity-based mobile social networking, which can support a wide range of matching metrics with different privacy levels. Last, we present a secure combination scheme for crowdsourcing-based cooperative spectrum sensing systems that can enable robust primary user detection even when malicious cognitive radio users constitute the majority.
ContributorsZhang, Rui (Author) / Zhang, Yanchao (Thesis advisor) / Duman, Tolga Mete (Committee member) / Xue, Guoliang (Committee member) / Zhang, Junshan (Committee member) / Arizona State University (Publisher)
Created2013
Description
Properties of random porous material such as pervious concrete are strongly dependant on its pore structure features. This research deals with the development of an understanding of the relationship between the material structure and the mechanical and functional properties of pervious concretes. The fracture response of pervious concrete specimens proportioned for different porosities, as a function of the pore structure features and fiber volume fraction, is studied. Stereological and morphological methods are used to extract the relevant pore structure features of pervious concretes from planar images. A two-parameter fracture model is used to obtain the fracture toughness (KIC) and critical crack tip opening displacement (CTODc) from load-crack mouth opening displacement (CMOD) data of notched beams under three-point bending. The experimental results show that KIC is primarily dependent on the porosity of pervious concretes. For a similar porosity, an increase in pore size results in a reduction in KIC. At similar pore sizes, the effect of fibers on the post-peak response is more prominent in mixtures with a higher porosity, as shown by the residual load capacity, stress-crack extension relationships, and GR curves. These effects are explained using the mean free spacing of pores and pore-to-pore tortuosity in these systems. A sensitivity analysis is employed to quantify the influence of material design parameters on KIC. This research has also focused on studying the relationship between permeability and tortuosity as it pertains to porosity and pore size of pervious concretes. Various ideal geometric shapes were also constructed that had varying pore sizes and porosities. The pervious concretes also had differing pore sizes and porosities. The permeabilities were determined using three different methods; Stokes solver, Lattice Boltzmann method and the Katz-Thompson equation. These values were then compared to the tortuosity values determined using a Matlab code that uses a pore connectivity algorithm. The tortuosity was also determined from the inverse of the conductivity determined from a numerical analysis that was necessary for using the Katz-Thompson equation. These tortuosity values were then compared to the permeabilities. The pervious concretes and ideal geometric shapes showed consistent similarities betbetween their tortuosities and permeabilities.
ContributorsRehder, Benjamin (Author) / Neithalath, Narayanana (Thesis advisor) / Mobasher, Barzin (Committee member) / Rajan, Subramaniam D. (Committee member) / Arizona State University (Publisher)
Created2013
Description
Under the framework of intelligent management of power grids by leveraging advanced information, communication and control technologies, a primary objective of this study is to develop novel data mining and data processing schemes for several critical applications that can enhance the reliability of power systems. Specifically, this study is broadly organized into the following two parts: I) spatio-temporal wind power analysis for wind generation forecast and integration, and II) data mining and information fusion of synchrophasor measurements toward secure power grids. Part I is centered around wind power generation forecast and integration. First, a spatio-temporal analysis approach for short-term wind farm generation forecasting is proposed. Specifically, using extensive measurement data from an actual wind farm, the probability distribution and the level crossing rate of wind farm generation are characterized using tools from graphical learning and time-series analysis. Built on these spatial and temporal characterizations, finite state Markov chain models are developed, and a point forecast of wind farm generation is derived using the Markov chains. Then, multi-timescale scheduling and dispatch with stochastic wind generation and opportunistic demand response is investigated. Part II focuses on incorporating the emerging synchrophasor technology into the security assessment and the post-disturbance fault diagnosis of power systems. First, a data-mining framework is developed for on-line dynamic security assessment by using adaptive ensemble decision tree learning of real-time synchrophasor measurements. Under this framework, novel on-line dynamic security assessment schemes are devised, aiming to handle various factors (including variations of operating conditions, forced system topology change, and loss of critical synchrophasor measurements) that can have significant impact on the performance of conventional data-mining based on-line DSA schemes. Then, in the context of post-disturbance analysis, fault detection and localization of line outage is investigated using a dependency graph approach. It is shown that a dependency graph for voltage phase angles can be built according to the interconnection structure of power system, and line outage events can be detected and localized through networked data fusion of the synchrophasor measurements collected from multiple locations of power grids. Along a more practical avenue, a decentralized networked data fusion scheme is proposed for efficient fault detection and localization.
ContributorsHe, Miao (Author) / Zhang, Junshan (Thesis advisor) / Vittal, Vijay (Thesis advisor) / Hedman, Kory (Committee member) / Si, Jennie (Committee member) / Ye, Jieping (Committee member) / Arizona State University (Publisher)
Created2013
Description
This thesis concerns the flashover issue of the substation insulators operating in a polluted environment. The outdoor insulation equipment used in the power delivery infrastructure encounter different types of pollutants due to varied environmental conditions. Various methods have been developed by manufacturers and researchers to mitigate the flashover problem. The application of Room Temperature Vulcanized (RTV) silicone rubber is one such favorable method as it can be applied over the already installed units. Field experience has already showed that the RTV silicone rubber coated insulators have a lower flashover probability than the uncoated insulators. The scope of this research is to quantify the improvement in the flashover performance. Artificial contamination tests were carried on station post insulators for assessing their performance. A factorial experiment design was used to model the flashover performance. The formulation included the severity of contamination and leakage distance of the insulator samples. Regression analysis was used to develop a mathematical model from the data obtained from the experiments. The main conclusion drawn from the study is that the RTV coated insulators withstood much higher levels of contamination even when the coating had lost its hydrophobicity. This improvement in flashover performance was found to be in the range of 20-40%. A much better flashover performance was observed when the coating recovered its hydrophobicity. It was also seen that the adhesion of coating was excellent even after many tests which involved substantial discharge activity.
ContributorsGholap, Vipul (Author) / Gorur, Ravi S (Thesis advisor) / Karady, George G. (Committee member) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Created2013
Description
Heating of asphalt during production and construction causes the volatilization and oxidation of binders used in mixes. Volatilization and oxidation causes degradation of asphalt pavements by increasing the stiffness of the binders, increasing susceptibility to cracking and negatively affecting the functional and structural performance of the pavements. Degradation of asphalt binders by volatilization and oxidation due to high production temperature occur during early stages of pavement life and are known as Short Term Aging (STA). Elevated temperatures and increased exposure time to elevated temperatures causes increased STA of asphalt. The objective of this research was to investigate how elevated mixing temperatures and exposure time to elevated temperatures affect aging and stiffening of binders, thus influencing properties of the asphalt mixtures. The study was conducted in two stages. The first stage evaluated STA effect of asphalt binders. It involved aging two Performance Graded (PG) virgin asphalt binders, PG 76-16 and PG 64-22 at two different temperatures and durations, then measuring their viscosities. The second stage involved evaluating the effects of elevated STA temperature and time on properties of the asphalt mixtures. It involved STA of asphalt mixtures produced in the laboratory with the PG 64-22 binder at mixing temperatures elevated 25OF above standard practice; STA times at 2 and 4 hours longer than standard practices, and then compacted in a gyratory compactor. Dynamic modulus (E*) and Indirect Tensile Strength (IDT) were measured for the aged mixtures for each temperature and duration to determine the effect of different aging times and temperatures on the stiffness and fatigue properties of the aged asphalt mixtures. The binder test results showed that in all cases, there was increased viscosity. The results showed the highest increase in viscosity resulted from increased aging time. The results also indicated that PG 64-22 was more susceptible to elevated STA temperature and extended time than the PG 76-16 binders. The asphalt mixture test results confirmed the expected outcome that increasing the STA and mixing temperature by 25oF alters the stiffness of mixtures. Significant change in the dynamic modulus mostly occurred at four hour increase in STA time regardless of temperature.
ContributorsLolly, Rubben (Author) / Kaloush, Kamil (Thesis advisor) / Bearup, Wylie (Committee member) / Zapata, Claudia (Committee member) / Mamlouk, Michael (Committee member) / Arizona State University (Publisher)
Created2013
Description
With increasing transistor volume and reducing feature size, it has become a major design constraint to reduce power consumption also. This has given rise to aggressive architectural changes for on-chip power management and rapid development to energy efficient hardware accelerators. Accordingly, the objective of this research work is to facilitate software developers to leverage these hardware techniques and improve energy efficiency of the system. To achieve this, I propose two solutions for Linux kernel: Optimal use of these architectural enhancements to achieve greater energy efficiency requires accurate modeling of processor power consumption. Though there are many models available in literature to model processor power consumption, there is a lack of such models to capture power consumption at the task-level. Task-level energy models are a requirement for an operating system (OS) to perform real-time power management as OS time multiplexes tasks to enable sharing of hardware resources. I propose a detailed design methodology for constructing an architecture agnostic task-level power model and incorporating it into a modern operating system to build an online task-level power profiler. The profiler is implemented inside the latest Linux kernel and validated for Intel Sandy Bridge processor. It has a negligible overhead of less than 1\% hardware resource consumption. The profiler power prediction was demonstrated for various application benchmarks from SPEC to PARSEC with less than 4\% error. I also demonstrate the importance of the proposed profiler for emerging architectural techniques through use case scenarios, which include heterogeneous computing and fine grained per-core DVFS. Along with architectural enhancement in general purpose processors to improve energy efficiency, hardware accelerators like Coarse Grain reconfigurable architecture (CGRA) are gaining popularity. Unlike vector processors, which rely on data parallelism, CGRA can provide greater flexibility and compiler level control making it more suitable for present SoC environment. To provide streamline development environment for CGRA, I propose a flexible framework in Linux to do design space exploration for CGRA. With accurate and flexible hardware models, fine grained integration with accurate architectural simulator, and Linux memory management and DMA support, a user can carry out limitless experiments on CGRA in full system environment.
ContributorsDesai, Digant Pareshkumar (Author) / Vrudhula, Sarma (Thesis advisor) / Chakrabarti, Chaitali (Committee member) / Wu, Carole-Jean (Committee member) / Arizona State University (Publisher)
Created2013
Description
GaN high electron mobility transistors (HEMTs) based on the III-V nitride material system have been under extensive investigation because of their superb performance as high power RF devices. Two dimensional electron gas(2-DEG) with charge density ten times higher than that of GaAs-based HEMT and mobility much higher than Si enables a low on-resistance required for RF devices. Self-heating issues with GaN HEMT and lack of understanding of various phenomena are hindering their widespread commercial development. There is a need to understand device operation by developing a model which could be used to optimize electrical and thermal characteristics of GaN HEMT design for high power and high frequency operation. In this thesis work a physical simulation model of AlGaN/GaN HEMT is developed using commercially available software ATLAS from SILVACO Int. based on the energy balance/hydrodynamic carrier transport equations. The model is calibrated against experimental data. Transfer and output characteristics are the key focus in the analysis along with saturation drain current. The resultant IV curves showed a close correspondence with experimental results. Various combinations of electron mobility, velocity saturation, momentum and energy relaxation times and gate work functions were attempted to improve IV curve correlation. Thermal effects were also investigated to get a better understanding on the role of self-heating effects on the electrical characteristics of GaN HEMTs. The temperature profiles across the device were observed. Hot spots were found along the channel in the gate-drain spacing. These preliminary results indicate that the thermal effects do have an impact on the electrical device characteristics at large biases even though the amount of self-heating is underestimated with respect to thermal particle-based simulations that solve the energy balance equations for acoustic and optical phonons as well (thus take proper account of the formation of the hot-spot). The decrease in drain current is due to decrease in saturation carrier velocity. The necessity of including hydrodynamic/energy balance transport models for accurate simulations is demonstrated. Possible ways for improving model accuracy are discussed in conjunction with future research.
ContributorsChowdhury, Towhid (Author) / Vasileska, Dragica (Thesis advisor) / Goodnick, Stephen (Committee member) / Goryll, Michael (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