ASU Electronic Theses and Dissertations
This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.
In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.
Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.
Displaying 1 - 10 of 73
Description
Developing a system capable of using solar energy to drive the conversion of an abundant and available precursor to fuel would profoundly impact humanity's energy use and thereby the condition of the global ecosystem. Such is the goal of artificial photosynthesis: to convert water to hydrogen using solar radiation as the sole energy input and ideally do so with the use of low cost, abundant materials. Constructing photoelectrochemical cells incorporating photoanodes structurally reminiscent of those used in dye sensitized photovoltaic solar cells presents one approach to establishing an artificial photosynthetic system. The work presented herein describes the production, integration, and study of water oxidation catalysts, molecular dyes, and metal oxide based photoelectrodes carried out in the pursuit of developing solar water splitting systems.
ContributorsSherman, Benjamin D (Author) / Moore, Thomas (Thesis advisor) / Moore, Ana (Committee member) / Buttry, Daniel (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
With the rapid growth of power systems and the concomitant technological advancements, the goal of achieving smart grids is no longer a vision but a foreseeable reality. Hence, the existing grids are undergoing infrastructural modifications to achieve the diverse characteristics of a smart grid. While there are many subjects associated with the operation of smart grids, this dissertation addresses two important aspects of smart grids: increased penetration of renewable resources, and increased reliance on sensor systems to improve reliability and performance of critical power system components. Present renewable portfolio standards are changing both structural and performance characteristics of power systems by replacing conventional generation with alternate energy resources such as photovoltaic (PV) systems. The present study investigates the impact of increased penetration of PV systems on steady state performance as well as transient stability of a large power system which is a portion of the Western U.S. interconnection. Utility scale and residential rooftop PVs are added to replace a portion of conventional generation resources. While steady state voltages are observed under various PV penetration levels, the impact of reduced inertia on transient stability performance is also examined. The simulation results obtained effectively identify both detrimental and beneficial impacts of increased PV penetration both for steady state stability and transient stability performance. With increased penetration of the renewable energy resources, and with the current loading scenario, more transmission system components such as transformers and circuit breakers are subject to increased stress and overloading. This research work explores the feasibility of increasing system reliability by applying condition monitoring systems to selected circuit breakers and transformers. A very important feature of smart grid technology is that this philosophy decreases maintenance costs by deploying condition monitoring systems that inform the operator of impending failures; or the approach can ameliorate problematic conditions. A method to identify the most critical transformers and circuit breakers with the aid of contingency ranking methods is presented in this study. The work reported in this dissertation parallels an industry sponsored study in which a considerable level of industry input and industry reported concerns are reflected.
ContributorsEftekharnejad, Sara (Author) / Heydt, Gerald (Thesis advisor) / Vittal, Vijay (Thesis advisor) / Si, Jennie (Committee member) / Tylavsky, Daniel (Committee member) / Arizona State University (Publisher)
Created2012
Description
The work presented in this thesis covers the synthesis and characterization of an ionomer that is applicable to zinc-air batteries. Polysulfone polymer is first chloromethylated and then quaternized to create an ion-conducting polymer. Nuclear magnetic resonance (NMR) spectra indicates that the degree of chloromethylation was 114%. The chemical and physical properties that were investigated include: the ionic conductivity, ion exchange capacity, water retention capacity, diameter and thickness swelling ratios, porosity, glass transition temperature, ionic conductivity enhanced by free salt addition, and the concentration and diffusivity of oxygen within the ionomer. It was found that the fully hydrated hydroxide form of the ionomer had a room temperature ionic conductivity of 39.92mS/cm while the chloride form had a room temperature ionic conductivity of 11.80mS/cm. The ion exchange capacity of the ionomer was found to be 1.022mmol/g. The water retention capacity (WRC) of the hydroxide form was found to be 172.6% while the chloride form had a WRC of 67.9%. The hydroxide form of the ionomer had a diameter swelling ratio of 34% and a thickness swelling ratio of 55%. The chloride form had a diameter swelling ratio of 32% and a thickness swelling ratio of 28%. The largest pore size in the ionomer was found to be 32.6nm in diameter. The glass transition temperature of the ionomer is speculated to be 344°C. A definite measurement could not be made. The room temperature ionic conductivity at 50% relative humidity was improved to 12.90mS/cm with the addition of 80% free salt. The concentration and diffusivity of oxygen in the ionomer was found to be 1.3 ±0.2mMol and (0.49 ±0.15)x10-5 cm2/s respectively. The ionomer synthesized in this research had material properties and performance that is comparable to other ionomers reported in the literature. This is an indication that this ionomer is suitable for further study and integration into a zinc-air battery. This thesis is concluded with suggestions for future research that is focused on improving the performance of the ionomer as well as improving the methodology.
ContributorsPadilla, Manuel (Author) / Friesen, Cody A (Thesis advisor) / Buttry, Daniel (Committee member) / Sieradzki, Karl (Committee member) / Arizona State University (Publisher)
Created2012
Description
Dealloying, the selective dissolution of an elemental component from an alloy, is an important corrosion mechanism and a technological significant means to fabricate nanoporous structures for a variety of applications. In noble metal alloys, dealloying proceeds above a composition dependent critical potential, and bi-continuous structure evolves "simultaneously" as a result of the interplay between percolation dissolution and surface diffusion. In contrast, dealloying in alloys that show considerable solid-state mass transport at ambient temperature is largely unexplored despite its relevance to nanoparticle catalysts and Li-ion anodes. In my dissertation, I discuss the behaviors of two alloy systems in order to elucidate the role of bulk lattice diffusion in dealloying. First, Mg-Cd alloys are chosen to show that when the dealloying is controlled by bulk diffusion, a new type of porosity - negative void dendrites will form, and the process mirrors electrodeposition. Then, Li-Sn alloys are studied with respect to the composition, particle size and dealloying rate effects on the morphology evolution. Under the right condition, dealloying of Li-Sn supported by percolation dissolution results in the same bi-continuous structure as nanoporous noble metals; whereas lattice diffusion through the otherwise "passivated" surface allows for dealloying with no porosity evolution. The interactions between bulk diffusion, surface diffusion and dissolution are revealed by chronopotentiometry and linear sweep voltammetry technics. The better understanding of dealloying from these experiments enables me to construct a brief review summarizing the electrochemistry and morphology aspects of dealloying as well as offering interpretations to new observations such as critical size effect and encased voids in nanoporous gold. At the end of the dissertation, I will describe a preliminary attempt to generalize the morphology evolution "rules of dealloying" to all solid-to-solid interfacial controlled phase transition process, demonstrating that bi-continuous morphologies can evolve regardless of the nature of parent phase.
ContributorsChen, Qing (Author) / Sieradzki, Karl (Thesis advisor) / Friesen, Cody (Committee member) / Buttry, Daniel (Committee member) / Chan, Candace (Committee member) / Arizona State University (Publisher)
Created2013
Description
The combined heat and power (CHP)-based distributed generation (DG) or dis-tributed energy resources (DERs) are mature options available in the present energy mar-ket, considered to be an effective solution to promote energy efficiency. In the urban en-vironment, the electricity, water and natural gas distribution networks are becoming in-creasingly interconnected with the growing penetration of the CHP-based DG. Subse-quently, this emerging interdependence leads to new topics meriting serious consideration: how much of the CHP-based DG can be accommodated and where to locate these DERs, and given preexisting constraints, how to quantify the mutual impacts on operation performances between these urban energy distribution networks and the CHP-based DG. The early research work was conducted to investigate the feasibility and design methods for one residential microgrid system based on existing electricity, water and gas infrastructures of a residential community, mainly focusing on the economic planning. However, this proposed design method cannot determine the optimal DG sizing and sit-ing for a larger test bed with the given information of energy infrastructures. In this con-text, a more systematic as well as generalized approach should be developed to solve these problems. In the later study, the model architecture that integrates urban electricity, water and gas distribution networks, and the CHP-based DG system was developed. The pro-posed approach addressed the challenge of identifying the optimal sizing and siting of the CHP-based DG on these urban energy networks and the mutual impacts on operation per-formances were also quantified. For this study, the overall objective is to maximize the electrical output and recovered thermal output of the CHP-based DG units. The electrici-ty, gas, and water system models were developed individually and coupled by the devel-oped CHP-based DG system model. The resultant integrated system model is used to constrain the DG's electrical output and recovered thermal output, which are affected by multiple factors and thus analyzed in different case studies. The results indicate that the designed typical gas system is capable of supplying sufficient natural gas for the DG normal operation, while the present water system cannot support the complete recovery of the exhaust heat from the DG units.
ContributorsZhang, Xianjun (Author) / Karady, George G. (Thesis advisor) / Ariaratnam, Samuel T. (Committee member) / Holbert, Keith E. (Committee member) / Si, Jennie (Committee member) / Arizona State University (Publisher)
Created2013
Description
This work demonstrated a novel microfluidic device based on direct current (DC) insulator based dielectrophoresis (iDEP) for trapping individual mammalian cells in a microfluidic device. The novel device is also applicable for selective trapping of weakly metastatic mammalian breast cancer cells (MCF-7) from mixtures with mammalian Peripheral Blood Mononuclear Cells (PBMC) and highly metastatic mammalian breast cancer cells, MDA-MB-231. The advantage of this approach is the ease of integration of iDEP structures in microfliudic channels using soft lithography, the use of DC electric fields, the addressability of the single cell traps for downstream analysis and the straightforward multiplexing for single cell trapping. These microfluidic devices are targeted for capturing of single cells based on their DEP behavior. The numerical simulations point out the trapping regions in which single cell DEP trapping occurs. This work also demonstrates the cell conductivity values of different cell types, calculated using the single-shell model. Low conductivity buffers are used for trapping experiments. These low conductivity buffers help reduce the Joule heating. Viability of the cells in the buffer system was studied in detail with a population size of approximately 100 cells for each study. The work also demonstrates the development of the parallelized single cell trap device with optimized traps. This device is also capable of being coupled detection of target protein using MALDI-MS.
ContributorsBhattacharya, Sanchari (Author) / Ros, Alexandra (Committee member) / Ros, Robert (Committee member) / Buttry, Daniel (Committee member) / Arizona State University (Publisher)
Created2013
Description
This dissertation considers an integrated approach to system design and controller design based on analyzing limits of system performance. Historically, plant design methodologies have not incorporated control relevant considerations. Such an approach could result in a system that might not meet its specifications (or one that requires a complex control architecture to do so). System and controller designers often go through several iterations in order to converge to an acceptable plant and controller design. The focus of this dissertation is on the design and control an air-breathing hypersonic vehicle using such an integrated system-control design framework. The goal is to reduce the number of system-control design iterations (by explicitly incorporate control considerations in the system design process), as well as to influence the guidance/trajectory specifications for the system. Due to the high computational costs associated with obtaining a dynamic model for each plant configuration considered, approximations to the system dynamics are used in the control design process. By formulating the control design problem using bilinear and polynomial matrix inequalities, several common control and system design constraints can be simultaneously incorporated into a vehicle design optimization. Several design problems are examined to illustrate the effectiveness of this approach (and to compare the computational burden of this methodology against more traditional approaches).
ContributorsSridharan, Srikanth (Author) / Rodriguez, Armando A (Thesis advisor) / Mittelmann, Hans D (Committee member) / Si, Jennie (Committee member) / Tsakalis, Konstantinos S (Committee member) / Arizona State University (Publisher)
Created2014
Description
The basal ganglia are four sub-cortical nuclei associated with motor control and reward learning. They are part of numerous larger mostly segregated loops where the basal ganglia receive inputs from specific regions of cortex. Converging on these inputs are dopaminergic neurons that alter their firing based on received and/or predicted rewarding outcomes of a behavior. The basal ganglia's output feeds through the thalamus back to the areas of the cortex where the loop originated. Understanding the dynamic interactions between the various parts of these loops is critical to understanding the basal ganglia's role in motor control and reward based learning. This work developed several experimental techniques that can be applied to further study basal ganglia function. The first technique used micro-volume injections of low concentration muscimol to decrease the firing rates of recorded neurons in a limited area of cortex in rats. Afterwards, an artificial cerebrospinal fluid flush was injected to rapidly eliminate the muscimol's effects. This technique was able to contain the effects of muscimol to approximately a 1 mm radius volume and limited the duration of the drug effect to less than one hour. This technique could be used to temporarily perturb a small portion of the loops involving the basal ganglia and then observe how these effects propagate in other connected regions. The second part applied self-organizing maps (SOM) to find temporal patterns in neural firing rate that are independent of behavior. The distribution of detected patterns frequency on these maps can then be used to determine if changes in neural activity are occurring over time. The final technique focused on the role of the basal ganglia in reward learning. A new conditioning technique was created to increase the occurrence of selected patterns of neural activity without utilizing any external reward or behavior. A pattern of neural activity in the cortex of rats was selected using an SOM. The pattern was then reinforced by being paired with electrical stimulation of the medial forebrain bundle triggering dopamine release in the basal ganglia. Ultimately, this technique proved unsuccessful possibly due to poor selection of the patterns being reinforced.
ContributorsBaldwin, Nathan Aaron (Author) / Helms Tillery, Stephen I (Thesis advisor) / Castaneda, Edward (Committee member) / Buneo, Christopher A (Committee member) / Muthuswamy, Jitendran (Committee member) / Si, Jennie (Committee member) / Arizona State University (Publisher)
Created2014
Description
This study focuses on state estimation of nonlinear discrete time systems with constraints. Physical processes have inherent in them, constraints on inputs, outputs, states and disturbances. These constraints can provide additional information to the estimator in estimating states from the measured output. Recursive filters such as Kalman Filters or Extended Kalman Filters are commonly used in state estimation; however, they do not allow inclusion of constraints in their formulation. On the other hand, computational complexity of full information estimation (using all measurements) grows with iteration and becomes intractable. One way of formulating the recursive state estimation problem with constraints is the Moving Horizon Estimation (MHE) approximation. Estimates of states are calculated from the solution of a constrained optimization problem of fixed size. Detailed formulation of this strategy is studied and properties of this estimation algorithm are discussed in this work. The problem with the MHE formulation is solving an optimization problem in each iteration which is computationally intensive. State estimation with constraints can be formulated as Extended Kalman Filter (EKF) with a projection applied to estimates. The states are estimated from the measurements using standard Extended Kalman Filter (EKF) algorithm and the estimated states are projected on to a constrained set. Detailed formulation of this estimation strategy is studied and the properties associated with this algorithm are discussed. Both these state estimation strategies (MHE and EKF with projection) are tested with examples from the literature. The average estimation time and the sum of square estimation error are used to compare performance of these estimators. Results of the case studies are analyzed and trade-offs are discussed.
ContributorsJoshi, Rakesh (Author) / Tsakalis, Konstantinos (Thesis advisor) / Rodriguez, Armando (Committee member) / Si, Jennie (Committee member) / Arizona State University (Publisher)
Created2013