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- Genre: Doctoral Dissertation
Description
In this thesis, a novel silica nanosphere (SNS) lithography technique has been developed to offer a fast, cost-effective, and large area applicable nano-lithography approach. The SNS can be easily deposited with a simple spin-coating process after introducing a N,N-dimethyl-formamide (DMF) solvent which can produce a highly close packed SNS monolayer over large silicon (Si) surface area, since DMF offers greatly improved wetting, capillary and convective forces in addition to slow solvent evaporation rate. Since the period and dimension of the surface pattern can be conveniently changed and controlled by introducing a desired size of SNS, and additional SNS size reduction with dry etching process, using SNS for lithography provides a highly effective nano-lithography approach for periodically arrayed nano-/micro-scale surface patterns with a desired dimension and period. Various Si nanostructures (i.e., nanopillar, nanotip, inverted pyramid, nanohole) are successfully fabricated with the SNS nano-lithography technique by using different etching technique like anisotropic alkaline solution (i.e., KOH) etching, reactive-ion etching (RIE), and metal-assisted chemical etching (MaCE).
In this research, computational optical modeling is also introduced to design the Si nanostructure, specifically nanopillars (NPs) with a desired period and dimension. The optical properties of Si NP are calculated with two different optical modeling techniques, which are the rigorous coupled wave analysis (RCWA) and finite-difference time-domain (FDTD) methods. By using these two different optical modeling techniques, the optical properties of Si NPs with different periods and dimensions have been investigated to design ideal Si NP which can be potentially used for thin c-Si solar cell applications. From the results of the computational and experimental work, it was observed that low aspect ratio Si NPs fabricated in a periodic hexagonal array can provide highly enhanced light absorption for the target spectral range (600 ~ 1100nm), which is attributed to (1) the effective confinement of resonant scattering within the Si NP and (2) increased high order diffraction of transmitted light providing an extended absorption length. From the research, therefore, it is successfully demonstrated that the nano-fabrication process with SNS lithography can offer enhanced lithographical accuracy to fabricate desired Si nanostructures which can realize enhanced light absorption for thin Si solar cell.
In this research, computational optical modeling is also introduced to design the Si nanostructure, specifically nanopillars (NPs) with a desired period and dimension. The optical properties of Si NP are calculated with two different optical modeling techniques, which are the rigorous coupled wave analysis (RCWA) and finite-difference time-domain (FDTD) methods. By using these two different optical modeling techniques, the optical properties of Si NPs with different periods and dimensions have been investigated to design ideal Si NP which can be potentially used for thin c-Si solar cell applications. From the results of the computational and experimental work, it was observed that low aspect ratio Si NPs fabricated in a periodic hexagonal array can provide highly enhanced light absorption for the target spectral range (600 ~ 1100nm), which is attributed to (1) the effective confinement of resonant scattering within the Si NP and (2) increased high order diffraction of transmitted light providing an extended absorption length. From the research, therefore, it is successfully demonstrated that the nano-fabrication process with SNS lithography can offer enhanced lithographical accuracy to fabricate desired Si nanostructures which can realize enhanced light absorption for thin Si solar cell.
ContributorsChoi, JeaYoung (Author) / Honsberg, Christiana (Thesis advisor) / Alford, Terry (Thesis advisor) / Goodnick, Stephen (Committee member) / Arizona State University (Publisher)
Created2015
Description
Tracking a time-varying number of targets is a challenging
dynamic state estimation problem whose complexity is intensified
under low signal-to-noise ratio (SNR) or high clutter conditions.
This is important, for example, when tracking
multiple, closely spaced targets moving in the same direction such as a
convoy of low observable vehicles moving through a forest or multiple
targets moving in a crisscross pattern. The SNR in
these applications is usually low as the reflected signals from
the targets are weak or the noise level is very high.
An effective approach for detecting and tracking a single target
under low SNR conditions is the track-before-detect filter (TBDF)
that uses unthresholded measurements. However, the TBDF has only been used to
track a small fixed number of targets at low SNR.
This work proposes a new multiple target TBDF approach to track a
dynamically varying number of targets under the recursive Bayesian framework.
For a given maximum number of
targets, the state estimates are obtained by estimating the joint
multiple target posterior probability density function under all possible
target
existence combinations. The estimation of the corresponding target existence
combination probabilities and the target existence probabilities are also
derived. A feasible sequential Monte Carlo (SMC) based implementation
algorithm is proposed. The approximation accuracy of the SMC
method with a reduced number of particles is improved by an efficient
proposal density function that partitions the multiple target space into a
single target space.
The proposed multiple target TBDF method is extended to track targets in sea
clutter using highly time-varying radar measurements. A generalized
likelihood function for closely spaced multiple targets in compound Gaussian
sea clutter is derived together with the maximum likelihood estimate of
the model parameters using an iterative fixed point algorithm.
The TBDF performance is improved by proposing a computationally feasible
method to estimate the space-time covariance matrix of rapidly-varying sea
clutter. The method applies the Kronecker product approximation to the
covariance matrix and uses particle filtering to solve the resulting dynamic
state space model formulation.
dynamic state estimation problem whose complexity is intensified
under low signal-to-noise ratio (SNR) or high clutter conditions.
This is important, for example, when tracking
multiple, closely spaced targets moving in the same direction such as a
convoy of low observable vehicles moving through a forest or multiple
targets moving in a crisscross pattern. The SNR in
these applications is usually low as the reflected signals from
the targets are weak or the noise level is very high.
An effective approach for detecting and tracking a single target
under low SNR conditions is the track-before-detect filter (TBDF)
that uses unthresholded measurements. However, the TBDF has only been used to
track a small fixed number of targets at low SNR.
This work proposes a new multiple target TBDF approach to track a
dynamically varying number of targets under the recursive Bayesian framework.
For a given maximum number of
targets, the state estimates are obtained by estimating the joint
multiple target posterior probability density function under all possible
target
existence combinations. The estimation of the corresponding target existence
combination probabilities and the target existence probabilities are also
derived. A feasible sequential Monte Carlo (SMC) based implementation
algorithm is proposed. The approximation accuracy of the SMC
method with a reduced number of particles is improved by an efficient
proposal density function that partitions the multiple target space into a
single target space.
The proposed multiple target TBDF method is extended to track targets in sea
clutter using highly time-varying radar measurements. A generalized
likelihood function for closely spaced multiple targets in compound Gaussian
sea clutter is derived together with the maximum likelihood estimate of
the model parameters using an iterative fixed point algorithm.
The TBDF performance is improved by proposing a computationally feasible
method to estimate the space-time covariance matrix of rapidly-varying sea
clutter. The method applies the Kronecker product approximation to the
covariance matrix and uses particle filtering to solve the resulting dynamic
state space model formulation.
ContributorsEbenezer, Samuel P (Author) / Papandreou-Suppappola, Antonia (Thesis advisor) / Chakrabarti, Chaitali (Committee member) / Bliss, Daniel (Committee member) / Kovvali, Narayan (Committee member) / Arizona State University (Publisher)
Created2015
Description
This work considers the problem of multiple detection and tracking in two complex time-varying environments, urban terrain and underwater. Tracking multiple radar targets in urban environments is rst investigated by exploiting multipath signal returns, wideband underwater acoustic (UWA) communications channels are estimated using adaptive learning methods, and multiple UWA communications users are detected by designing the transmit signal to match the environment. For the urban environment, a multi-target tracking algorithm is proposed that integrates multipath-to-measurement association and the probability hypothesis density method implemented using particle filtering. The algorithm is designed to track an unknown time-varying number of targets by extracting information from multiple measurements due to multipath returns in the urban terrain. The path likelihood probability is calculated by considering associations between measurements and multipath returns, and an adaptive clustering algorithm is used to estimate the number of target and their corresponding parameters. The performance of the proposed algorithm is demonstrated for different multiple target scenarios and evaluated using the optimal subpattern assignment metric. The underwater environment provides a very challenging communication channel due to its highly time-varying nature, resulting in large distortions due to multipath and Doppler-scaling, and frequency-dependent path loss. A model-based wideband UWA channel estimation algorithm is first proposed to estimate the channel support and the wideband spreading function coefficients. A nonlinear frequency modulated signaling scheme is proposed that is matched to the wideband characteristics of the underwater environment. Constraints on the signal parameters are derived to optimally reduce multiple access interference and the UWA channel effects. The signaling scheme is compared to a code division multiple access (CDMA) scheme to demonstrate its improved bit error rate performance. The overall multi-user communication system performance is finally analyzed by first estimating the UWA channel and then designing the signaling scheme for multiple communications users.
ContributorsZhou, Meng (Author) / Papandreou-Suppappola, Antonia (Thesis advisor) / Tepedelenlioğlu, Cihan (Committee member) / Kovvali, Narayan (Committee member) / Berisha, Visar (Committee member) / Arizona State University (Publisher)
Created2014
Description
The healthcare system in this country is currently unacceptable. New technologies may contribute to reducing cost and improving outcomes. Early diagnosis and treatment represents the least risky option for addressing this issue. Such a technology needs to be inexpensive, highly sensitive, highly specific, and amenable to adoption in a clinic. This thesis explores an immunodiagnostic technology based on highly scalable, non-natural sequence peptide microarrays designed to profile the humoral immune response and address the healthcare problem. The primary aim of this thesis is to explore the ability of these arrays to map continuous (linear) epitopes. I discovered that using a technique termed subsequence analysis where epitopes could be decisively mapped to an eliciting protein with high success rate. This led to the discovery of novel linear epitopes from Plasmodium falciparum (Malaria) and Treponema palladium (Syphilis), as well as validation of previously discovered epitopes in Dengue and monoclonal antibodies. Next, I developed and tested a classification scheme based on Support Vector Machines for development of a Dengue Fever diagnostic, achieving higher sensitivity and specificity than current FDA approved techniques. The software underlying this method is available for download under the BSD license. Following this, I developed a kinetic model for immunosignatures and tested it against existing data driven by previously unexplained phenomena. This model provides a framework and informs ways to optimize the platform for maximum stability and efficiency. I also explored the role of sequence composition in explaining an immunosignature binding profile, determining a strong role for charged residues that seems to have some predictive ability for disease. Finally, I developed a database, software and indexing strategy based on Apache Lucene for searching motif patterns (regular expressions) in large biological databases. These projects as a whole have advanced knowledge of how to approach high throughput immunodiagnostics and provide an example of how technology can be fused with biology in order to affect scientific and health outcomes.
ContributorsRicher, Joshua Amos (Author) / Johnston, Stephen A. (Thesis advisor) / Woodbury, Neal (Committee member) / Stafford, Phillip (Committee member) / Papandreou-Suppappola, Antonia (Committee member) / Arizona State University (Publisher)
Created2014
Description
Horn antennas have been used for over a hundred years. They have a wide variety of uses where they are a basic and popular microwave antenna for many practical applications, such as feed elements for communication reflector dishes on satellite or point-to-point relay antennas. They are also widely utilized as gain standards for calibration and gain measurement of other antennas.
The gain and loss factor of conical horns are revisited in this dissertation based on
spherical and quadratic aperture phase distributions. The gain is compared with published classical data in an attempt to confirm their validity and accuracy and to determine whether they were derived based on spherical or quadratic aperture phase distributions. In this work, it is demonstrated that the gain of a conical horn antenna obtained by using a spherical phase distribution is in close agreement with published classical data. Moreover, more accurate expressions for the loss factor, to account for amplitude and phase tapers over the horn aperture, are derived. New formulas for the design of optimum gain conical horns, based on the more accurate spherical aperture phase distribution, are derived.
To better understand the impact of edge diffractions on aperture antenna performance, an extensive investigation of the edge diffractions impact is undertaken in this dissertation for commercial aperture antennas. The impact of finite uncoated and coated PEC ground plane edge diffractions on the amplitude patterns in the principal planes of circular apertures is intensively examined. Similarly, aperture edge diffractions of aperture antennas without ground planes are examined. Computational results obtained by the analytical model are compared with experimental and HFSS-simulated results for all cases studied. In addition, the impact of the ground plane size, coating thickness, and relative permittivity of the dielectric layer on the radiation amplitude in the back region has been examined.
This investigation indicates that the edge diffractions do impact the main forward lobe pattern, especially in the E plane. Their most significant contribution appears in far side and back lobes. This work demonstrates that the finite edge contributors must be considered to obtain more accurate amplitude patterns of aperture antennas.
The gain and loss factor of conical horns are revisited in this dissertation based on
spherical and quadratic aperture phase distributions. The gain is compared with published classical data in an attempt to confirm their validity and accuracy and to determine whether they were derived based on spherical or quadratic aperture phase distributions. In this work, it is demonstrated that the gain of a conical horn antenna obtained by using a spherical phase distribution is in close agreement with published classical data. Moreover, more accurate expressions for the loss factor, to account for amplitude and phase tapers over the horn aperture, are derived. New formulas for the design of optimum gain conical horns, based on the more accurate spherical aperture phase distribution, are derived.
To better understand the impact of edge diffractions on aperture antenna performance, an extensive investigation of the edge diffractions impact is undertaken in this dissertation for commercial aperture antennas. The impact of finite uncoated and coated PEC ground plane edge diffractions on the amplitude patterns in the principal planes of circular apertures is intensively examined. Similarly, aperture edge diffractions of aperture antennas without ground planes are examined. Computational results obtained by the analytical model are compared with experimental and HFSS-simulated results for all cases studied. In addition, the impact of the ground plane size, coating thickness, and relative permittivity of the dielectric layer on the radiation amplitude in the back region has been examined.
This investigation indicates that the edge diffractions do impact the main forward lobe pattern, especially in the E plane. Their most significant contribution appears in far side and back lobes. This work demonstrates that the finite edge contributors must be considered to obtain more accurate amplitude patterns of aperture antennas.
ContributorsAboserwal, Nafati Abdasallam (Author) / Balanis, Constantine A (Thesis advisor) / Aberle, James T (Committee member) / Pan, George (Committee member) / Tepedelenlioğlu, Cihan (Committee member) / Arizona State University (Publisher)
Created2014
Description
Deoxyribonucleic acid (DNA) has emerged as an excellent molecular building block for nanoconstruction in addition to its biological role of preserving genetic information. Its unique features such as predictable conformation and programmable intra- and inter-molecular Watson-Crick base pairing interactions make it a remarkable engineering material. A variety of convenient design rules and reliable assembly methods have been developed to engineer DNA nanostructures. The ability to create designer DNA architectures with accurate spatial control has allowed researchers to explore novel applications in directed material assembly, structural biology, biocatalysis, DNA
computing, nano-robotics, disease diagnosis, and drug delivery.
This dissertation focuses on developing the structural design rules for "static" DNA nano-architectures with increasing complexity. By using a modular self-assembly method, Archimedean tilings were achieved by association of different DNA motifs with designed arm lengths and inter-tile sticky end interactions. By employing DNA origami method, a new set of design rules was created to allow the scaffolds to travel in arbitrary directions in a designed geometry without local symmetry restrictions. Sophisticated wireframe structures of higher-order complexity were designed and constructed successfully. This dissertation also presents the use of "dynamic" DNA nanotechnology to construct DNA origami nanostructures with programmed reconfigurations.
computing, nano-robotics, disease diagnosis, and drug delivery.
This dissertation focuses on developing the structural design rules for "static" DNA nano-architectures with increasing complexity. By using a modular self-assembly method, Archimedean tilings were achieved by association of different DNA motifs with designed arm lengths and inter-tile sticky end interactions. By employing DNA origami method, a new set of design rules was created to allow the scaffolds to travel in arbitrary directions in a designed geometry without local symmetry restrictions. Sophisticated wireframe structures of higher-order complexity were designed and constructed successfully. This dissertation also presents the use of "dynamic" DNA nanotechnology to construct DNA origami nanostructures with programmed reconfigurations.
ContributorsZhang, Fei (Author) / Yan, Hao (Thesis advisor) / Liu, Yan (Thesis advisor) / Gould, Ian (Committee member) / Zhang, Peiming (Committee member) / Arizona State University (Publisher)
Created2015
Description
An underrepresentation of females exists in the STEM fields. In order to tackle this issue, work begins early in the education of young women to ensure they are interested and have the confidence to gain a career in the STEM fields. It is important to engage girls in STEM opportunities in and out of school to ignite their interest and build their confidence. Brigid Barron's learning ecology perspective shows that girls pursuing STEM outside of the classroom is critical to their achievement in the STEM pipeline. This study investigated the impact after-school STEM learning opportunities have on middle school girls by investigating (a) how the length of engagement in after-school programs can affect the confidence of female students in their science and math abilities; (b) how length of engagement in after-school programs can affect the interest of female students in attaining a career in STEM; (c) how length of engagement in after-school programs can affect interest in science and math classes; and (d) how length of engagement can affect how female students' view gender parity in the STEM workforce. The major findings revealed no statistical significance when comparing confidence in math or science abilities or the perception that gender plays a role in attaining a career in STEM. The findings revealed statistical significance in the areas when comparing length of engagement in the girls' interest in their math class and attaining a career in three of the four STEM fields: science, technology, and engineering. The findings showed that multiple terms of engagement in the after-school STEM programs appear to be an effective catalyst to maintain the interest of girls pursuing STEM-related careers, in addition to allowing their interest in a topic to provide a new lens for the way they see their math work during the school day. The implications of this study show that schools must engage middle school girls who are interested in STEM in a multitude of settings, including outside of the classroom in order to maintain engagement in the STEM pipeline.
ContributorsCupp, Garth Meichel (Author) / Spencer, Dee Ann (Thesis advisor) / Appleton, Nicholas (Committee member) / Schauer, David K (Committee member) / Arizona State University (Publisher)
Created2015
Description
Economic and environmental concerns necessitate the preference for retrofits over new construction in manufacturing facilities for incorporating modern technology, expanding production, becoming more energy-efficient and improving operational efficiency. Despite the technical and functional challenges in retrofits, the expectation from the project team is to; reduce costs, ensure the time to market and maintain a high standard for quality and safety. Thus, the construction supply chain faces increasing pressure to improve performance by ensuring better labor productivity, among other factors, for efficiency gain. Building Information Modeling (BIM) & off-site prefabrication are determined as effective management & production methods to meet these goals. However, there are limited studies assessing their impact on labor productivity within the constraints of a retrofit environment. This study fills the gap by exploring the impact of BIM on labor productivity (metric) in retrofits (context).
BIM use for process tool installation at a semiconductor manufacturing facility serves as an ideal environment for practical observations. Direct site observations indicate a positive correlation between disruptions in the workflow attributed to an immature use of BIM, waste due to rework and high non-value added time at the labor work face. Root-cause analysis traces the origins of the said disruptions to decision-factors that are critical for the planning, management and implementation of BIM. Analysis shows that stakeholders involved in decision-making during BIM planning, management and implementation identify BIM-value based on their immediate utility for BIM-use instead of the utility for the customers of the process. This differing value-system manifests in the form of unreliable and inaccurate information at the labor work face.
Grounding the analysis in theory and observations, the author hypothesizes that stakeholders of a construction project value BIM and BIM-aspects (i.e. geometrical information, descriptive information and workflows) differently and the accuracy of geometrical information is critical for improving labor productivity when using prefabrication in retrofit construction. In conclusion, this research presents a BIM-value framework, associating stakeholders with their relative value for BIM, the decision-factors for the planning, management and implementation of BIM and the potential impact of those decisions on labor productivity.
BIM use for process tool installation at a semiconductor manufacturing facility serves as an ideal environment for practical observations. Direct site observations indicate a positive correlation between disruptions in the workflow attributed to an immature use of BIM, waste due to rework and high non-value added time at the labor work face. Root-cause analysis traces the origins of the said disruptions to decision-factors that are critical for the planning, management and implementation of BIM. Analysis shows that stakeholders involved in decision-making during BIM planning, management and implementation identify BIM-value based on their immediate utility for BIM-use instead of the utility for the customers of the process. This differing value-system manifests in the form of unreliable and inaccurate information at the labor work face.
Grounding the analysis in theory and observations, the author hypothesizes that stakeholders of a construction project value BIM and BIM-aspects (i.e. geometrical information, descriptive information and workflows) differently and the accuracy of geometrical information is critical for improving labor productivity when using prefabrication in retrofit construction. In conclusion, this research presents a BIM-value framework, associating stakeholders with their relative value for BIM, the decision-factors for the planning, management and implementation of BIM and the potential impact of those decisions on labor productivity.
ContributorsGhosh, Arundhati (Author) / Chasey, Allan D (Thesis advisor) / Laroche, Dominique-Claude (Committee member) / Fowler, John (Committee member) / Arizona State University (Publisher)
Created2015
Description
This thesis presents research on innovative AC transmission design concepts and focused mathematics for electric power transmission design. The focus relates to compact designs, high temperature low sag conductors, and high phase order design. The motivation of the research is to increase transmission capacity with limited right of way.
Regarding compact phase spacing, insight into the possibility of increasing the security rating of transmission lines is the primary focus through increased mutual coupling and decreased positive sequence reactance. Compact design can reduce the required corridor width to as little as 31% of traditional designs, especially with the use of inter-phase spacers. Typically transmission lines are built with conservative clearances, with difficulty obtaining right of way, more compact phase spacing may be needed. With design consideration significant compaction can produce an increase by 5-25% in the transmission line security (steady state stability) rating. In addition, other advantages and disadvantages of compact phase design are analyzed. Also, the next two topics: high temperature low sag conductors and high phase order designs include the use of compact designs.
High temperature low sag (HTLS) conductors are used to increase the thermal capacity of a transmission line up to two times the capacity compared to traditional conductors. HTLS conductors can operate continuously at 150-210oC and in emergency at 180-250oC (depending on the HTLS conductor). ACSR conductors operate continuously at 50-110oC and in emergency conditions at 110-150oC depending on the utility, line, and location. HTLS conductors have decreased sag characteristics of up to 33% compared to traditional ACSR conductors at 100oC and up to 22% at 180oC. In addition to what HTLS has to offer in terms of the thermal rating improvement, the possibility of using HTLS conductors to indirectly reduce tower height and compact the phases to increase the security limit is investigated. In addition, utilizing HTLS conductors to increase span length and decrease the number of transmission towers is investigated. The phase compaction or increased span length is accomplished by utilization of the improved physical sag characteristics of HTLS conductors.
High phase order (HPO) focuses on the ability to increase the power capacity for a given right of way. For example, a six phase line would have a thermal rating of approximately 173%, a security rating of approximately 289%, and the SIL would be approximately 300% of a double circuit three phase line with equal right of way and equal voltage line to line. In addition, this research focuses on algorithm and model development of HPO systems. A study of the impedance of HPO lines is presented. The line impedance matrices for some high phase order configurations are circulant Toeplitz matrices. Properties of circulant matrices are developed for the generalized sequence impedances of HPO lines. A method to calculate the sequence impedances utilizing unique distance parameter algorithms is presented. A novel method to design the sequence impedances to specifications is presented. Utilizing impedance matrices in circulant form, a generalized form of the sequence components transformation matrix is presented. A generalized voltage unbalance factor in discussed for HPO transmission lines. Algorithms to calculate the number of fault types and number of significant fault types for an n-phase system are presented. A discussion is presented on transposition of HPO transmission lines and a generalized fault analysis of a high phase order circuit is presented along with an HPO analysis program.
The work presented has the objective of increasing the use of rights of way for bulk power transmission through the use of innovative transmission technologies. The purpose of this dissertation is to lay down some of the building blocks and to help make the three technologies discussed practical applications in the future.
Regarding compact phase spacing, insight into the possibility of increasing the security rating of transmission lines is the primary focus through increased mutual coupling and decreased positive sequence reactance. Compact design can reduce the required corridor width to as little as 31% of traditional designs, especially with the use of inter-phase spacers. Typically transmission lines are built with conservative clearances, with difficulty obtaining right of way, more compact phase spacing may be needed. With design consideration significant compaction can produce an increase by 5-25% in the transmission line security (steady state stability) rating. In addition, other advantages and disadvantages of compact phase design are analyzed. Also, the next two topics: high temperature low sag conductors and high phase order designs include the use of compact designs.
High temperature low sag (HTLS) conductors are used to increase the thermal capacity of a transmission line up to two times the capacity compared to traditional conductors. HTLS conductors can operate continuously at 150-210oC and in emergency at 180-250oC (depending on the HTLS conductor). ACSR conductors operate continuously at 50-110oC and in emergency conditions at 110-150oC depending on the utility, line, and location. HTLS conductors have decreased sag characteristics of up to 33% compared to traditional ACSR conductors at 100oC and up to 22% at 180oC. In addition to what HTLS has to offer in terms of the thermal rating improvement, the possibility of using HTLS conductors to indirectly reduce tower height and compact the phases to increase the security limit is investigated. In addition, utilizing HTLS conductors to increase span length and decrease the number of transmission towers is investigated. The phase compaction or increased span length is accomplished by utilization of the improved physical sag characteristics of HTLS conductors.
High phase order (HPO) focuses on the ability to increase the power capacity for a given right of way. For example, a six phase line would have a thermal rating of approximately 173%, a security rating of approximately 289%, and the SIL would be approximately 300% of a double circuit three phase line with equal right of way and equal voltage line to line. In addition, this research focuses on algorithm and model development of HPO systems. A study of the impedance of HPO lines is presented. The line impedance matrices for some high phase order configurations are circulant Toeplitz matrices. Properties of circulant matrices are developed for the generalized sequence impedances of HPO lines. A method to calculate the sequence impedances utilizing unique distance parameter algorithms is presented. A novel method to design the sequence impedances to specifications is presented. Utilizing impedance matrices in circulant form, a generalized form of the sequence components transformation matrix is presented. A generalized voltage unbalance factor in discussed for HPO transmission lines. Algorithms to calculate the number of fault types and number of significant fault types for an n-phase system are presented. A discussion is presented on transposition of HPO transmission lines and a generalized fault analysis of a high phase order circuit is presented along with an HPO analysis program.
The work presented has the objective of increasing the use of rights of way for bulk power transmission through the use of innovative transmission technologies. The purpose of this dissertation is to lay down some of the building blocks and to help make the three technologies discussed practical applications in the future.
ContributorsPierre, Brian J (Author) / Heydt, Gerald (Thesis advisor) / Karady, George G. (Committee member) / Shunk, Dan (Committee member) / Vittal, Vijay (Committee member) / Arizona State University (Publisher)
Created2015
Description
Cigarette smoking remains a major global public health issue. This is partially due to the chronic and relapsing nature of tobacco use, which contributes to the approximately 90% quit attempt failure rate. The recent rise in mobile technologies has led to an increased ability to frequently measure smoking behaviors and related constructs over time, i.e., obtain intensive longitudinal data (ILD). Dynamical systems modeling and system identification methods from engineering offer a means to leverage ILD in order to better model dynamic smoking behaviors. In this dissertation, two sets of dynamical systems models are estimated using ILD from a smoking cessation clinical trial: one set describes cessation as a craving-mediated process; a second set was reverse-engineered and describes a psychological self-regulation process in which smoking activity regulates craving levels. The estimated expressions suggest that self-regulation more accurately describes cessation behavior change, and that the psychological self-regulator resembles a proportional-with-filter controller. In contrast to current clinical practice, adaptive smoking cessation interventions seek to personalize cessation treatment over time. An intervention of this nature generally reflects a control system with feedback and feedforward components, suggesting its design could benefit from a control systems engineering perspective. An adaptive intervention is designed in this dissertation in the form of a Hybrid Model Predictive Control (HMPC) decision algorithm. This algorithm assigns counseling, bupropion, and nicotine lozenges each day to promote tracking of target smoking and craving levels. Demonstrated through a diverse series of simulations, this HMPC-based intervention can aid a successful cessation attempt. Objective function weights and three-degree-of-freedom tuning parameters can be sensibly selected to achieve intervention performance goals despite strict clinical and operational constraints. Such tuning largely affects the rate at which peak bupropion and lozenge dosages are assigned; total post-quit smoking levels, craving offset, and other performance metrics are consequently affected. Overall, the interconnected nature of the smoking and craving controlled variables facilitate the controller's robust decision-making capabilities, even despite the presence of noise or plant-model mismatch. Altogether, this dissertation lays the conceptual and computational groundwork for future efforts to utilize engineering concepts to further study smoking behaviors and to optimize smoking cessation interventions.
ContributorsTimms, Kevin Patrick (Author) / Rivera, Daniel E (Thesis advisor) / Frakes, David (Committee member) / Nielsen, David R (Committee member) / Arizona State University (Publisher)
Created2014