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Description
Suction stabilized floats have been implemented into a variety of applications such as supporting wind turbines in off-shore wind farms and for stabilizing cargo ships. This thesis proposes an alternative use for the technology in creating a system of suction stabilized floats equipped with real time location modules to help first responders establish a localized coordinate system to assist in rescues. The floats create a stabilized platform for each anchor module due to the inverse slack tank effect established by the inner water chamber. The design of the float has also been proven to be stable in most cases of amplitudes and frequencies ranging from 0 to 100 except for when the frequency ranges from 23 to 60 Hz for almost all values of the amplitude. The modules in the system form a coordinate grid based off the anchors that can track the location of a tag module within the range of the system using ultra-wideband communications. This method of location identification allows responders to use the system in GPS denied environments. The system can be accessed through an Android app with Bluetooth communications in close ranges or through internet of things (IoT) using a module as a listener, a Raspberry Pi and an internet source. The system has proven to identify the location of the tag in moderate ranges with an approximate accuracy of the tag location being 15 cm.
ContributorsDye, Michaela (Author) / Redkar, Sangram (Thesis advisor) / Sugar, Thomas (Committee member) / Rogers, Bradley (Committee member) / Arizona State University (Publisher)
Created2020
Description
Essential knowledge of Co-continuous composite material properties are explored in this thesis. Mechanical characterization of these materials gives a detailed outlook to use them in design, manufacture and tailor make the products.
Soft and hard polymer materials have extensive properties individually, but when combined to make a single structure, they give an exceptional combination of properties. In this study, Polymer materials used are in the form of Co-Continuous structures (i.e., both soft and hard polymers are continuous throughout the microstructure) fabricated into several microstructures namely, Simple Cubic (SC), Body-Centered Cubic (BCC) and Face Centered Cubic (FCC) shapes. An experimental process is designed and fine-tuned from existing methods to understand and record the mechanical response of these co-continuous polymers. Experimental testing is used to gather detailed information about several constituencies namely stress behavior and damage progression. A 3D imaging technique, Microtomography is used to visualize damage initiation and progression in the sample. Variations in energy absorption, fracture initiation and damage propagation in samples are observed and correlated analysis is performed to provide a logical explanation. Comparative studies are performed as well for different structures.
Based on the Knowledge gained from the above study on co-continuous polymer composites, several conclusions are drawn, and future work directions are suggested.
Soft and hard polymer materials have extensive properties individually, but when combined to make a single structure, they give an exceptional combination of properties. In this study, Polymer materials used are in the form of Co-Continuous structures (i.e., both soft and hard polymers are continuous throughout the microstructure) fabricated into several microstructures namely, Simple Cubic (SC), Body-Centered Cubic (BCC) and Face Centered Cubic (FCC) shapes. An experimental process is designed and fine-tuned from existing methods to understand and record the mechanical response of these co-continuous polymers. Experimental testing is used to gather detailed information about several constituencies namely stress behavior and damage progression. A 3D imaging technique, Microtomography is used to visualize damage initiation and progression in the sample. Variations in energy absorption, fracture initiation and damage propagation in samples are observed and correlated analysis is performed to provide a logical explanation. Comparative studies are performed as well for different structures.
Based on the Knowledge gained from the above study on co-continuous polymer composites, several conclusions are drawn, and future work directions are suggested.
ContributorsVARAKANTHAM, MADHAVA REDDY (Author) / Yongming, Liu (Thesis advisor) / Patel, Jay (Committee member) / Hanqing, Jiang (Committee member) / Arizona State University (Publisher)
Created2019
Description
The delivery of construction projects, particularly with respect to design phase or preconstruction efforts, has changed significantly over the past twenty years. As alternative delivery methods such as Construction-Manager-at-Risk (CMAR) and Design-Build models have become more prominent, general contractors, owners, and designers have had the opportunity to take advantage of the collaborative planning opportunities that exist during the preconstruction portion of the project. While much has been written regarding the benefits of more collaborative approaches and the utilization of various tools and practices during preconstruction to mitigate risk and maximize positive outcomes, what is lesser known is how to teach a coursework that exposes students to various tools and practices that are being utilized today. The objective of this research was to create a testable methodology that can be used to analyze a developed approach that answers the question of how to teach preconstruction tools and practices. A coursework was developed and taught as a graduate level class and data was collected from the actual teaching of that class. In addition, feedback was solicited from the construction industry concerning recommended content applicable to such a class. Data was then analyzed to ascertain student retention of the material and topical content of the course. Through these findings and literature review process the methodology and baseline coursework was shown as an effective means to teach preconstruction tools and practices.
ContributorsKutz, Barry Thomas (Author) / Sullivan, Kenneth T. (Thesis advisor) / Standage, Richard (Committee member) / Hurtado, Kristen (Committee member) / Arizona State University (Publisher)
Created2019
Description
In the last few decades, with the revolution of availability of low-cost microelectronics, which allow fast and complex computations to be performed on board, there has been increasing attention to aerial vehicles, especially rotary-wing vehicles. This is because of their ability to vertically takeoff and land (VTOL), which make them appropriate for urban environments where no runways are needed. Quadrotors took considerable attention in research and development due to their symmetric body, which makes them simpler to model and control compared to other configurations.
One contribution of this work is the design of a new open-source based Quadrotor platform for research. This platform is compatible with both HTC Vive Tracking System (HVTS) and OptiTrack Motion Capture System, Robot Operating System (ROS), and MAVLINK communication protocol.
The thesis examined both nonlinear and linear modeling of a 6-DOF rigid-body quadrotor's dynamics along with actuator dynamics. Nonlinear/linear models are used to develop control laws for both low-level and high-level hierarchical control structures. Both HVTS and OptiTrack were used to demonstrate path following for single and multiple quadrotors. Hardware and simulation data are compared. In short, this work establishes a foundation for future work on formation flight of multi-quadrotor.
One contribution of this work is the design of a new open-source based Quadrotor platform for research. This platform is compatible with both HTC Vive Tracking System (HVTS) and OptiTrack Motion Capture System, Robot Operating System (ROS), and MAVLINK communication protocol.
The thesis examined both nonlinear and linear modeling of a 6-DOF rigid-body quadrotor's dynamics along with actuator dynamics. Nonlinear/linear models are used to develop control laws for both low-level and high-level hierarchical control structures. Both HVTS and OptiTrack were used to demonstrate path following for single and multiple quadrotors. Hardware and simulation data are compared. In short, this work establishes a foundation for future work on formation flight of multi-quadrotor.
ContributorsAltawaitan, Abdullah (Author) / Rodriguez, Armando A (Thesis advisor) / Tsakalis, Konstantinos (Committee member) / Berman, Spring (Committee member) / Arizona State University (Publisher)
Created2019
Description
Accurate forecasting of electricity prices has been a key factor for bidding strategies in the electricity markets. The increase in renewable generation due to large scale PV and wind deployment in California has led to an increase in day-ahead and real-time price volatility. This has also led to prices going negative due to the supply-demand imbalance caused by excess renewable generation during instances of low demand. This research focuses on applying machine learning models to analyze the impact of renewable generation on the hourly locational marginal prices (LMPs) for California Independent System Operator (CAISO). Historical data involving the load, renewable generation from solar and wind, fuel prices, aggregated generation outages is extracted and collected together in a dataset and used as features to train different machine learning models. Tree- based machine learning models such as Extra Trees, Gradient Boost, Extreme Gradient Boost (XGBoost) as well as models based on neural networks such as Long short term memory networks (LSTMs) are implemented for price forecasting. The focus is to capture the best relation between the features and the target LMP variable and determine the weight of every feature in determining the price.
The impact of renewable generation on LMP forecasting is determined for several different days in 2018. It is seen that the prices are impacted significantly by solar and wind generation and it ranks second in terms of impact after the electric load. The results of this research propose a method to evaluate the impact of several parameters on the day-ahead price forecast and would be useful for the grid operators to evaluate the parameters that could significantly impact the day-ahead price prediction and which parameters with low impact could be ignored to avoid an error in the forecast.
The impact of renewable generation on LMP forecasting is determined for several different days in 2018. It is seen that the prices are impacted significantly by solar and wind generation and it ranks second in terms of impact after the electric load. The results of this research propose a method to evaluate the impact of several parameters on the day-ahead price forecast and would be useful for the grid operators to evaluate the parameters that could significantly impact the day-ahead price prediction and which parameters with low impact could be ignored to avoid an error in the forecast.
ContributorsVad, Chinmay (Author) / Honsberg, C. (Christiana B.) (Thesis advisor) / King, Richard R. (Committee member) / Kurtz, Sarah (Committee member) / Arizona State University (Publisher)
Created2019
Description
The study of soft magnetic materials has been growing in popularity in recent years. Driving this interest are new applications for traditional electrical power-management components, such as inductors and transformers, which must be scaled down to the micro and nano scale while the frequencies of operation have been scaling up to the gigahertz range and beyond. The exceptional magnetic properties of the materials make them highly effective in these small-component applications, but the ability of these materials to provide highly-effective shielding has not been so thoroughly considered. Most shielding is done with traditional metals, such as aluminum, because of the relatively low cost of the material and high workability in shaping the material to meet size and dimensional requirements.
This research project focuses on analyzing the variance in shielding effectiveness and electromagnetic field effects of a thin film of Cobalt Zirconium Tantalum Boron (CZTB) in the band of frequencies most likely to require innovative solutions to long-standing problems of noise and interference. The measurements include Near H-Field attenuation and field effects, Far Field shielding, and Backscatter. Minor variances in the thickness and layering of sputter deposition can have significant changes electromagnetic signature of devices which radiate energy through the material.
The material properties presented in this research are H-Field attenuation, H-Field Flux Orientation, Far-Field Approximation, E Field Vector Directivity, H Field Vector Directivity, and Backscatter Magnitude. The results are presented, analyzed and explained using characterization techniques. Future work includes the effect of sputter deposition orientation, application to devices, and applicability in mitigating specific noise signals beyond the 5G band.
This research project focuses on analyzing the variance in shielding effectiveness and electromagnetic field effects of a thin film of Cobalt Zirconium Tantalum Boron (CZTB) in the band of frequencies most likely to require innovative solutions to long-standing problems of noise and interference. The measurements include Near H-Field attenuation and field effects, Far Field shielding, and Backscatter. Minor variances in the thickness and layering of sputter deposition can have significant changes electromagnetic signature of devices which radiate energy through the material.
The material properties presented in this research are H-Field attenuation, H-Field Flux Orientation, Far-Field Approximation, E Field Vector Directivity, H Field Vector Directivity, and Backscatter Magnitude. The results are presented, analyzed and explained using characterization techniques. Future work includes the effect of sputter deposition orientation, application to devices, and applicability in mitigating specific noise signals beyond the 5G band.
ContributorsMiller, Phillip Carl (Author) / Yu, Hongbin (Thesis advisor) / Aberle, James T., 1961- (Committee member) / Blain Christen, Jennifer (Committee member) / Arizona State University (Publisher)
Created2019
Description
Despite the fact that machine learning supports the development of computer vision applications by shortening the development cycle, finding a general learning algorithm that solves a wide range of applications is still bounded by the ”no free lunch theorem”. The search for the right algorithm to solve a specific problem is driven by the problem itself, the data availability and many other requirements.
Automated visual inspection (AVI) systems represent a major part of these challenging computer vision applications. They are gaining growing interest in the manufacturing industry to detect defective products and keep these from reaching customers. The process of defect detection and classification in semiconductor units is challenging due to different acceptable variations that the manufacturing process introduces. Other variations are also typically introduced when using optical inspection systems due to changes in lighting conditions and misalignment of the imaged units, which makes the defect detection process more challenging.
In this thesis, a BagStack classification framework is proposed, which makes use of stacking and bagging concepts to handle both variance and bias errors. The classifier is designed to handle the data imbalance and overfitting problems by adaptively transforming the
multi-class classification problem into multiple binary classification problems, applying a bagging approach to train a set of base learners for each specific problem, adaptively specifying the number of base learners assigned to each problem, adaptively specifying the number of samples to use from each class, applying a novel data-imbalance aware cross-validation technique to generate the meta-data while taking into account the data imbalance problem at the meta-data level and, finally, using a multi-response random forest regression classifier as a meta-classifier. The BagStack classifier makes use of multiple features to solve the defect classification problem. In order to detect defects, a locally adaptive statistical background modeling is proposed. The proposed BagStack classifier outperforms state-of-the-art image classification techniques on our dataset in terms of overall classification accuracy and average per-class classification accuracy. The proposed detection method achieves high performance on the considered dataset in terms of recall and precision.
Automated visual inspection (AVI) systems represent a major part of these challenging computer vision applications. They are gaining growing interest in the manufacturing industry to detect defective products and keep these from reaching customers. The process of defect detection and classification in semiconductor units is challenging due to different acceptable variations that the manufacturing process introduces. Other variations are also typically introduced when using optical inspection systems due to changes in lighting conditions and misalignment of the imaged units, which makes the defect detection process more challenging.
In this thesis, a BagStack classification framework is proposed, which makes use of stacking and bagging concepts to handle both variance and bias errors. The classifier is designed to handle the data imbalance and overfitting problems by adaptively transforming the
multi-class classification problem into multiple binary classification problems, applying a bagging approach to train a set of base learners for each specific problem, adaptively specifying the number of base learners assigned to each problem, adaptively specifying the number of samples to use from each class, applying a novel data-imbalance aware cross-validation technique to generate the meta-data while taking into account the data imbalance problem at the meta-data level and, finally, using a multi-response random forest regression classifier as a meta-classifier. The BagStack classifier makes use of multiple features to solve the defect classification problem. In order to detect defects, a locally adaptive statistical background modeling is proposed. The proposed BagStack classifier outperforms state-of-the-art image classification techniques on our dataset in terms of overall classification accuracy and average per-class classification accuracy. The proposed detection method achieves high performance on the considered dataset in terms of recall and precision.
ContributorsHaddad, Bashar Muneer (Author) / Karam, Lina (Thesis advisor) / Li, Baoxin (Committee member) / He, Jingrui (Committee member) / Turaga, Pavan (Committee member) / Arizona State University (Publisher)
Created2019
Description
The first task faced by many teams endeavoring to solve complex scientific problems is to seek funding for their research venture. Often, this necessitates forming new, geographically dispersed teams of researchers from multiple disciplines. While the team science and organizational management fields have studied project teams extensively, nascent teams are underrepresented in the literature. Nonetheless, understanding proposal team dynamics is important because if left unaddressed, obstacles may persist beyond the funding decision and undermine the possibility of team successes adjunctive to funding. Participant observation of more than 100 multi-investigator proposal teams and semi-structured interviews with six leaders of multidisciplinary proposal teams identified investigator motivations for collaboration, obstacles to collaboration, and indicators of proposal team success. The motivations ranged from technical interests in the research question to a desire to have impact beyond oneself. The obstacles included inconsistent or non-existent communication protocols, unclear processes for producing and reviewing documents, ad hoc file and citation management systems, short and stressful time horizons, ambiguous decision-making procedures, and uncertainty in establishing a shared vision. While funding outcome was the most objective indicator of a proposal team’s success, other success indicators emerged, including whether the needs of the team member(s) had been met and the willingness of team members to continue collaborating. This multi-dimensional definition of success makes it possible for teams to simultaneously be considered successes and failures. As a framework to analyze and overcome obstacles, this work turned to the United States military’s command and control (C2) approach, which relies on specifying the following elements to increase an organization’s agility: patterns of interaction, distribution of information, and allocation of decision rights. To address disciplinary differences and varied motivations for collaboration, this work added a fourth element: shared meaning-making. The broader impact of this work is that by implementing a C2 framework to uncover and address obstacles, the proposal experience—from team creation, to idea generation, to document creation, to final submittal—becomes more rewarding for faculty, leading to greater job satisfaction. This in turn will change how university research enterprises create, organize, and share knowledge to solve complex problems in the post-industrial information age.
ContributorsPassantino, Laurel (Author) / Seager, Thomas P (Thesis advisor) / Cantwell, Elizabeth R (Committee member) / Johnston, Erik (Committee member) / Arizona State University (Publisher)
Created2021
Description
In the structural engineering industry, the design of structures typically follows a prescriptive approach in which engineers conform to a series of code requirements that stipulate the design process. Prescriptive design is tested, reliable, and understood by practically every structural engineer in the industry; however, in recent history a new method of design has started to gain traction among certain groups of engineers. Performance-based design is a reversal of the prescriptive approach in that it allows engineers to set performance goals and work to prove that their proposed designs meet the criteria they have established. To many, it is an opportunity for growth in the structural design industry. Currently, performance-based design is most commonly utilized in regions where seismic activity plays an important role in the design process. Due to its flexible nature, performance-based design has proven extremely useful when applied to unique structures such as high-rises, stadiums, and other community-centric designs. With a focus placed on performance objectives and not on current code prescriptions, engineers utilizing performance-based design are more adept to implement new materials, design processes, and construction methods, and can more efficiently design their structures to exist on a specific area of land. Despite these many cited benefits, performance-based design is still considered an uncommon practice in the broad view of structural design. In order to ensure that structural engineers have the proper tools to practice performance-based design in instances where they see fit, a coordinated effort will be required of the engineers themselves, the firms of which they are employed, the professional societies to which they belong, and the educators who are preparing their next generation. Performance-based design holds with it the opportunity to elevate the role of the structural engineer to which they are informed members of the community, where the structures they create not only perform according to design prescriptions, but also perform according to the needs of the owners, engineers, and society.
ContributorsMaurer, Cole (Author) / Hjelmstad, Keith (Thesis advisor) / Chatziefstratiou, Efthalia (Committee member) / Dusenberry, Donald (Committee member) / Arizona State University (Publisher)
Created2021
Description
Low frequency oscillations (LFOs) are recognized as one of the most challenging problems in electric grids as they limit power transfer capability and can result in system instability. In recent years, the deployment of phasor measurement units (PMUs) has increased the accessibility to time-synchronized wide-area measurements, which has, in turn, enabledthe effective detection and control of the oscillatory modes of the power system. This work assesses the stability improvements that can be achieved through the coordinated wide-area control of power system stabilizers (PSSs), static VAr compensators (SVCs), and supplementary damping controllers (SDCs) of high voltage DC (HVDC) lines, for damping electromechanical oscillations in a modern power system. The improved damping is achieved by designing different types of coordinated wide-area damping controllers (CWADC) that employ partial state-feedback. The first design methodology uses a linear matrix inequality (LMI)-based mixed H2/Hinfty control that is robust for multiple operating scenarios. To counteract the negative impact of communication failure or missing PMU measurements on the designed control, a scheme to identify the alternate set of feedback signals is proposed. Additionally, the impact of delays on the performance of the control design is investigated.
The second approach is motivated by the increasing popularity of artificial intelligence (AI) in enhancing the performance of interconnected power systems. Two different wide-area coordinated control schemes are developed using deep neural networks (DNNs) and deep reinforcement learning (DRL), while accounting for the uncertainties present in the power system. The DNN-CWADC learns to make control decisions using supervised learning; the training dataset consisting of polytopic controllers designed with the help of LMI-based mixed H2/Hinfty optimization. The DRL-CWADC learns to adapt to the system uncertainties based on its continuous interaction with the power system environment by employing
an advanced version of the state-of-the-art deep deterministic policy gradient (DDPG) algorithm referred to as bounded exploratory control-based DDPG (BEC-DDPG). The studies performed on a 29 machine, 127 bus equivalent model of theWestern Electricity Coordinating Council (WECC) system-embedded with different types of damping controls have demonstrated the effectiveness and robustness of the proposed CWADCs.
ContributorsGupta, Pooja (Author) / Pal, Anamitra (Thesis advisor) / Vittal, Vijay (Thesis advisor) / Zhang, Junshan (Committee member) / Hedmnan, Mojdeh (Committee member) / Wu, Meng (Committee member) / Arizona State University (Publisher)
Created2021