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ABSTRACT
While attempting to provide real world experiences in STEM, educators face numerous challenges including adhering to curriculum requirements and working with potentially limited resources. The purpose of this action research study was to examine how the addition of authentic learning modules to the existing University of Arizona Middle School Engineering 101 (UA MS engineering 101) unit on energy efficiency can provide students with real world experiences as active participants. During an instructional workshop, participating teachers were introduced to strategies they use in their classroom so students could engage with individuals from both inside and outside of the school to create solutions for energy issues the students have identified within their own schools. This study used a series of observations, interviews, and focus groups with the teacher participants to gather data in determining how and in what ways students were able to obtain real world experiences as active participants through the authentic learning modules. Because there are numerous teachers within the UA MS engineering 101 group, a future goal was to assist these additional teachers in providing this innovation to their students.
While attempting to provide real world experiences in STEM, educators face numerous challenges including adhering to curriculum requirements and working with potentially limited resources. The purpose of this action research study was to examine how the addition of authentic learning modules to the existing University of Arizona Middle School Engineering 101 (UA MS engineering 101) unit on energy efficiency can provide students with real world experiences as active participants. During an instructional workshop, participating teachers were introduced to strategies they use in their classroom so students could engage with individuals from both inside and outside of the school to create solutions for energy issues the students have identified within their own schools. This study used a series of observations, interviews, and focus groups with the teacher participants to gather data in determining how and in what ways students were able to obtain real world experiences as active participants through the authentic learning modules. Because there are numerous teachers within the UA MS engineering 101 group, a future goal was to assist these additional teachers in providing this innovation to their students.
ContributorsJagielski, Donna Marie (Author) / Marley, Scott C. (Thesis advisor) / Carlson, David L. (Committee member) / Medrano, Juan (Committee member) / Arizona State University (Publisher)
Created2016
Description
Information divergence functions, such as the Kullback-Leibler divergence or the Hellinger distance, play a critical role in statistical signal processing and information theory; however estimating them can be challenge. Most often, parametric assumptions are made about the two distributions to estimate the divergence of interest. In cases where no parametric model fits the data, non-parametric density estimation is used. In statistical signal processing applications, Gaussianity is usually assumed since closed-form expressions for common divergence measures have been derived for this family of distributions. Parametric assumptions are preferred when it is known that the data follows the model, however this is rarely the case in real-word scenarios. Non-parametric density estimators are characterized by a very large number of parameters that have to be tuned with costly cross-validation. In this dissertation we focus on a specific family of non-parametric estimators, called direct estimators, that bypass density estimation completely and directly estimate the quantity of interest from the data. We introduce a new divergence measure, the $D_p$-divergence, that can be estimated directly from samples without parametric assumptions on the distribution. We show that the $D_p$-divergence bounds the binary, cross-domain, and multi-class Bayes error rates and, in certain cases, provides provably tighter bounds than the Hellinger divergence. In addition, we also propose a new methodology that allows the experimenter to construct direct estimators for existing divergence measures or to construct new divergence measures with custom properties that are tailored to the application. To examine the practical efficacy of these new methods, we evaluate them in a statistical learning framework on a series of real-world data science problems involving speech-based monitoring of neuro-motor disorders.
ContributorsWisler, Alan (Author) / Berisha, Visar (Thesis advisor) / Spanias, Andreas (Thesis advisor) / Liss, Julie (Committee member) / Bliss, Daniel (Committee member) / Arizona State University (Publisher)
Created2017
Description
Lithium ion batteries have emerged as the most popular energy storage system, but they pose safety issues under extreme temperatures or in the event of a thermal runaway. Lithium ion batteries with inorganic separators offer the advantage of safer operation. An inorganic separator for lithium ion battery was prepared by an improved method of blade coating α-Al2O3 slurry directly on the electrode followed by drying. The improved separator preparation involves a twice-coating process instead of coating the slurry all at once in order to obtain a thin (~40 µm) and uniform coat. It was also found that α-Al2O3 powder with particle size greater than the pore size in the electrode is preferable for obtaining a separator with 40 µm thickness and consistent cell performance. Unlike state-of-the-art polyolefin separators such as polypropylene (PP) which are selectively wettable with only certain electrolytes, the excellent electrolyte solvent wettability of α-Al2O3 allows the coated alumina separator to function with different electrolytes. The coated α-Al2O3 separator has a much higher resistance to temperature effects than its polyolefin counterparts, retaining its dimensional integrity at temperatures as high as 200ºC. This eliminates the possibility of a short circuit during thermal runaway. Lithium ion batteries assembled as half-cells and full cells with coated α-Al2O3 separator exhibit electrochemical performance comparable with that of polyolefin separators at room temperature. However, the cells with coated alumina separator shows better cycling performance under extreme temperatures in the temperature range of -30°C to 60°C. Therefore, the coated α-Al2O3 separator is very promising for application in safe lithium-ion batteries.
ContributorsSharma, Gaurav (Author) / Lin, Jerry Y.S. (Thesis advisor) / Chan, Candace (Committee member) / Kannan, Arunachala (Committee member) / Arizona State University (Publisher)
Created2016
Description
Alloying in semiconductors has enabled many civilian technologies in optoelectronic, photonic fields and more. While the phenomenon of alloying is well established in traditional bulk semiconductors, owing to vastly available ternary phase diagrams, the ability to alloy in 2D systems are less clear. Recently anisotropic materials such as ReS2 and TiS3 have been extensively studied due to their direct-gap semiconductor and high mobility behaviors. This work is a report on alloys of ReS2 & ReSe2 and TiS3 &TiSe3.
Alloying selenium into ReS2 in the creation of ReS2xSe2-x, tunes the band gap and changes its vibrational spectrum. Depositing this alloy using bottom up approach has resulted in the loss of crystallinity. This loss of crystallinity was evidenced by grain boundaries and point defect shown by TEM images.
Also, in the creation of TiS3xSe3-x, by alloying Se into TiS3, a fixed ratio of 8% selenium deposit into TiS3 host matrix is observed. This is despite the vastly differing precursor amounts and growth temperatures, as evinced by detailed TEM, EDAX, TEM diffraction, and Raman spectroscopy measurements. This unusual behavior contrasts with other well-known layered material systems such as MoSSe, WMoS2 where continuous alloying can be attained. Cluster expansion theory calculations suggest that only limited composition (x) can be achieved. Considering the fact that TiSe3 vdW crystals have not been synthesized in the past, these alloying rejections can be attributed to energetic instability in the ternary phase diagrams estimated by calculations performed. Overall findings highlight potential means and challenges in achieving stable alloying in promising direct gap and high carrier mobility TiS3 materials.
Alloying selenium into ReS2 in the creation of ReS2xSe2-x, tunes the band gap and changes its vibrational spectrum. Depositing this alloy using bottom up approach has resulted in the loss of crystallinity. This loss of crystallinity was evidenced by grain boundaries and point defect shown by TEM images.
Also, in the creation of TiS3xSe3-x, by alloying Se into TiS3, a fixed ratio of 8% selenium deposit into TiS3 host matrix is observed. This is despite the vastly differing precursor amounts and growth temperatures, as evinced by detailed TEM, EDAX, TEM diffraction, and Raman spectroscopy measurements. This unusual behavior contrasts with other well-known layered material systems such as MoSSe, WMoS2 where continuous alloying can be attained. Cluster expansion theory calculations suggest that only limited composition (x) can be achieved. Considering the fact that TiSe3 vdW crystals have not been synthesized in the past, these alloying rejections can be attributed to energetic instability in the ternary phase diagrams estimated by calculations performed. Overall findings highlight potential means and challenges in achieving stable alloying in promising direct gap and high carrier mobility TiS3 materials.
ContributorsAgarwal, Ashutosh (Author) / Tongay, Sefaattin (Thesis advisor) / Green, Matthew (Committee member) / Zhuang, Houlong (Committee member) / Arizona State University (Publisher)
Created2018
Description
This is a two-part thesis. Part 1 presents the seasonal and tilt angle dependence of soiling loss factor of photovoltaic (PV) modules over two years for Mesa, Arizona (a desert climatic condition). Part 2 presents the development of an indoor artificial soil deposition chamber replicating natural dew cycle. Several environmental factors affect the performance of PV systems including soiling. Soiling on PV modules results in a decrease of sunlight reaching the solar cell, thereby reducing the current and power output. Dust particles, air pollution particles, pollen, bird droppings and other industrial airborne particles are some natural sources that cause soiling. The dust particles vary from one location to the other in terms of particle size, color, and chemical composition. The thickness and properties of the soil layer determine the optical path of light through the soil/glass interface. Soil accumulation on the glass surface is also influenced by environmental factors such as dew, wind speeds and rainfall. Studies have shown that soil deposition is closely related to tilt angle and exposure period before a rain event. The first part of this thesis analyzes the reduction in irradiance transmitted to a solar cell through the air/soil/glass in comparison to a clean cell (air/glass interface). A time series representation is used to compare seasonal soiling loss factors for two consecutive years (2014-2016). The effect of tilt angle and rain events on these losses are extensively analyzed. Since soiling is a significant field issue, there is a growing need to address the problem, and several companies have come up with solutions such as anti-soiling coatings, automated cleaning systems etc. To test and validate the effectiveness of these anti-soiling coating technologies, various research institutes around the world are working on the design and development of artificial indoor soiling chambers to replicate the natural process in the field. The second part of this thesis work deals with the design and development of an indoor artificial soiling chamber that replicates natural soil deposition process in the field.
ContributorsVirkar, Shalaim (Author) / Tamizhmani, Govindasamy (Thesis advisor) / Srinivasan, Devarajan (Committee member) / Kuitche, Joseph (Committee member) / Arizona State University (Publisher)
Created2017
Description
Advancements in thermal interface materials (TIMs) allows for the creation of new and more powerful electronics as they increase the heat transfer from the component to the heat sink. Current industrial options provide decent heat transfer, but the creation of TIMs with higher thermal conductivities is needed. In addition, if these TIMs are elastic in nature, their effectiveness can greatly increase as they can deal with changing interfaces without degradation of their properties. The research performed delves into this idea, creating elastic TIMs using liquid metal (LM), in this case galinstan, along with other matrix particles embedded in Polydimethylsiloxane (PDMS) to create an easy to use, relatively inexpensive, thermally conductive, but electrically insulative, pad with increased thermal conductivity from industrial solutions.
The pads were created using varying amounts of LM and matrix materials ranging from copper microspheres to diamond powder mixed into PDMS using a high-speed mixer. The material was then cast into molds and cured to create the pads. Once the pads were created, the difficulty came in quantifying their thermal properties. A stepped bar apparatus (SBA) following ASTM D5470 was created to measure the thermal resistance of the pads but it was determined that thermal conductivity was a more usable metric of the pads’ performance. This meant that the pad’s in-situ thickness was needed during testing, prompting the installation of a linear encoder to measure the thickness. The design and analysis of the necessary modification and proposed future design is further detailed in the following paper.
The pads were created using varying amounts of LM and matrix materials ranging from copper microspheres to diamond powder mixed into PDMS using a high-speed mixer. The material was then cast into molds and cured to create the pads. Once the pads were created, the difficulty came in quantifying their thermal properties. A stepped bar apparatus (SBA) following ASTM D5470 was created to measure the thermal resistance of the pads but it was determined that thermal conductivity was a more usable metric of the pads’ performance. This meant that the pad’s in-situ thickness was needed during testing, prompting the installation of a linear encoder to measure the thickness. The design and analysis of the necessary modification and proposed future design is further detailed in the following paper.
ContributorsKemme, Nicholas (Author) / Rykaczewski, Konrad (Thesis advisor) / Wang, Robert (Thesis advisor) / Wang, Liping (Committee member) / Arizona State University (Publisher)
Created2017
Description
Robert (Bob) Barnhill came to ASU in 1986 as Chair of the Computer Science Department and left in 1997 as the Vice President for Research. The interview addresses a number of topics including the beginnings of Computer Graphics, moving the Computer Science Department to a more research-oriented effort, achieving Research 1 status, working with the University of Arizona to develop a new statewide Intellectual Property template, dodging the Unabomber and playing soccer. Common themes throughout the interview include Bob’s success at getting groups of people to actually do something other than just meet and the importance of a strategic plan.
ContributorsScheatzle, Dave (Interviewer) / Storad, Conrad (Producer)
Created2011-04-11
Description
The purpose of this project was to develop a system capable of launching projectiles at a curved trajectory. This system effectively imparts spin on projectiles, enabling controlled indirect fire for the intended use of military operations. Through this proof of concept, it was determined whether a scaled system would be a viable solution to the issue of controlled indirect fire in dense urban areas. Using a series of coaxial motors with independently controlled speeds, it was possible to alter the horizontal and vertical displacement of objects in flight.
ContributorsShores, Jamie (Author) / Grewal, Anoop (Thesis director) / Latino, Steven (Committee member) / Mechanical and Aerospace Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
Energy performance and efficiency plays of major role in the operations of K-12 schools, as it is a significant expense and a source of budgetary pressure upon schools. Energy performance is tied to the physical infrastructure of schools, as well as the operational and behavioral patterns they accommodate. Little documentation exists within the existing literature on the measured post-occupancy performance of schools once they have begun measuring and tracking their energy performance. Further, little is known about the patterns of change over time in regard to energy performance and whether there is differentiation in these patterns between school districts.
This paper examines the annual Energy Use Intensity (EUI) of 28 different K-12 schools within the Phoenix Metropolitan Region of Arizona over the span of five years and presents an analysis of changes in energy performance resulting from the measurement of energy use in K-12 schools. This paper also analyzes the patterns of change in energy use over time and provides a comparison of these patterns by school district.
An analysis of the energy performance data for the selected schools revealed a significant positive impact on the ability for schools to improve their energy performance through ongoing performance measurement. However, while schools tend to be able to make energy improvements through the implementation of energy measurement and performance tracking, deviation may exist in their ability to maintain ongoing energy performance over time. The results suggest that implementation of ongoing measurement is likely to produce positive impacts on the energy performance of schools, however further research is recommended to enhance and refine these results.
This paper examines the annual Energy Use Intensity (EUI) of 28 different K-12 schools within the Phoenix Metropolitan Region of Arizona over the span of five years and presents an analysis of changes in energy performance resulting from the measurement of energy use in K-12 schools. This paper also analyzes the patterns of change in energy use over time and provides a comparison of these patterns by school district.
An analysis of the energy performance data for the selected schools revealed a significant positive impact on the ability for schools to improve their energy performance through ongoing performance measurement. However, while schools tend to be able to make energy improvements through the implementation of energy measurement and performance tracking, deviation may exist in their ability to maintain ongoing energy performance over time. The results suggest that implementation of ongoing measurement is likely to produce positive impacts on the energy performance of schools, however further research is recommended to enhance and refine these results.
ContributorsThurston, Anna (Author) / Sullivan, Kenneth (Thesis advisor) / Okamura, Patrick (Committee member) / Slife, Curtis (Committee member) / Arizona State University (Publisher)
Created2015
Description
Distributed wireless sensor networks (WSNs) have attracted researchers recently due to their advantages such as low power consumption, scalability and robustness to link failures. In sensor networks with no fusion center, consensus is a process where
all the sensors in the network achieve global agreement using only local transmissions. In this dissertation, several consensus and consensus-based algorithms in WSNs are studied.
Firstly, a distributed consensus algorithm for estimating the maximum and minimum value of the initial measurements in a sensor network in the presence of communication noise is proposed. In the proposed algorithm, a soft-max approximation together with a non-linear average consensus algorithm is used. A design parameter controls the trade-off between the soft-max error and convergence speed. An analysis of this trade-off gives guidelines towards how to choose the design parameter for the max estimate. It is also shown that if some prior knowledge of the initial measurements is available, the consensus process can be accelerated.
Secondly, a distributed system size estimation algorithm is proposed. The proposed algorithm is based on distributed average consensus and L2 norm estimation. Different sources of error are explicitly discussed, and the distribution of the final estimate is derived. The CRBs for system size estimator with average and max consensus strategies are also considered, and different consensus based system size estimation approaches are compared.
Then, a consensus-based network center and radius estimation algorithm is described. The center localization problem is formulated as a convex optimization problem with a summation form by using soft-max approximation with exponential functions. Distributed optimization methods such as stochastic gradient descent and diffusion adaptation are used to estimate the center. Then, max consensus is used to compute the radius of the network area.
Finally, two average consensus based distributed estimation algorithms are introduced: distributed degree distribution estimation algorithm and algorithm for tracking the dynamics of the desired parameter. Simulation results for all proposed algorithms are provided.
all the sensors in the network achieve global agreement using only local transmissions. In this dissertation, several consensus and consensus-based algorithms in WSNs are studied.
Firstly, a distributed consensus algorithm for estimating the maximum and minimum value of the initial measurements in a sensor network in the presence of communication noise is proposed. In the proposed algorithm, a soft-max approximation together with a non-linear average consensus algorithm is used. A design parameter controls the trade-off between the soft-max error and convergence speed. An analysis of this trade-off gives guidelines towards how to choose the design parameter for the max estimate. It is also shown that if some prior knowledge of the initial measurements is available, the consensus process can be accelerated.
Secondly, a distributed system size estimation algorithm is proposed. The proposed algorithm is based on distributed average consensus and L2 norm estimation. Different sources of error are explicitly discussed, and the distribution of the final estimate is derived. The CRBs for system size estimator with average and max consensus strategies are also considered, and different consensus based system size estimation approaches are compared.
Then, a consensus-based network center and radius estimation algorithm is described. The center localization problem is formulated as a convex optimization problem with a summation form by using soft-max approximation with exponential functions. Distributed optimization methods such as stochastic gradient descent and diffusion adaptation are used to estimate the center. Then, max consensus is used to compute the radius of the network area.
Finally, two average consensus based distributed estimation algorithms are introduced: distributed degree distribution estimation algorithm and algorithm for tracking the dynamics of the desired parameter. Simulation results for all proposed algorithms are provided.
ContributorsZhang, Sai (Electrical engineer) (Author) / Tepedelenlioğlu, Cihan (Thesis advisor) / Spanias, Andreas (Thesis advisor) / Tsakalis, Kostas (Committee member) / Bliss, Daniel (Committee member) / Arizona State University (Publisher)
Created2017