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Dreadnought is a free-to-play multiplayer flight simulation in which two teams of 8 players each compete against one another to complete an objective. Each player controls a large-scale spaceship, various aspects of which can be customized to improve a player’s performance in a game. One such aspect is Officer Briefings,

Dreadnought is a free-to-play multiplayer flight simulation in which two teams of 8 players each compete against one another to complete an objective. Each player controls a large-scale spaceship, various aspects of which can be customized to improve a player’s performance in a game. One such aspect is Officer Briefings, which are passive abilities that grant ships additional capabilities. Two of these Briefings, known as Retaliator and Get My Good Side, have strong synergy when used together, which has led to the Dreadnought community’s claiming that the Briefings are too powerful and should be rebalanced to be more in line with the power levels of other Briefings. This study collected gameplay data with and without the use of these specific Officer Briefings to determine the precise impact on gameplay. Linear correlation matrices and inference on two means were used to determine performance impact. It was found that, although these Officer Briefings do improve an individual player’s performance in a game, they do not have a consistent impact on the player’s team performance, and that these Officer Briefings are therefore not in need of rebalancing.

ContributorsJacobs, Max I. (Author) / Schneider, Laurence (Thesis director) / Tran, Samantha (Committee member) / Mechanical and Aerospace Engineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Advanced composites are being widely used in aerospace applications due to their high stiffness, strength and energy absorption capabilities. However, the assurance of structural reliability is a critical issue because a damage event will compromise the integrity of composite structures and lead to ultimate failure. In this dissertation a novel

Advanced composites are being widely used in aerospace applications due to their high stiffness, strength and energy absorption capabilities. However, the assurance of structural reliability is a critical issue because a damage event will compromise the integrity of composite structures and lead to ultimate failure. In this dissertation a novel homogenization based multiscale modeling framework using semi-analytical micromechanics is presented to simulate the response of textile composites. The novelty of this approach lies in the three scale homogenization/localization framework bridging between the constituent (micro), the fiber tow scale (meso), weave scale (macro), and the global response. The multiscale framework, named Multiscale Generalized Method of Cells (MSGMC), continuously bridges between the micro to the global scale as opposed to approaches that are top-down and bottom-up. This framework is fully generalized and capable of modeling several different weave and braids without reformulation. Particular emphasis in this dissertation is placed on modeling the nonlinearity and failure of both polymer matrix and ceramic matrix composites.
ContributorsLiu, Guang (Author) / Chattopadhyay, Aditi (Thesis advisor) / Mignolet, Marc (Committee member) / Jiang, Hanqing (Committee member) / Li, Jian (Committee member) / Rajadas, John (Committee member) / Arizona State University (Publisher)
Created2011
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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

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
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Composite materials are increasingly being used in aircraft, automobiles, and other applications due to their high strength to weight and stiffness to weight ratios. However, the presence of damage, such as delamination or matrix cracks, can significantly compromise the performance of these materials and result in premature failure. Structural components

Composite materials are increasingly being used in aircraft, automobiles, and other applications due to their high strength to weight and stiffness to weight ratios. However, the presence of damage, such as delamination or matrix cracks, can significantly compromise the performance of these materials and result in premature failure. Structural components are often manually inspected to detect the presence of damage. This technique, known as schedule based maintenance, however, is expensive, time-consuming, and often limited to easily accessible structural elements. Therefore, there is an increased demand for robust and efficient Structural Health Monitoring (SHM) techniques that can be used for Condition Based Monitoring, which is the method in which structural components are inspected based upon damage metrics as opposed to flight hours. SHM relies on in situ frameworks for detecting early signs of damage in exposed and unexposed structural elements, offering not only reduced number of schedule based inspections, but also providing better useful life estimates. SHM frameworks require the development of different sensing technologies, algorithms, and procedures to detect, localize, quantify, characterize, as well as assess overall damage in aerospace structures so that strong estimations in the remaining useful life can be determined. The use of piezoelectric transducers along with guided Lamb waves is a method that has received considerable attention due to the weight, cost, and function of the systems based on these elements. The research in this thesis investigates the ability of Lamb waves to detect damage in feature dense anisotropic composite panels. Most current research negates the effects of experimental variability by performing tests on structurally simple isotropic plates that are used as a baseline and damaged specimen. However, in actual applications, variability cannot be negated, and therefore there is a need to research the effects of complex sample geometries, environmental operating conditions, and the effects of variability in material properties. This research is based on experiments conducted on a single blade-stiffened anisotropic composite panel that localizes delamination damage caused by impact. The overall goal was to utilize a correlative approach that used only the damage feature produced by the delamination as the damage index. This approach was adopted because it offered a simplistic way to determine the existence and location of damage without having to conduct a more complex wave propagation analysis or having to take into account the geometric complexities of the test specimen. Results showed that even in a complex structure, if the damage feature can be extracted and measured, then an appropriate damage index can be associated to it and the location of the damage can be inferred using a dense sensor array. The second experiment presented in this research studies the effects of temperature on damage detection when using one test specimen for a benchmark data set and another for damage data collection. This expands the previous experiment into exploring not only the effects of variable temperature, but also the effects of high experimental variability. Results from this work show that the damage feature in the data is not only extractable at higher temperatures, but that the data from one panel at one temperature can be directly compared to another panel at another temperature for baseline comparison due to linearity of the collected data.
ContributorsVizzini, Anthony James, II (Author) / Chattopadhyay, Aditi (Thesis advisor) / Fard, Masoud (Committee member) / Papandreou-Suppappola, Antonia (Committee member) / Arizona State University (Publisher)
Created2012
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The NFL is one of largest and most influential industries in the world. In America there are few companies that have a stronger hold on the American culture and create such a phenomena from year to year. In this project aimed to develop a strategy that helps an NFL team

The NFL is one of largest and most influential industries in the world. In America there are few companies that have a stronger hold on the American culture and create such a phenomena from year to year. In this project aimed to develop a strategy that helps an NFL team be as successful as possible by defining which positions are most important to a team's success. Data from fifteen years of NFL games was collected and information on every player in the league was analyzed. First there needed to be a benchmark which describes a team as being average and then every player in the NFL must be compared to that average. Based on properties of linear regression using ordinary least squares this project aims to define such a model that shows each position's importance. Finally, once such a model had been established then the focus turned to the NFL draft in which the goal was to find a strategy of where each position needs to be drafted so that it is most likely to give the best payoff based on the results of the regression in part one.
ContributorsBalzer, Kevin Ryan (Author) / Goegan, Brian (Thesis director) / Dassanayake, Maduranga (Committee member) / Barrett, The Honors College (Contributor) / Economics Program in CLAS (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2015-05
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In the words of W. Edwards Deming, "the central problem in management and in leadership is failure to understand the information in variation." While many quality management programs propose the institution of technical training in advanced statistical methods, this paper proposes that by understanding the fundamental information behind statistical theory,

In the words of W. Edwards Deming, "the central problem in management and in leadership is failure to understand the information in variation." While many quality management programs propose the institution of technical training in advanced statistical methods, this paper proposes that by understanding the fundamental information behind statistical theory, and by minimizing bias and variance while fully utilizing the available information about the system at hand, one can make valuable, accurate predictions about the future. Combining this knowledge with the work of quality gurus W. E. Deming, Eliyahu Goldratt, and Dean Kashiwagi, a framework for making valuable predictions for continuous improvement is made. After this information is synthesized, it is concluded that the best way to make accurate, informative predictions about the future is to "balance the present and future," seeing the future through the lens of the present and thus minimizing bias, variance, and risk.
ContributorsSynodis, Nicholas Dahn (Author) / Kashiwagi, Dean (Thesis director, Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2015-05
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Analytic research on basketball games is growing quickly, specifically in the National Basketball Association. This paper explored the development of this analytic research and discovered that there has been a focus on individual player metrics and a dearth of quantitative team characterizations and evaluations. Consequently, this paper continued the exploratory

Analytic research on basketball games is growing quickly, specifically in the National Basketball Association. This paper explored the development of this analytic research and discovered that there has been a focus on individual player metrics and a dearth of quantitative team characterizations and evaluations. Consequently, this paper continued the exploratory research of Fewell and Armbruster's "Basketball teams as strategic networks" (2012), which modeled basketball teams as networks and used metrics to characterize team strategy in the NBA's 2010 playoffs. Individual players and outcomes were nodes and passes and actions were the links. This paper used data that was recorded from playoff games of the two 2012 NBA finalists: the Miami Heat and the Oklahoma City Thunder. The same metrics that Fewell and Armbruster used were explained, then calculated using this data. The offensive networks of these two teams during the playoffs were analyzed and interpreted by using other data and qualitative characterization of the teams' strategies; the paper found that the calculated metrics largely matched with our qualitative characterizations of the teams. The validity of the metrics in this paper and Fewell and Armbruster's paper was then discussed, and modeling basketball teams as multiple-order Markov chains rather than as networks was explored.
ContributorsMohanraj, Hariharan (Co-author) / Choi, David (Co-author) / Armbruster, Dieter (Thesis director) / Fewell, Jennifer (Committee member) / Brooks, Daniel (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2013-05
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A model has been developed to modify Euler-Bernoulli beam theory for wooden beams, using visible properties of wood knot-defects. Treating knots in a beam as a system of two ellipses that change the local bending stiffness has been shown to improve the fit of a theoretical beam displacement function to

A model has been developed to modify Euler-Bernoulli beam theory for wooden beams, using visible properties of wood knot-defects. Treating knots in a beam as a system of two ellipses that change the local bending stiffness has been shown to improve the fit of a theoretical beam displacement function to edge-line deflection data extracted from digital imagery of experimentally loaded beams. In addition, an Ellipse Logistic Model (ELM) has been proposed, using L1-regularized logistic regression, to predict the impact of a knot on the displacement of a beam. By classifying a knot as severely positive or negative, vs. mildly positive or negative, ELM can classify knots that lead to large changes to beam deflection, while not over-emphasizing knots that may not be a problem. Using ELM with a regression-fit Young's Modulus on three-point bending of Douglass Fir, it is possible estimate the effects a knot will have on the shape of the resulting displacement curve.
Created2015-05
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Chapter 1: Functional Specialization and Arm Length in Octopus bimaculoides<br/>Although studies are limited, there is some evidence that octopuses use their arms for specialized functions. For example, in Octopus maya and O. vulgaris, the anterior arms are utilized more frequently for grasping and exploring (Lee, 1992; Byrne et al., 2006a),

Chapter 1: Functional Specialization and Arm Length in Octopus bimaculoides<br/>Although studies are limited, there is some evidence that octopuses use their arms for specialized functions. For example, in Octopus maya and O. vulgaris, the anterior arms are utilized more frequently for grasping and exploring (Lee, 1992; Byrne et al., 2006a), while posterior arms are more frequently utilized for crawling in O. vulgaris (Levy et al., 2015). In addition, O. vulgaris uses favored arms when retrieving food and making contact with a T-maze as dictated by their lateralized vision (Byrne, 2006b). O. vulgaris also demonstrates a preference for anterior arms when retrieving food from a Y-maze (Gutnick et. al. 2020). In Octopus bimaculoides bending and elongation were more frequent in anterior arms than posterior arms during reaching and grasping tasks, and right arms displayed deformation more frequently than left arms, with the exception of the hectocotylus (R3) in males (Kennedy et. al. 2020). Given these observed functional differences, the goal of this study was to determine if morphological differences exist between different octopus arm identities, coded as L1-L4 and R1-R4. In particular, the relationship between arm length and arm identity was analyzed statistically. The dataset included 111 intact arms from 22 wild-caught specimens of O. bimaculoides (11 male and 11 female). Simple linear regressions and an analysis of covariance were performed to test the relationship between arm length and a number of factors, including body mass, sex, anterior versus posterior location, and left versus the right side. Mass had a significant linear relationship with arm length and a one-way ANOVA demonstrated that arm identity is significantly correlated with arm length. Moreover, an analysis of covariance demonstrated that independent of mass, arm identity has a significant linear relationship with arm length. Despite an overall appearance of bilateral symmetry, arms of different identities do not have statistically equivalent lengths in O. bimaculoides. Furthermore, differences in arm length do not appear to be related to sex, anterior versus posterior location, or left or right side. These results call into question the existing practice of treating all arms as equivalent by either using a single-arm measurement as representative of all eight or calculating an average length and suggest that morphological analyses of specific arm identities may be more informative.<br/><br/>Chapter 2: Predicting and Analyzing Octopus bimaculoides Sensitivity to Global Anesthetic<br/>Although global anesthetic is widely used in human and veterinary medicine the mechanism and impact of global anesthetic is relatively poorly comprehended, even in well-studied mammalian models. Invertebrate anesthetic is even less understood. In order to evaluate factors that impact anesthetic effectiveness analyses were conducted on 22 wild-caught specimens of Octopus bimaculoides during 72 anesthetic events.Three machine learning models: regression tree, random forest, and generalized additive model were utilized to make predictions of the concentration of anesthetic (percent ethanol by volume) from 11 features and to determine feature importance in making those predictions. The fit of each model was analyzed on three criteria: correlation coefficient, mean squared error, and relative error. Feature importance was determined in a model-specific manner. Predictions from the best performing model, random forest, have a .82 correlation coefficient with experimental values. Feature importance suggests that temperature on arrival and cohabitation factors strongly influence predictions for anesthesia concentration. This likely indicates the transportation process was incurring stress on the animals and that cohabitation was also stressful for the typically solitary O. bimaculoides. This long-term stress could lead to a decline in the animal’s well-being and a lower necessary ethanol concentration (Horvath et al., 2013). This analysis provides information to improve the care of octopus in laboratory settings and furthers the understanding of the effects of global anesthetic in invertebrates, particularly one with a distributed nervous system.

ContributorsSorge, Marieke Alexandria (Author) / Fisher, Rebecca (Thesis director) / Zhao, Yunpeng (Committee member) / Marvi, Hamid (Committee member) / School of Life Sciences (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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The concentration factor edge detection method was developed to compute the locations and values of jump discontinuities in a piecewise-analytic function from its first few Fourier series coecients. The method approximates the singular support of a piecewise smooth function using an altered Fourier conjugate partial sum. The accuracy and characteristic

The concentration factor edge detection method was developed to compute the locations and values of jump discontinuities in a piecewise-analytic function from its first few Fourier series coecients. The method approximates the singular support of a piecewise smooth function using an altered Fourier conjugate partial sum. The accuracy and characteristic features of the resulting jump function approximation depends on these lters, known as concentration factors. Recent research showed that that these concentration factors could be designed using aexible iterative framework, improving upon the overall accuracy and robustness of the method, especially in the case where some Fourier data are untrustworthy or altogether missing. Hypothesis testing methods were used to determine how well the original concentration factor method could locate edges using noisy Fourier data. This thesis combines the iterative design aspect of concentration factor design and hypothesis testing by presenting a new algorithm that incorporates multiple concentration factors into one statistical test, which proves more ective at determining jump discontinuities than the previous HT methods. This thesis also examines how the quantity and location of Fourier data act the accuracy of HT methods. Numerical examples are provided.
ContributorsLubold, Shane Michael (Author) / Gelb, Anne (Thesis director) / Cochran, Doug (Committee member) / Viswanathan, Aditya (Committee member) / Economics Program in CLAS (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05