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Description
Damage detection in heterogeneous material systems is a complex problem and requires an in-depth understanding of the material characteristics and response under varying load and environmental conditions. A significant amount of research has been conducted in this field to enhance the fidelity of damage assessment methodologies, using a wide range of sensors and detection techniques, for both metallic materials and composites. However, detecting damage at the microscale is not possible with commercially available sensors. A probable way to approach this problem is through accurate and efficient multiscale modeling techniques, which are capable of tracking damage initiation at the microscale and propagation across the length scales. The output from these models will provide an improved understanding of damage initiation; the knowledge can be used in conjunction with information from physical sensors to improve the size of detectable damage. In this research, effort has been dedicated to develop multiscale modeling approaches and associated damage criteria for the estimation of damage evolution across the relevant length scales. Important issues such as length and time scales, anisotropy and variability in material properties at the microscale, and response under mechanical and thermal loading are addressed. Two different material systems have been studied: metallic material and a novel stress-sensitive epoxy polymer.
For metallic material (Al 2024-T351), the methodology initiates at the microscale where extensive material characterization is conducted to capture the microstructural variability. A statistical volume element (SVE) model is constructed to represent the material properties. Geometric and crystallographic features including grain orientation, misorientation, size, shape, principal axis direction and aspect ratio are captured. This SVE model provides a computationally efficient alternative to traditional techniques using representative volume element (RVE) models while maintaining statistical accuracy. A physics based multiscale damage criterion is developed to simulate the fatigue crack initiation. The crack growth rate and probable directions are estimated simultaneously.
Mechanically sensitive materials that exhibit specific chemical reactions upon external loading are currently being investigated for self-sensing applications. The "smart" polymer modeled in this research consists of epoxy resin, hardener, and a stress-sensitive material called mechanophore The mechanophore activation is based on covalent bond-breaking induced by external stimuli; this feature can be used for material-level damage detections. In this work Tris-(Cinnamoyl oxymethyl)-Ethane (TCE) is used as the cyclobutane-based mechanophore (stress-sensitive) material in the polymer matrix. The TCE embedded polymers have shown promising results in early damage detection through mechanically induced fluorescence. A spring-bead based network model, which bridges nanoscale information to higher length scales, has been developed to model this material system. The material is partitioned into discrete mass beads which are linked using linear springs at the microscale. A series of MD simulations were performed to define the spring stiffness in the statistical network model. By integrating multiple spring-bead models a network model has been developed to represent the material properties at the mesoscale. The model captures the statistical distribution of crosslinking degree of the polymer to represent the heterogeneous material properties at the microscale. The developed multiscale methodology is computationally efficient and provides a possible means to bridge multiple length scales (from 10 nm in MD simulation to 10 mm in FE model) without significant loss of accuracy. Parametric studies have been conducted to investigate the influence of the crosslinking degree on the material behavior. The developed methodology has been used to evaluate damage evolution in the self-sensing polymer.
For metallic material (Al 2024-T351), the methodology initiates at the microscale where extensive material characterization is conducted to capture the microstructural variability. A statistical volume element (SVE) model is constructed to represent the material properties. Geometric and crystallographic features including grain orientation, misorientation, size, shape, principal axis direction and aspect ratio are captured. This SVE model provides a computationally efficient alternative to traditional techniques using representative volume element (RVE) models while maintaining statistical accuracy. A physics based multiscale damage criterion is developed to simulate the fatigue crack initiation. The crack growth rate and probable directions are estimated simultaneously.
Mechanically sensitive materials that exhibit specific chemical reactions upon external loading are currently being investigated for self-sensing applications. The "smart" polymer modeled in this research consists of epoxy resin, hardener, and a stress-sensitive material called mechanophore The mechanophore activation is based on covalent bond-breaking induced by external stimuli; this feature can be used for material-level damage detections. In this work Tris-(Cinnamoyl oxymethyl)-Ethane (TCE) is used as the cyclobutane-based mechanophore (stress-sensitive) material in the polymer matrix. The TCE embedded polymers have shown promising results in early damage detection through mechanically induced fluorescence. A spring-bead based network model, which bridges nanoscale information to higher length scales, has been developed to model this material system. The material is partitioned into discrete mass beads which are linked using linear springs at the microscale. A series of MD simulations were performed to define the spring stiffness in the statistical network model. By integrating multiple spring-bead models a network model has been developed to represent the material properties at the mesoscale. The model captures the statistical distribution of crosslinking degree of the polymer to represent the heterogeneous material properties at the microscale. The developed multiscale methodology is computationally efficient and provides a possible means to bridge multiple length scales (from 10 nm in MD simulation to 10 mm in FE model) without significant loss of accuracy. Parametric studies have been conducted to investigate the influence of the crosslinking degree on the material behavior. The developed methodology has been used to evaluate damage evolution in the self-sensing polymer.
ContributorsZhang, Jinjun (Author) / Chattopadhyay, Aditi (Thesis advisor) / Dai, Lenore (Committee member) / Jiang, Hanqing (Committee member) / Papandreou-Suppappola, Antonia (Committee member) / Rajadas, John (Committee member) / Arizona State University (Publisher)
Created2014
Description
Identification of early damage in polymer composite materials is of significant importance so that preventative measures can be taken before the materials reach catastrophic failure. Scientists have been developing damage detection technologies over many years and recently, mechanophore-based polymers, in which mechanical energy is translated to activate a chemical transformation, have received increasing attention. More specifically, the damage can be made detectable by mechanochromic polymers, which provide a visible color change upon the scission of covalent bonds under stress. This dissertation focuses on the study of a novel self-sensing framework for identifying early and in-situ damage by employing unique stress-sensing mechanophores. Two types of mechanophores, cyclobutane and cyclooctane, were utilized, and the former formed from cinnamoyl moeities and the latter formed from anthracene upon photodimerization. The effects on the thermal and mechanical properties with the addition of the cyclobutane-based polymers into epoxy matrices were investigated. The emergence of cracks was detected by fluorescent signals at a strain level right after the yield point of the polymer blends, and the fluorescence intensified with the accumulation of strain. Similar to the mechanism of fluorescence emission from the cleavage of cyclobutane, the cyclooctane moiety generated fluorescent emission with a higher quantum yield upon cleavage. The experimental results also demonstrated the success of employing the cyclooctane type mechanophore as a potential force sensor, as the fluorescence intensification was correlated with the strain increase.
ContributorsZou, Jin (Author) / Dai, Lenore L (Thesis advisor) / Chattopadhyay, Aditi (Thesis advisor) / Lind, Mary L (Committee member) / Mu, Bin (Committee member) / Yu, Hongyu (Committee member) / Arizona State University (Publisher)
Created2014
Description
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
Description
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
Description
With the maturity of advanced composites as feasible structural materials for various applications there is a critical need to solve the challenge of designing these material systems for optimal performance. However, determining superior design methods requires a deep understanding of the material-structure properties at various length scales. Due to the length-scale dependent behavior of advanced composites, multiscale modeling techniques may be used to describe the dominant mechanisms of damage and failure in these material systems. With polymer matrix fiber composites and nanocomposites it becomes essential to include even the atomic length scale, where the resin-hardener-nanofiller molecules interact, in the multiscale modeling framework. Additionally, sources of variability are also critical to be included in these models due to the important role of uncertainty in advance composite behavior. Such a methodology should be able to describe length scale dependent mechanisms in a computationally efficient manner for the analysis of practical composite structures.
In the research presented in this dissertation, a comprehensive nano to macro multiscale framework is developed for the mechanical and multifunctional analysis of advanced composite materials and structures. An atomistically informed statistical multiscale model is developed for linear problems, to estimate and scale elastic properties of carbon fiber reinforced polymer composites (CFRPs) and carbon nanotube (CNT) enhanced CFRPs using information from molecular dynamics simulation of the resin-hardener-nanofiller nanoscale system. For modeling inelastic processes, an atomistically informed coupled damage-plasticity model is developed using the framework of continuum damage mechanics, where fundamental nanoscale covalent bond disassociation information is scaled up as a continuum scale damage identifying parameter. This damage model is coupled with a nanocomposite microstructure generation algorithm to study the sub-microscale damage mechanisms in CNT/CFRP microstructures. It is further integrated in a generalized method of cells (GMC) micromechanics model to create a low-fidelity computationally efficient nonlinear multiscale method with imperfect interfaces between the fiber and matrix, where the interface behavior is adopted from nanoscale MD simulations. This algorithm is used to understand damage mechanisms in adhesively bonded composite joints as a case study for the comprehensive nano to macroscale structural analysis of practical composites structures. At each length scale sources of variability are identified, characterized, and included in the multiscale modeling framework.
In the research presented in this dissertation, a comprehensive nano to macro multiscale framework is developed for the mechanical and multifunctional analysis of advanced composite materials and structures. An atomistically informed statistical multiscale model is developed for linear problems, to estimate and scale elastic properties of carbon fiber reinforced polymer composites (CFRPs) and carbon nanotube (CNT) enhanced CFRPs using information from molecular dynamics simulation of the resin-hardener-nanofiller nanoscale system. For modeling inelastic processes, an atomistically informed coupled damage-plasticity model is developed using the framework of continuum damage mechanics, where fundamental nanoscale covalent bond disassociation information is scaled up as a continuum scale damage identifying parameter. This damage model is coupled with a nanocomposite microstructure generation algorithm to study the sub-microscale damage mechanisms in CNT/CFRP microstructures. It is further integrated in a generalized method of cells (GMC) micromechanics model to create a low-fidelity computationally efficient nonlinear multiscale method with imperfect interfaces between the fiber and matrix, where the interface behavior is adopted from nanoscale MD simulations. This algorithm is used to understand damage mechanisms in adhesively bonded composite joints as a case study for the comprehensive nano to macroscale structural analysis of practical composites structures. At each length scale sources of variability are identified, characterized, and included in the multiscale modeling framework.
ContributorsRai, Ashwin (Author) / Chattopadhyay, Aditi (Thesis advisor) / Dai, Lenore (Committee member) / Jiang, Hanqing (Committee member) / Rajadas, John (Committee member) / Fard, Masoud Yekani (Committee member) / Arizona State University (Publisher)
Created2018
Description
Few studies have examined the correlations between individual characteristics and other popular forms of social media other than Facebook. This study explored the ways emerging adults use Instagram and Snapchat and examined the relationships between social media and individual characteristics. A sample of 393 participants were recruited from a large university in the Southwestern United States. The participants completed an online questionnaire that included a newly developed social media measure along with established measures that examined the individual characteristics of social comparison orientation, self-esteem, loneliness, contingent self-worth, narcissism, and life satisfaction. In the present study, more participants reported having an active Instagram account than an active Facebook or Snapchat account. Additionally, a higher number of participants also reported preferring Instagram and Snapchat compared to Facebook. Significant correlations were found between various individual characteristics and three aspects of social media use: overall time spent on social media, whether the individual felt that their time spent on social media was meaningful, and how the individual felt emotionally after comparing themselves to others' photos and posts. Potential explanations and implications of the results are discussed.
ContributorsArndorfer, Sydney (Author) / Field, Ryan (Thesis director) / Sechler, Casey (Committee member) / School of Community Resources and Development (Contributor) / Sanford School of Social and Family Dynamics (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
This paper looks at the growth of influencer marketing in application and how it has shifted the relationship between brands and consumers. Barriers to enter the space and methods of practice are discussed and analyzed to project the accessibility of obtaining influencer status. Best practices for brands and influencers are outlined based on research, and key findings are analyzed from interviewed participants that play an active role in the field. Another component of the paper includes the discussion of the significance of platform dependence regarding influencers and brands using social media channels to reach consumers. The dynamic of the relationship that exists between consumers, brands and platforms is demonstrated through a model to demonstrate the interdependence of the relationship. The final component of the paper involves the exploration of the field as an active participant through an experiment that was conducted by the researcher on behalf of the question: can anyone be an influencer? The answer to this question is explored through personal accounts on the journey during an eight month process of testing content creation and promotion to build awareness and increase engagement. The barriers to enter the space as an influencer and to collaborate with brands is addressed through the process of testing tactics and strategies on social channels, along with travel expeditions across Arizona to contribute to content creation purposed into blog articles. The findings throughout the paper are conclusive that the value of influencer marketing is increasing as more brands validate and utilize this method in their marketing efforts.
ContributorsDavis, Natalie Marie (Author) / Giles, Bret (Thesis director) / Schlacter, John (Committee member) / Department of Information Systems (Contributor) / Department of Marketing (Contributor) / Walter Cronkite School of Journalism and Mass Communication (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
The purpose of this essay is to explain how celebrities manage their brand, as an image and commodity, using social media. Merriam-Webster defines "celebrity" as the "state of being celebrated." This essay will continue to explain how this state of celebration is a manufactured idea by the individual and the media's portrayal. Celebrities are "well-known for their well-knowness" (Boorstin, 1961, p. 58). Boorstin (1961) explains celebrities achieve fame not for their achievements, but by creating a unique personality (as cited in Turner, 2004). Crowd culture, networks, and audience knowledge are tools celebrities must use to navigate digital nuances. They must manage performance of self, adhere to internet social norms, and the obsessive fame culture. Celebrities are often referred to have "star power" and have a certain "charisma." This cultural identity is "negotiated and formed" contrived by a team through promotion, publicity, and advertising (Turner, 2004). Celebrities market themselves through branded content, media used to promote a product, on their social media pages while targeting crowd cultures. Networks truly define how celebrities must brand themselves on social media. This person-to-person contact establishes fan and consumer connections that build the celebrity's base and following. Despite campaigning in a digital world, it goes back to people connecting with people, not accounts linking to accounts. Celebrities manufacture all of these strategies and tactics as they market themselves as a commodity to target crowd culture audiences. This is why targeting crowd cultures is vitally important for celebrities. This essay explores the techniques of select celebrities as they succeed and fail navigating digital nuances.
ContributorsPierce, Ellen (Author) / Jacoby, Jim (Thesis director) / Himberg, Julia (Committee member) / Department of English (Contributor) / Walter Cronkite School of Journalism and Mass Communication (Contributor) / Barrett, The Honors College (Contributor)
Created2017-12
Description
This thesis will examine the recruitment process of educated millennials coming from four-year institutions to their first job out of college. When referring to millennials throughout my research, I am specifically focusing on current college graduates in order to better relate to my own experiences as a soon-to-be-graduate seeking a job. I will examine the various recruiting techniques, i.e. channels to connect with graduates, and the hiring and interview process as a whole. This thesis will also discuss the challenges and differences of recruiting millennials versus other generations. It will also discuss the latest trends in college and early talent recruiting. In order to do this, I conducted a number of in-depth interviews with recruiters and hiring managers from various companies that recruit heavily from Arizona State University (ASU), in order to determine what these companies have done to be successful among young college graduates. I aimed to identify the specific techniques that these companies use to connect with recent college graduates, what skills these firms are looking for, and what the hiring process looks like for new millennial employees. I also conducted an extensive online literature search about recruiting educated millennials in the workforce, and I used that information as a basis to form my interview questions. The interviews were meant to confirm or deny that research, but the interviewees also revealed many new trends and insights. I hope that this information will be beneficial not only to college seniors seeking first-time employment, but also to other companies who feel that they are struggling to capture young talent.
ContributorsCapra, Alexandria Luccia (Author) / Kalika, Dale (Thesis director) / Eaton, Kathryn (Committee member) / W. P. Carey School of Business (Contributor) / Department of Marketing (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Nonprofits often struggle in fully implementing a successful social media strategy. These organizations neglect to create and maintain relationships with stakeholders, engage their audience, and build brand awareness in an online setting. As social media has essentially become one of the largest sources of information dissemination and one of the most populated platforms in the online world, a nonprofit's online presence has become increasingly important. Through a 22-day content analysis and 43-question survey that was distributed to the general public on Twitter and Facebook, this paper looks comprehensively into the elements and tactics used by Make-A-Wish, Halo and ALS Association. Based off of the research findings from this study, important aspects of these nonprofits' online strategy will be identified and analyzed.
ContributorsJoseph, Teresa Marie (Author) / Wu, Xu (Thesis director) / Thornton, Leslie (Committee member) / Department of Marketing (Contributor) / Walter Cronkite School of Journalism and Mass Communication (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05