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- Creators: Barrett, The Honors College
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
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
The vastly growing field of supercomputing is in dire need of a new measurement system to optimize JMRAM (Josephson junction magnetoresistive random access memory) devices. To effectively measure these devices, an ultra-low-noise, low cost cryogenic dipping probe with a dynamic voltage range is required. This dipping probe has been designed by ASU with <100 nVp-p noise, <10 nV offsets, 10 pV to 16 mV voltage range, and negligible thermoelectric drift. There is currently no other research group or company that can currently match both these low noise levels and wide voltage range. Two different dipping probes can be created with these specifications: one for high-use applications and one for low-use applications. The only difference between these probes is the outer shell; the high-use application probe has a shell made of G-10 fiberglass for a higher price, and the low-use application probe has a shell made of AISI 310 steel for a lower price. Both types of probes can be assembled in less than 8 hours for less than $2,500, requiring only soldering expertise. The low cost and short time to create these probes makes wide profit margins possible. The market for these cryogenic dipping probes is currently untapped, as most research groups and companies that use these probes build their own, which allows for rapid business growth. These potential consumers can be easily reached by marketing these probes at superconducting conferences. After several years of selling >50 probes, mass production can easily become possible by hiring several technicians, and still maintaining wide profit margins.
ContributorsHudson, Brooke Ashley (Author) / Adams, James (Thesis director) / Anwar, Shahriar (Committee member) / Materials Science and Engineering Program (Contributor) / W. P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Although wind turbine bearings are designed to operate 18-20 years, in the recent years premature failure among these bearings has caused this life to reduce to as low as a few months to a year. One of the leading causes of premature failure called white structure flaking is a mechanism that was first cited in literature decades ago but not much is understood about it even today. The cause of this mode of failure results from the initiation of white etched cracks (WECs). In this report, different failure mechanisms, especially premature failure mechanisms that were tested and analyzed are demonstrated as a pathway to understanding this phenomenon. Through the use of various tribometers, samples were tested in diverse and extreme conditions in order to study the effect of these different operational conditions on the specimen. Analysis of the tested samples allowed for a comparison of the microstructure alterations in the tested samples to the field bearings affected by WSF.
ContributorsSharma, Aman (Author) / Foy, Joseph (Thesis director) / Adams, James (Committee member) / Barrett, The Honors College (Contributor) / Mechanical and Aerospace Engineering Program (Contributor)
Created2015-05
Description
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.
ContributorsSexton, Thurston Bryant (Author) / Takahashi, Timothy (Thesis director) / Jones, Donald (Committee member) / Barrett, The Honors College (Contributor) / Mechanical and Aerospace Engineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / School of Human Evolution and Social Change (Contributor)
Created2015-05
Description
The following is a report that will evaluate the microstructure of the nickel-based superalloy Hastelloy X and its relationship to mechanical properties in different load conditions. Hastelloy X is of interest to the company AORA because its strength and oxidation resistance at high temperatures is directly applicable to their needs in a hybrid concentrated solar module. The literature review shows that the microstructure will produce different carbides at various temperatures, which can be beneficial to the strength of the alloy. These precipitates are found along the grain boundaries and act as pins that limit dislocation flow, as well as grain boundary sliding, and improve the rupture strength of the material. Over time, harmful precipitates form which counteract the strengthening effect of the carbides and reduce rupture strength, leading to failure. A combination of indentation and microstructure mapping was used in an effort to link local mechanical behavior to microstructure variability. Electron backscatter diffraction (EBSD) and energy dispersive spectroscopy (EDS) were initially used as a means to characterize the microstructure prior to testing. Then, a series of room temperature Vickers hardness tests at 50 and 500 gram-force were used to evaluate the variation in the local response as a function of indentation size. The room temperature study concluded that both the hardness and standard deviation increased at lower loads, which is consistent with the grain size distribution seen in the microstructure scan. The material was then subjected to high temperature spherical indentation. Load-displacement curves were essential in evaluating the decrease in strength of the material with increasing temperature. Through linear regression of the unloading portion of the curve, the plastic deformation was determined and compared at different temperatures as a qualitative method to evaluate local strength.
ContributorsCelaya, Andrew Jose (Author) / Peralta, Pedro (Thesis director) / Solanki, Kiran (Committee member) / Barrett, The Honors College (Contributor) / Mechanical and Aerospace Engineering Program (Contributor)
Created2015-05
Description
The transition to lead-free solder in the electronics industry has benefited the environment in many ways. However, with new materials systems comes new materials issues. During the processing of copper pads, a protective surface treatment is needed to prevent the copper from oxidizing. Characterizing the copper oxidation underneath the surface treatment is challenging but necessary for product reliability and failure analysis. Currently, FIB-SEM, which is time-consuming and expensive, is what is used to understand and analyze the surface treatment-copper oxide(s)-copper system. This project's goals were to determine a characterization methodology that cuts both characterization time and cost in half for characterizing copper oxidation beneath a surface treatment and to determine which protective surface treatment is the best as defined by multiple criterion such as cost, sustainability, and reliability. Two protective surface treatments, organic solderability preservative (OSP) and chromium zincate, were investigated, and multiple characterization techniques were researched. Six techniques were tested, and three were deemed promising. Through our studies, it was determined that the best surface treatment was organic solderability preservative (OSP) and the ideal characterization methodology would be using FIB-SEM to calibrate a QCM model, along with using SERA to confirm the QCM model results. The methodology we propose would result in a 91% reduction in characterization cost and a 92% reduction in characterization time. Future work includes further calibration of the QCM model using more FIB/SEM data points and eventually creating a model for oxide layer thickness as a function of exposure time and processing temperature using QCM as the primary data source. An additional short essay on the role of SEM on the continuing miniaturization of integrated circuits is included at the end. This paper explores the intertwined histories of the scanning electron microscope and the integrated circuit, highlighting how advances in SEM influence integrated circuit advances.
ContributorsSmith, Bethany Blair (Co-author) / Marion, Branch Kelly (Co-author) / Cruz, Hernandez (Co-author) / Kimberly, McGuiness (Co-author) / Adams, James (Thesis director) / Krause, Stephen (Committee member) / Barrett, The Honors College (Contributor) / Materials Science and Engineering Program (Contributor)
Created2015-05
Description
Widespread knowledge of fracture mechanics is mostly based on previous models that generalize crack growth in materials over several loading cycles. The objective of this project is to characterize crack growth that occurs in titanium alloys, specifically Grade 5 Ti-6Al-4V, at the sub-cycle scale, or within a single loading cycle. Using scanning electron microscopy (SEM), imaging analysis is performed to observe crack behavior at ten loading steps throughout the loading and unloading paths. Analysis involves measuring the incremental crack growth and crack tip opening displacement (CTOD) of specimens at loading ratios of 0.1, 0.3, and 0.5. This report defines the relationship between crack growth and the stress intensity factor, K, of the specimens, as well as the relationship between the R-ratio and stress opening level. The crack closure phenomena and effect of microcracks are discussed as they influence the crack growth behavior. This method has previously been used to characterize crack growth in Al 7075-T6. The results for Ti-6Al-4V are compared to these previous findings in order to strengthen conclusions about crack growth behavior.
ContributorsNazareno, Alyssa Noelle (Author) / Liu, Yongming (Thesis director) / Jiao, Yang (Committee member) / Mechanical and Aerospace Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
The study of the mechanical behavior of nanocrystalline metals using microelectromechanical systems (MEMS) devices lies at the intersection of nanotechnology, mechanical engineering and material science. The extremely small grains that make up nanocrystalline metals lead to higher strength but lower ductility as compared to bulk metals. Effects of strain-rate dependence on the mechanical behavior of nanocrystalline metals are explored. Knowing the strain rate dependence of mechanical properties would enable optimization of material selection for different applications and lead to lighter structural components and enhanced sustainability.
ContributorsHall, Andrea Paulette (Author) / Rajagopalan, Jagannathan (Thesis director) / Liao, Yabin (Committee member) / Barrett, The Honors College (Contributor) / Mechanical and Aerospace Engineering Program (Contributor)
Created2014-05
Description
Solid-state lithium-ion batteries are a major area of research due to their increased safety characteristics over conventional liquid electrolyte batteries. Lithium lanthanum zirconate (LLZO) is a promising garnet-type ceramic for use as a solid-state electrolyte due to its high ionic conductivity. The material exists in two dierent phases, one that is cubic in structure and one that is tetragonal. One potential synthesis method that results in LLZO in the more useful, cubic phase, is electrospinning, where a mat of nanowires is spun and then calcined into LLZO. A phase containing lanthanum zirconate (LZO) and amorphous lithium occursas an intermediate during the calcination process. LZO has been shown to be a sintering aid for LLZO, allowing for lower sintering temperatures. Here it is shown the eects of internal LZO on the sintered pellets. This is done by varying the 700C calcination time to transform diering amounts of LZO and LLZO in electrospun nanowires, and then using the same sintering parameters for each sample. X-ray diraction was used to get structural and compositional analysis of both the calcined powders and sintered pellets. Pellets formed from wires calcined at 1 hour or longer contained only LLZO even if the calcined powder had only undergone the rst phase transformation. The relative density of the pellet with no initial LLZO of 61.0% was higher than that of the pellet with no LZO, which had a relative density of 57.7%. This allows for the same, or slightly higher, quality material to be synthesized with a shorter amount of processing time.
ContributorsLondon, Nathan Harry (Author) / Chan, Candace (Thesis director) / Tongay, Sefaattin (Committee member) / Department of Physics (Contributor) / Materials Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05