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The goal of this research is to compare the mechanical properties of CP-Ti and Ti-O and to understand the relationship between a material's microstructure and its response to fatigue. Titanium has been selected due to its desirable properties and applicability in several engineering fields. Both samples are polished and etched

The goal of this research is to compare the mechanical properties of CP-Ti and Ti-O and to understand the relationship between a material's microstructure and its response to fatigue. Titanium has been selected due to its desirable properties and applicability in several engineering fields. Both samples are polished and etched in order to visualize and characterize the microstructure and its features. The samples then undergo strain-controlled fatigue tests for several thousand cycles. Throughout testing, images of the samples are taken at zero and maximum load for DIC analysis. The DIC results can be used to study the local strains of the samples. The DIC analysis performed on the CP-Ti sample and presented in this study will be used to understand how the addition of oxygen in the Ti-O impacts fatigue response. The outcome of this research can be used to develop long-lasting, high strength materials.
ContributorsRiley, Erin Ashland (Author) / Solanki, Kiran (Thesis director) / Oswald, Jay (Committee member) / School of Art (Contributor) / Mechanical and Aerospace Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
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Description
Uncertainty quantification is critical for engineering design and analysis. Determining appropriate ways of dealing with uncertainties has been a constant challenge in engineering. Statistical methods provide a powerful aid to describe and understand uncertainties. This work focuses on applying Bayesian methods and machine learning in uncertainty quantification and prognostics among

Uncertainty quantification is critical for engineering design and analysis. Determining appropriate ways of dealing with uncertainties has been a constant challenge in engineering. Statistical methods provide a powerful aid to describe and understand uncertainties. This work focuses on applying Bayesian methods and machine learning in uncertainty quantification and prognostics among all the statistical methods. This study focuses on the mechanical properties of materials, both static and fatigue, the main engineering field on which this study focuses. This work can be summarized in the following items: First, maintaining the safety of vintage pipelines requires accurately estimating the strength. The objective is to predict the reliability-based strength using nondestructive multimodality surface information. Bayesian model averaging (BMA) is implemented for fusing multimodality non-destructive testing results for gas pipeline strength estimation. Several incremental improvements are proposed in the algorithm implementation. Second, the objective is to develop a statistical uncertainty quantification method for fatigue stress-life (S-N) curves with sparse data.Hierarchical Bayesian data augmentation (HBDA) is proposed to integrate hierarchical Bayesian modeling (HBM) and Bayesian data augmentation (BDA) to deal with sparse data problems for fatigue S-N curves. The third objective is to develop a physics-guided machine learning model to overcome limitations in parametric regression models and classical machine learning models for fatigue data analysis. A Probabilistic Physics-guided Neural Network (PPgNN) is proposed for probabilistic fatigue S-N curve estimation. This model is further developed for missing data and arbitrary output distribution problems. Fourth, multi-fidelity modeling combines the advantages of low- and high-fidelity models to achieve a required accuracy at a reasonable computation cost. The fourth objective is to develop a neural network approach for multi-fidelity modeling by learning the correlation between low- and high-fidelity models. Finally, conclusions are drawn, and future work is outlined based on the current study.
ContributorsChen, Jie (Author) / Liu, Yongming (Thesis advisor) / Chattopadhyay, Aditi (Committee member) / Mignolet, Marc (Committee member) / Ren, Yi (Committee member) / Yan, Hao (Committee member) / Arizona State University (Publisher)
Created2022
Description

This study experimentally investigated a selected methodology of mechanical torque testing of 3D printed gears. The motivation for pursuing this topic of research stemmed from a previous experience of one of the team members that propelled inspiration to quantify how different variables associated with 3D printing affect the structural integrity

This study experimentally investigated a selected methodology of mechanical torque testing of 3D printed gears. The motivation for pursuing this topic of research stemmed from a previous experience of one of the team members that propelled inspiration to quantify how different variables associated with 3D printing affect the structural integrity of the resulting piece. With this goal in mind, the team set forward with creating an experimental set-up and the construction of a test rig. However, due to restrictions in time and other unforeseen circumstances, this thesis underwent a change in scope. The new scope focused solely on determining if the selected methodology of mechanical torque testing was valid. Following the securement of parts and construction of a test rig, the team was able to conduct mechanical testing. This testing was done multiple times on an identically printed gear. The data collected showed results similar to a stress-strain curve when the torque was plotted against the angle of twist. In the resulting graph, the point of plastic deformation is clearly visible and the maximum torque the gear could withstand is clearly identifiable. Additionally, across the tests conducted, the results show high similarity in results. From this, it is possible to conclude that if the tests were repeated multiple times the maximum possible torque could be found. From that maximum possible torque, the mechanical strength of the tested gear could be identified.

ContributorsGarcia, Andres (Author) / Parekh, Mohan (Co-author) / Middleton, James (Thesis director) / Murthy, Raghavendra (Committee member) / Barrett, The Honors College (Contributor) / Mechanical and Aerospace Engineering Program (Contributor)
Created2023-05
Description

This study experimentally investigated a selected methodology of mechanical torque testing of 3D printed gears. The motivation for pursuing this topic of research stemmed from a previous experience of one of the team members that propelled inspiration to quantify how different variables associated with 3D printing affect the structural integrity

This study experimentally investigated a selected methodology of mechanical torque testing of 3D printed gears. The motivation for pursuing this topic of research stemmed from a previous experience of one of the team members that propelled inspiration to quantify how different variables associated with 3D printing affect the structural integrity of the resulting piece. With this goal in mind, the team set forward with creating an experimental set-up and the construction of a test rig. However, due to restrictions in time and other unforeseen circumstances, this thesis underwent a change in scope. The new scope focused solely on determining if the selected methodology of mechanical torque testing was valid. Following the securement of parts and construction of a test rig, the team was able to conduct mechanical testing. This testing was done multiple times on an identically printed gear. The data collected showed results similar to a stress-strain curve when the torque was plotted against the angle of twist. In the resulting graph, the point of plastic deformation is clearly visible and the maximum torque the gear could withstand is clearly identifiable. Additionally, across the tests conducted, the results show high similarity in results. From this, it is possible to conclude that if the tests were repeated multiple times the maximum possible torque could be found. From that maximum possible torque, the mechanical strength of the tested gear could be identified.

ContributorsParekh, Mohan (Author) / Garcia, Andres (Co-author) / Middleton, James (Thesis director) / Murthy, Raghavendra (Committee member) / Barrett, The Honors College (Contributor) / Mechanical and Aerospace Engineering Program (Contributor)
Created2023-05
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Description
Ultra-fast 2D/3D material microstructure reconstruction and quantitative structure-property mapping are crucial components of integrated computational material engineering (ICME). It is particularly challenging for modeling random heterogeneous materials such as alloys, composites, polymers, porous media, and granular matters, which exhibit strong randomness and variations of their material properties due to

Ultra-fast 2D/3D material microstructure reconstruction and quantitative structure-property mapping are crucial components of integrated computational material engineering (ICME). It is particularly challenging for modeling random heterogeneous materials such as alloys, composites, polymers, porous media, and granular matters, which exhibit strong randomness and variations of their material properties due to the hierarchical uncertainties associated with their complex microstructure at different length scales. Such uncertainties also exist in disordered hyperuniform systems that are statistically isotropic and possess no Bragg peaks like liquids and glasses, yet they suppress large-scale density fluctuations in a similar manner as in perfect crystals. The unique hyperuniform long-range order in these systems endow them with nearly optimal transport, electronic and mechanical properties. The concept of hyperuniformity was originally introduced for many-particle systems and has subsequently been generalized to heterogeneous materials such as porous media, composites, polymers, and biological tissues for unconventional property discovery. An explicit mixture random field (MRF) model is proposed to characterize and reconstruct multi-phase stochastic material property and microstructure simultaneously, where no additional tuning step nor iteration is needed compared with other stochastic optimization approaches such as the simulated annealing. The proposed method is shown to have ultra-high computational efficiency and only requires minimal imaging and property input data. Considering microscale uncertainties, the material reliability will face the challenge of high dimensionality. To deal with the so-called “curse of dimensionality”, efficient material reliability analysis methods are developed. Then, the explicit hierarchical uncertainty quantification model and efficient material reliability solvers are applied to reliability-based topology optimization to pursue the lightweight under reliability constraint defined based on structural mechanical responses. Efficient and accurate methods for high-resolution microstructure and hyperuniform microstructure reconstruction, high-dimensional material reliability analysis, and reliability-based topology optimization are developed. The proposed framework can be readily incorporated into ICME for probabilistic analysis, discovery of novel disordered hyperuniform materials, material design and optimization.
ContributorsGao, Yi (Author) / Liu, Yongming (Thesis advisor) / Jiao, Yang (Committee member) / Ren, Yi (Committee member) / Pan, Rong (Committee member) / Mignolet, Marc (Committee member) / Arizona State University (Publisher)
Created2021
Description
During the height of COVID-19 in the summer of 2020, most major sports leagues were shut down or postponed, to limit the spread of COVID-19. However, people still yearned for the community of cheering on their favorite team. To that end, The Game Band, a Los Angeles-based game development studio,

During the height of COVID-19 in the summer of 2020, most major sports leagues were shut down or postponed, to limit the spread of COVID-19. However, people still yearned for the community of cheering on their favorite team. To that end, The Game Band, a Los Angeles-based game development studio, decided to make America's favorite pastime, baseball, virtual. Just like that, Blaseball was born. In this creative project, the Season Twelve version of Blaseball.com was subjected to analysis of its user interface and user experience elements by the author of this paper in the role of the researcher. The research questions posited by this project were as follows: - What user interface/user experience elements of the Season Twelve version of Blaseball.com were effective, and what elements detracted from the purpose of the site? - What recommendations could be made by the researcher to improve the user experience and allow for a more effective user experience of the Season Twelve version of Blaseball.com? To answer these questions, two deliverables were decided upon. The first was a research study consisting of a usability survey and interviews with web developers who worked on Blaseball or Blaseball-related projects. The second deliverable was an industry-level analysis of the Season Twelve version of Blaseball.com to be presented as a culmination of the research and work. Through this process, it had been discovered that while the site was simplistic and could easily direct users to other pages, as intended by the developers, UI elements on individual pages confused and misled users. As such, clarifications and a more in-depth UI were recommended.
ContributorsLyons, Jacob (Author) / Selgrad, Justin (Thesis director) / Gray, Robert (Committee member) / Barrett, The Honors College (Contributor) / Computing and Informatics Program (Contributor) / Computer Science and Engineering Program (Contributor)
Created2022-05
Description

This thesis presents a comprehensive investigation into the design of roller coasters. The study includes an overview of various roller coaster types, cart design, brake design, lift hill and launch design, support design, and roller coaster safety. Utilizing No Limits 2 to design the layout and CAD software for component

This thesis presents a comprehensive investigation into the design of roller coasters. The study includes an overview of various roller coaster types, cart design, brake design, lift hill and launch design, support design, and roller coaster safety. Utilizing No Limits 2 to design the layout and CAD software for component design, a scale model roller coaster was designed. The physics of the roller coaster and its structures were analyzed and a scale model was produced. Afterward, an accelerometer was used to collect G force data as the cart moved along the track. However, the collected data differed from the expected results, as the launch speed was higher than predicted due to more friction than anticipated. As a result, further optimization of the design and models used to design the scale model roller coasters is necessary.

ContributorsCardinale, Matthew (Author) / Johnson, Kayla (Co-author) / Murthy, Raghavendra (Thesis director) / Singh, Anoop (Committee member) / Barrett, The Honors College (Contributor) / Mechanical and Aerospace Engineering Program (Contributor)
Created2023-05
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Description
The technology and science capabilities of SmallSats continue to grow with the increase of capabilities in commercial off the shelf components. However, the maturation of SmallSat hardware has also led to an increase in component power consumption, this poses an issue with using traditional passive thermal management systems (radiators, thermal

The technology and science capabilities of SmallSats continue to grow with the increase of capabilities in commercial off the shelf components. However, the maturation of SmallSat hardware has also led to an increase in component power consumption, this poses an issue with using traditional passive thermal management systems (radiators, thermal straps, etc.) to regulate high-power components. High power output becomes limited in order to maintain components within their allowable temperature ranges. The aim of this study is to explore new methods of using additive manufacturing to enable the usage of heat pipe structures on SmallSat platforms up to 3U’s in size. This analysis shows that these novel structures can increase the capabilities of SmallSat platforms by allowing for larger in-use heat loads from a nominal power density of 4.7 x 10^3 W/m3 to a higher 1.0 x 10^4 W/m3 , an order of magnitude increase. In addition, the mechanical properties of the SmallSat structure are also explored to characterize effects to the mechanical integrity of the spacecraft. The results show that the advent of heat pipe integration to the structures of SmallSats will lead to an increase in thermal management capabilities compared to the current state-of-the-art systems, while not reducing the structural integrity of the spacecraft. In turn, this will lead to larger science and technology capabilities for a field that is growing in both the education and private sectors.
ContributorsAcuna, Antonio (Author) / Das, Jnaneshwar (Thesis advisor) / Phelan, Patrick (Thesis advisor) / Mignolet, Marc (Committee member) / Arizona State University (Publisher)
Created2022
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Description
Aromatic polymers, with benzene-like rings in their main chains, include materials such as polyurea, an amorphous elastomer capable of dissipating large amounts of energy under dynamic loading, which makes it a promising coating for defensive systems. Although computational research exists that investigates the atomic-level response of polyurea and other amorphous

Aromatic polymers, with benzene-like rings in their main chains, include materials such as polyurea, an amorphous elastomer capable of dissipating large amounts of energy under dynamic loading, which makes it a promising coating for defensive systems. Although computational research exists that investigates the atomic-level response of polyurea and other amorphous aromatic polymers to extreme conditions, there is little experimental work to validate these models 1) at the atomic-scale and 2) under high pressures characteristic of extreme dynamic loading. Understanding structure-property relationships at the atomic-level is important for polymers, considering many of them undergo pressure and temperature-induced structural transformations, which must be understood to formulate accurate predictive models. This work aims to gain a deeper understanding of the high-pressure structural response of aromatic polymers at the atomic-level, with emphasis into the mechanisms associated with high-pressure transformations. Hence, atomic-level structural data at high pressures was obtained in situ via multiangle energy dispersive X-ray diffraction (EDXD) experiments at the Advanced Photon Source (APS) for polyurea and another amorphous aromatic polymer, polysulfone, chosen as a reference due to its relatively simple structure. Pressures up to 6 GPa were applied using a Paris Edinburgh (PE) hydraulic press at room temperature. Select polyurea samples were also heated to 277 °C at 6 GPa. The resulting structure factors and pair distribution functions, along with molecular dynamics simulations of polyurea provided by collaborators, suggest that the structures of both polymers are stable up to 6 GPa, aside from reductions in free-volume between polymer backbones. As higher pressures (≲ 32 GPa) were applied using diamond anvils in combination with the PE press, indications of structural transformations were observed in both polymers that appear similar in nature to the sp2-sp3 hybridization in compressed carbon. The transformation occurs gradually up to at least ~ 26 GPa in PSF, while it does not progress past ~ 15 GPa in polyurea. The changes are largely reversible, especially in polysulfone, consistent with pressure-driven, reversible graphite-diamond transformations in the absence of applied temperature. These results constitute some of the first in situ observations of the mechanisms that drive pressure-induced structural transformations in aromatic polymers.
ContributorsEastmond, Tyler (Author) / Peralta, Pedro (Thesis advisor) / Hoover, Christian (Committee member) / Hrubiak, Rostislav (Committee member) / Mignolet, Marc (Committee member) / Oswald, Jay (Committee member) / Arizona State University (Publisher)
Created2022
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Description
A new uniaxial testing apparatus that has been proposed takes advantage of less costly methods such as 3D printing of tensile fixtures and image reference markers for accurate data acquisition. The purpose of this research is to find methods to improve the resolution, accuracy, and repeatability of this newly designed

A new uniaxial testing apparatus that has been proposed takes advantage of less costly methods such as 3D printing of tensile fixtures and image reference markers for accurate data acquisition. The purpose of this research is to find methods to improve the resolution, accuracy, and repeatability of this newly designed testing apparatus. The first phase of the research involved building a program that optimized the testing apparatus design depending on the sample being tested. It was found that the design program allowed for quick modifications on the apparatus in order to test a wide variety of samples. The second phase of research was conducted using Finite Elements to determine which sample geometry reduced the impact of misalignment error most. It found that a previously proposed design by Dr. Wonmo Kang when combined with the testing apparatus lead to a large reduction in misalignment errors.
ContributorsAyoub, Yaseen (Author) / Kang, Wonmo (Thesis director) / Kashani, Hamzeh (Committee member) / Barrett, The Honors College (Contributor) / Mechanical and Aerospace Engineering Program (Contributor)
Created2022-12