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- All Subjects: engineering
- Creators: Mechanical and Aerospace Engineering Program
- Creators: Liu, Yongming
- Creators: Berman, Spring
Description
This research examines the current challenges of using Lamb wave interrogation methods to localize fatigue crack damage in a complex metallic structural component subjected to unknown temperatures. The goal of this work is to improve damage localization results for a structural component interrogated at an unknown temperature, by developing a probabilistic and reference-free framework for estimating Lamb wave velocities and the damage location. The methodology for damage localization at unknown temperatures includes the following key elements: i) a model that can describe the change in Lamb wave velocities with temperature; ii) the extension of an advanced time-frequency based signal processing technique for enhanced time-of-flight feature extraction from a dispersive signal; iii) the development of a Bayesian damage localization framework incorporating data association and sensor fusion. The technique requires no additional transducers to be installed on a structure, and allows for the estimation of both the temperature and the wave velocity in the component. Additionally, the framework of the algorithm allows it to function completely in an unsupervised manner by probabilistically accounting for all measurement origin uncertainty. The novel algorithm was experimentally validated using an aluminum lug joint with a growing fatigue crack. The lug joint was interrogated using piezoelectric transducers at multiple fatigue crack lengths, and at temperatures between 20°C and 80°C. The results showed that the algorithm could accurately predict the temperature and wave speed of the lug joint. The localization results for the fatigue damage were found to correlate well with the true locations at long crack lengths, but loss of accuracy was observed in localizing small cracks due to time-of-flight measurement errors. To validate the algorithm across a wider range of temperatures the electromechanically coupled LISA/SIM model was used to simulate the effects of temperatures. The numerical results showed that this approach would be capable of experimentally estimating the temperature and velocity in the lug joint for temperatures from -60°C to 150°C. The velocity estimation algorithm was found to significantly increase the accuracy of localization at temperatures above 120°C when error due to incorrect velocity selection begins to outweigh the error due to time-of-flight measurements.
ContributorsHensberry, Kevin (Author) / Chattopadhyay, Aditi (Thesis advisor) / Liu, Yongming (Committee member) / Papandreou-Suppappola, Antonia (Committee member) / Arizona State University (Publisher)
Created2013
Description
Aluminum alloys and their composites are attractive materials for applications requiring high strength-to-weight ratios and reasonable cost. Many of these applications, such as those in the aerospace industry, undergo fatigue loading. An understanding of the microstructural damage that occurs in these materials is critical in assessing their fatigue resistance. Two distinct experimental studies were performed to further the understanding of fatigue damage mechanisms in aluminum alloys and their composites, specifically fracture and plasticity. Fatigue resistance of metal matrix composites (MMCs) depends on many aspects of composite microstructure. Fatigue crack growth behavior is particularly dependent on the reinforcement characteristics and matrix microstructure. The goal of this work was to obtain a fundamental understanding of fatigue crack growth behavior in SiC particle-reinforced 2080 Al alloy composites. In situ X-ray synchrotron tomography was performed on two samples at low (R=0.1) and at high (R=0.6) R-ratios. The resulting reconstructed images were used to obtain three-dimensional (3D) rendering of the particles and fatigue crack. Behaviors of the particles and crack, as well as their interaction, were analyzed and quantified. Four-dimensional (4D) visual representations were constructed to aid in the overall understanding of damage evolution. During fatigue crack growth in ductile materials, a plastic zone is created in the region surrounding the crack tip. Knowledge of the plastic zone is important for the understanding of fatigue crack formation as well as subsequent growth behavior. The goal of this work was to quantify the 3D size and shape of the plastic zone in 7075 Al alloys. X-ray synchrotron tomography and Laue microdiffraction were used to non-destructively characterize the volume surrounding a fatigue crack tip. The precise 3D crack profile was segmented from the reconstructed tomography data. Depth-resolved Laue patterns were obtained using differential-aperture X-ray structural microscopy (DAXM), from which peak-broadening characteristics were quantified. Plasticity, as determined by the broadening of diffracted peaks, was mapped in 3D. Two-dimensional (2D) maps of plasticity were directly compared to the corresponding tomography slices. A 3D representation of the plastic zone surrounding the fatigue crack was generated by superimposing the mapped plasticity on the 3D crack profile.
ContributorsHruby, Peter (Author) / Chawla, Nikhilesh (Thesis advisor) / Solanki, Kiran (Committee member) / Liu, Yongming (Committee member) / Arizona State University (Publisher)
Created2014
Description
In this dissertation, the results of our comprehensive computational studies of disordered jammed (i.e., mechanically stable) packings of hard particles are presented, including the family of superdisks in 2D and ellipsoids in 3D Euclidean space. Following a very brief introduction to the hard-particle systems, the event driven molecular dynamics (EDMD) employed to generate the packing ensembles will be discussed. A large number of 2D packing configurations of superdisks are subsequently analyzed, through which a relatively accurate theoretical scheme for packing-fraction prediction based on local particle contact configurations is proposed and validated via additional numerical simulations. Moreover, the studies on binary ellipsoid packing in 3D are briefly discussed and the effects of different geometrical parameters on the final packing fraction are analyzed.
ContributorsXu, Yaopengxiao (Author) / Jiao, Yang (Thesis advisor) / Oswald, Jay (Committee member) / Liu, Yongming (Committee member) / Arizona State University (Publisher)
Created2014
Description
In this dissertation, three complex material systems including a novel class of hyperuniform composite materials, cellularized collagen gel and low melting point alloy (LMPA) composite are investigated, using statistical pattern characterization, stochastic microstructure reconstruction and micromechanical analysis. In Chapter 1, an introduction of this report is provided, in which a brief review is made about these three material systems. In Chapter 2, detailed discussion of the statistical morphological descriptors and a stochastic optimization approach for microstructure reconstruction is presented. In Chapter 3, the lattice particle method for micromechanical analysis of complex heterogeneous materials is introduced. In Chapter 4, a new class of hyperuniform heterogeneous material with superior mechanical properties is investigated. In Chapter 5, a bio-material system, i.e., cellularized collagen gel is modeled using correlation functions and stochastic reconstruction to study the collective dynamic behavior of the embed tumor cells. In chapter 6, LMPA soft robotic system is generated by generalizing the correlation functions and the rigidity tunability of this smart composite is discussed. In Chapter 7, a future work plan is presented.
ContributorsXu, Yaopengxiao (Author) / Jiao, Yang (Thesis advisor) / Liu, Yongming (Committee member) / Wang, Qing Hua (Committee member) / Ren, Yi (Committee member) / Arizona State University (Publisher)
Created2018
Description
The Autonomous Vehicle (AV), also known as self-driving car, promises to be a game changer for the transportation industry. This technology is predicted to drastically reduce the number of traffic fatalities due to human error [21].
However, road driving at any reasonable speed involves some risks. Therefore, even with high-tech AV algorithms and sophisticated sensors, there may be unavoidable crashes due to imperfection of the AV systems, or unexpected encounters with wildlife, children and pedestrians. Whenever there is a risk involved, there is the need for an ethical decision to be made [33].
While ethical and moral decision-making in humans has long been studied by experts, the advent of artificial intelligence (AI) also calls for machine ethics. To study the different moral and ethical decisions made by humans, experts may use the Trolley Problem [34], which is a scenario where one must pull a switch near a trolley track to redirect the trolley to kill one person on the track or do nothing, which will result in the deaths of five people. While it is important to take into account the input of members of a society and perform studies to understand how humans crash during unavoidable accidents to help program moral and ethical decision-making into self-driving cars, using the classical trolley problem is not ideal, as it is unrealistic and does not represent moral situations that people face in the real world.
This work seeks to increase the realism of the classical trolley problem for use in studies on moral and ethical decision-making by simulating realistic driving conditions in an immersive virtual environment with unavoidable crash scenarios, to investigate how drivers crash during these scenarios. Chapter 1 gives an in-depth background into autonomous vehicles and relevant ethical and moral problems; Chapter 2 describes current state-of-the-art online tools and simulators that were developed to study moral decision-making during unavoidable crashes. Chapters 3 focuses on building the simulator and the design of the crash scenarios. Chapter 4 describes human subjects experiments that were conducted with the simulator and their results, and Chapter 5 provides conclusions and avenues for future work.
However, road driving at any reasonable speed involves some risks. Therefore, even with high-tech AV algorithms and sophisticated sensors, there may be unavoidable crashes due to imperfection of the AV systems, or unexpected encounters with wildlife, children and pedestrians. Whenever there is a risk involved, there is the need for an ethical decision to be made [33].
While ethical and moral decision-making in humans has long been studied by experts, the advent of artificial intelligence (AI) also calls for machine ethics. To study the different moral and ethical decisions made by humans, experts may use the Trolley Problem [34], which is a scenario where one must pull a switch near a trolley track to redirect the trolley to kill one person on the track or do nothing, which will result in the deaths of five people. While it is important to take into account the input of members of a society and perform studies to understand how humans crash during unavoidable accidents to help program moral and ethical decision-making into self-driving cars, using the classical trolley problem is not ideal, as it is unrealistic and does not represent moral situations that people face in the real world.
This work seeks to increase the realism of the classical trolley problem for use in studies on moral and ethical decision-making by simulating realistic driving conditions in an immersive virtual environment with unavoidable crash scenarios, to investigate how drivers crash during these scenarios. Chapter 1 gives an in-depth background into autonomous vehicles and relevant ethical and moral problems; Chapter 2 describes current state-of-the-art online tools and simulators that were developed to study moral decision-making during unavoidable crashes. Chapters 3 focuses on building the simulator and the design of the crash scenarios. Chapter 4 describes human subjects experiments that were conducted with the simulator and their results, and Chapter 5 provides conclusions and avenues for future work.
ContributorsKankam, Immanuella (Author) / Berman, Spring (Thesis advisor) / Johnson, Kathryn (Committee member) / Yong, Sze Zheng (Committee member) / Arizona State University (Publisher)
Created2019
Description
Phase change materials (PCMs) are combined sensible-and-latent thermal energy storage materials that can be used to store and dissipate energy in the form of heat. PCMs incorporated into wall-element systems have been well-studied with respect to energy efficiency of building envelopes. New applications of PCMs in infrastructural concrete, e.g., for mitigating early-age cracking and freeze-and-thaw induced damage, have also been proposed. Hence, the focus of this dissertation is to develop a detailed understanding of the physic-chemical and thermo-mechanical characteristics of cementitious systems and novel coating systems for wall-elements containing PCM. The initial phase of this work assesses the influence of interface properties and inter-inclusion interactions between microencapsulated PCM, macroencapsulated PCM, and the cementitious matrix. The fact that these inclusions within the composites are by themselves heterogeneous, and contain multiple components necessitate careful application of models to predict the thermal properties. The next phase observes the influence of PCM inclusions on the fracture and fatigue behavior of PCM-cementitious composites. The compliant nature of the inclusion creates less variability in the fatigue life for these composites subjected to cyclic loading. The incorporation of small amounts of PCM is found to slightly improve the fracture properties compared to PCM free cementitious composites. Inelastic deformations at the crack-tip in the direction of crack opening are influenced by the microscale PCM inclusions. After initial laboratory characterization of the microstructure and evaluation of the thermo-mechanical performance of these systems, field scale applicability and performance were evaluated. Wireless temperature and strain sensors for smart monitoring were embedded within a conventional portland cement concrete pavement (PCCP) and a thermal control smart concrete pavement (TCSCP) containing PCM. The TCSCP exhibited enhanced thermal performance over multiple heating and cooling cycles. PCCP showed significant shrinkage behavior as a result of compressive strains in the reinforcement that were twice that of the TCSCP. For building applications, novel PCM-composites coatings were developed to improve and extend the thermal efficiency. These coatings demonstrated a delay in temperature by up to four hours and were found to be more cost-effective than traditional building insulating materials.
The results of this work prove the feasibility of PCMs as a temperature-regulating technology. Not only do PCMs reduce and control the temperature within cementitious systems without affecting the rate of early property development but they can also be used as an auto-adaptive technology capable of improving the thermal performance of building envelopes.
The results of this work prove the feasibility of PCMs as a temperature-regulating technology. Not only do PCMs reduce and control the temperature within cementitious systems without affecting the rate of early property development but they can also be used as an auto-adaptive technology capable of improving the thermal performance of building envelopes.
ContributorsAguayo, Matthew Joseph (Author) / Neithalath, Narayanan (Thesis advisor) / Rajan, Subramaniam D. (Committee member) / Mobasher, Barzin (Committee member) / Underwood, Benjamin (Committee member) / Liu, Yongming (Committee member) / Arizona State University (Publisher)
Created2018
Description
Over the past several years, there has been growing concern regarding concussions and traumatic brain injuries (TBIs) in all levels of sports. A concussion is a traumatic brain injury that occurs from a blow to the head. When a concussion occurs, the brain knocks against the walls of the skull. A concussion causes temporary loss of brain function leading to cognitive, physical, and emotional symptoms, such as confusion, vomiting,headache, nausea,depression, disturbed sleep, moodiness, and amnesia. Although the short-term effects of concussions are limited, the long-term effects of concussions, if untreated, can be devastating and even life-threatening. Concussions are having detrimental ramifications on society and it is important to know what these ramifications are. Concussions are a common occurrence in traditional physical sports such as soccer, basketball, and football. However, due to the violent nature of football (American football), concussions are more prevalent and the effects are more severe. Changes to rules and equipment, specifically helmets, have been made to reduce head impacts in football but there is not currently enough evidence to conclude that they significantly lessen the frequency and severity of concussions.
ContributorsLaughlin, Riley James (Author) / Squires, Kyle (Thesis director) / Shrake, Scott (Committee member) / Barrett, The Honors College (Contributor) / Mechanical and Aerospace Engineering Program (Contributor)
Created2015-05
Description
The flipped classroom is a teaching method that flips the activities done in and out of class, i.e., concepts are learned out of class and problems are worked in class under the supervision of the instructor. Studies have indicated several benefits of the FC, including improved performance and engagement. In the past years, further studies have investigated the benefits of FC in statics, dynamics, and mechanics of materials courses and indicate similar performance benefits. However, these studies address a need for additional studies to validate their results due to the short length of their research or small classroom size. In addition, many of these studies do not measure student attitudes, such as self-efficacy, or the difference in time spent out of class on coursework. The objective of this research is to determine the effectiveness of the flipped classroom system (FC) in comparison to the traditional classroom system (TC) in a large mechanics of materials course. Specifically, it aims to measure student performance, student self-efficacy, student attitudes on lecture quality, motivation, attendance, hours spent out of class, practice, and support, and difference in impact between high, middle, and low achieving students. In order to accomplish this, three undergraduate mechanics of materials courses were analyzed during the spring 2015 semester. One FC section served as the experimental group (92 students), while the two TC sections served as the control group (125 students). To analyze student self-efficacy and attitudes, a survey instrument was designed to measure 18 variables and was administered at the end of the semester. Standardized core outcomes were compared between groups to analyze performance. This paper presents the specific course framework used in this FC, detailed results of the quantitative and qualitative analysis, and discussion of strengths and weaknesses. Overall, an overwhelming majority of students were satisfied with FC and would like more of their classes taught using FC. Strengths of this teaching method include greater confidence, better focus, higher satisfaction with practice in class and assistance received from instructors and peers, more freedom to express ideas and questions in class, and less time required outside of class for coursework. Results also suggest that this method has a greater positive impact on high and low achieving students and leads to higher performance. The criticisms made by students focused on lecture videos to have more worked examples. Overall, results suggest that FC is more effective than TC in a large mechanics of materials course.
ContributorsLee, Andrew Ryan (Author) / Zhu, Haolin (Thesis director) / Middleton, James (Committee member) / Mechanical and Aerospace Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
A robotic exploration mission that would enter a lunar pit to characterize the environment is described. A hopping mechanism for the robot's mobility is proposed. Various methods of hopping drawn from research literature are discussed in detail. The feasibilities of mechanical, electric, fluid, and combustive methods are analyzed. Computer simulations show the mitigation of the risk of complex autonomous navigation systems. A mechanical hopping mechanism is designed to hop in Earth gravity and carry a payload half its mass. A physical experiment is completed and proves a need for further refinement of the prototype design. Future work is suggested to continue exploring hopping as a mobility method for the lunar robot.
ContributorsMcKinney, Tyler James (Author) / Thangavelautham, Jekan (Thesis director) / Robinson, Mark (Committee member) / Asphaug, Erik (Committee member) / Barrett, The Honors College (Contributor) / Mechanical and Aerospace Engineering Program (Contributor)
Created2015-05
Description
This thesis investigates the viability of a solar still for desalination of a personal water supply. The end goal of the project is to create a design that meets the output requirement while tailoring the components to focus on low cost so it would be feasible in the impoverished areas of the world. The primary requirement is an output of 3 liters of potable water per day, the minimum necessary for an adult human. The study examines the effect of several design parameters, such as the basin material, basin thickness, starting water depth, basin dimensions, cover material, cover angle, and cover thickness. A model for the performance of a solar still was created in MATLAB to simulate the system's behavior and sensitivity to these parameters. An instrumented prototype solar still demonstrated viability of the concept and provided data for validation of the MATLAB model.
ContributorsRasmussen, Dylan James (Author) / Wells, Valana (Thesis director) / Trimble, Steven (Committee member) / Barrett, The Honors College (Contributor) / Mechanical and Aerospace Engineering Program (Contributor)
Created2015-05