ASU Electronic Theses and Dissertations
This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.
In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.
Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.
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- Creators: Lee, Hyunglae
Description
A robotic swarm can be defined as a large group of inexpensive, interchangeable
robots with limited sensing and/or actuating capabilities that cooperate (explicitly
or implicitly) based on local communications and sensing in order to complete a
mission. Its inherent redundancy provides flexibility and robustness to failures and
environmental disturbances which guarantee the proper completion of the required
task. At the same time, human intuition and cognition can prove very useful in
extreme situations where a fast and reliable solution is needed. This idea led to the
creation of the field of Human-Swarm Interfaces (HSI) which attempts to incorporate
the human element into the control of robotic swarms for increased robustness and
reliability. The aim of the present work is to extend the current state-of-the-art in HSI
by applying ideas and principles from the field of Brain-Computer Interfaces (BCI),
which has proven to be very useful for people with motor disabilities. At first, a
preliminary investigation about the connection of brain activity and the observation
of swarm collective behaviors is conducted. After showing that such a connection
may exist, a hybrid BCI system is presented for the control of a swarm of quadrotors.
The system is based on the combination of motor imagery and the input from a game
controller, while its feasibility is proven through an extensive experimental process.
Finally, speech imagery is proposed as an alternative mental task for BCI applications.
This is done through a series of rigorous experiments and appropriate data analysis.
This work suggests that the integration of BCI principles in HSI applications can be
successful and it can potentially lead to systems that are more intuitive for the users
than the current state-of-the-art. At the same time, it motivates further research in
the area and sets the stepping stones for the potential development of the field of
Brain-Swarm Interfaces (BSI).
robots with limited sensing and/or actuating capabilities that cooperate (explicitly
or implicitly) based on local communications and sensing in order to complete a
mission. Its inherent redundancy provides flexibility and robustness to failures and
environmental disturbances which guarantee the proper completion of the required
task. At the same time, human intuition and cognition can prove very useful in
extreme situations where a fast and reliable solution is needed. This idea led to the
creation of the field of Human-Swarm Interfaces (HSI) which attempts to incorporate
the human element into the control of robotic swarms for increased robustness and
reliability. The aim of the present work is to extend the current state-of-the-art in HSI
by applying ideas and principles from the field of Brain-Computer Interfaces (BCI),
which has proven to be very useful for people with motor disabilities. At first, a
preliminary investigation about the connection of brain activity and the observation
of swarm collective behaviors is conducted. After showing that such a connection
may exist, a hybrid BCI system is presented for the control of a swarm of quadrotors.
The system is based on the combination of motor imagery and the input from a game
controller, while its feasibility is proven through an extensive experimental process.
Finally, speech imagery is proposed as an alternative mental task for BCI applications.
This is done through a series of rigorous experiments and appropriate data analysis.
This work suggests that the integration of BCI principles in HSI applications can be
successful and it can potentially lead to systems that are more intuitive for the users
than the current state-of-the-art. At the same time, it motivates further research in
the area and sets the stepping stones for the potential development of the field of
Brain-Swarm Interfaces (BSI).
ContributorsKaravas, Georgios Konstantinos (Author) / Artemiadis, Panagiotis (Thesis advisor) / Berman, Spring M. (Committee member) / Lee, Hyunglae (Committee member) / Arizona State University (Publisher)
Created2017
Description
Sn and Al alloys are widely used in various industries. Environmental-induced damage resulting in whiskering in Sn and corrosion in Al account for numerous failures globally every year. Therefore, for designing materials that can better withstand these failures, a comprehensive study on the characterization of the damage is necessary. This research implements advanced characterization techniques to study the above-mentioned environmental-induced damage in Sn and Al alloys.
Tin based films are known to be susceptible to whisker growth resulting in numerous failures. While the mechanisms and factors affecting whisker growth have been studied extensively, not much has been reported on the mechanical properties of tin whiskers themselves. This study focuses on the tensile behavior of tin whiskers. Tensile tests of whiskers were conducted in situ a dual beam focused ion beam (FIB) with a scanning electron microscope (SEM) using a micro electro-mechanical system (MEMS) tensile testing stage. The deformation mechanisms of whiskers were analyzed using transmission electron microscopy (TEM).
Due to the heterogenous nature of the microstructure of Al 7075, it is susceptible to corrosion forming corrosion products and pits. These can be sites for cracks nucleation and propagation resulting in stress corrosion cracking (SCC). Therefore, complete understanding of the corrosion damaged region and its effect on the strength of the alloy is necessary. Several studies have been performed to visualize pits and understand their effect on the mechanical performance of Al alloys using two-dimensional (2D) approaches which are often inadequate. To get a thorough understanding of the pits, it is necessary for three-dimensional (3D) studies. In this study, Al 7075 alloys were corroded in 3.5 wt.% NaCl solution and X-ray tomography was used to obtain the 3D microstructure of pits enabling the quantification of their dimensions accurately. Furthermore, microstructure and mechanical property correlations helped in a better understanding of the effect of corrosion. Apart from the pits, a surface corrosion layer also forms on Al. A subsurface damage layer has also been identified that forms due to the aggressive nature of NaCl. Energy dispersive X-ray spectroscopy (EDX) and nanoindentation helped in identifying this region and understanding the variation in properties.
Tin based films are known to be susceptible to whisker growth resulting in numerous failures. While the mechanisms and factors affecting whisker growth have been studied extensively, not much has been reported on the mechanical properties of tin whiskers themselves. This study focuses on the tensile behavior of tin whiskers. Tensile tests of whiskers were conducted in situ a dual beam focused ion beam (FIB) with a scanning electron microscope (SEM) using a micro electro-mechanical system (MEMS) tensile testing stage. The deformation mechanisms of whiskers were analyzed using transmission electron microscopy (TEM).
Due to the heterogenous nature of the microstructure of Al 7075, it is susceptible to corrosion forming corrosion products and pits. These can be sites for cracks nucleation and propagation resulting in stress corrosion cracking (SCC). Therefore, complete understanding of the corrosion damaged region and its effect on the strength of the alloy is necessary. Several studies have been performed to visualize pits and understand their effect on the mechanical performance of Al alloys using two-dimensional (2D) approaches which are often inadequate. To get a thorough understanding of the pits, it is necessary for three-dimensional (3D) studies. In this study, Al 7075 alloys were corroded in 3.5 wt.% NaCl solution and X-ray tomography was used to obtain the 3D microstructure of pits enabling the quantification of their dimensions accurately. Furthermore, microstructure and mechanical property correlations helped in a better understanding of the effect of corrosion. Apart from the pits, a surface corrosion layer also forms on Al. A subsurface damage layer has also been identified that forms due to the aggressive nature of NaCl. Energy dispersive X-ray spectroscopy (EDX) and nanoindentation helped in identifying this region and understanding the variation in properties.
ContributorsVallabhaneni, Venkata Sathya Sai Renuka (Author) / Chawla, Nikhilesh (Thesis advisor) / Rajagopalan, Jagannathan (Committee member) / Solanki, Kiran (Committee member) / Arizona State University (Publisher)
Created2017
Description
Millions of individuals suffer from gait impairments due to stroke or other neurological disorders. A primary goal of patients is to walk independently, but most patients only achieve a poor functional outcome five years after injury. Despite the growing interest in using robotic devices for rehabilitation of sensorimotor function, state-of-the-art robotic interventions in gait therapy have not resulted in improved outcomes when compared to traditional treadmill-based therapy. Because bipedal walking requires neural coupling and dynamic interactions between the legs, a fundamental understanding of the sensorimotor mechanisms of inter-leg coordination during walking is needed to inform robotic interventions in gait therapy. This dissertation presents a systematic exploration of sensorimotor mechanisms of inter-leg coordination by studying the effect of unilateral perturbations of the walking surface stiffness on contralateral muscle activation in healthy populations. An analysis of the contribution of several sensory modalities to the muscle activation of the opposite leg provides new insight into the sensorimotor control mechanisms utilized in human walking, including the role of supra-spinal neural circuits in inter-leg coordination. Based on these insights, a model is created which relates the unilateral deflection of the walking surface to the resulting neuromuscular activation in the opposite leg. Additionally, case studies with hemiplegic walkers indicate the existence of the observed mechanism in neurologically impaired walkers. The results of this dissertation suggest a novel approach to gait therapy for hemiplegic patients in which desired muscle activity is evoked in the impaired leg by only interacting with the healthy leg. One of the most significant advantages of this approach over current rehabilitation protocols is the safety of the patient since there is no direct manipulation of the impaired leg. Therefore, the methods and results presented in this dissertation represent a potential paradigm shift in robot-assisted gait therapy.
ContributorsSkidmore, Jeffrey Alan (Author) / Artemiadis, Panagiotis (Thesis advisor) / Santello, Marco (Committee member) / Berman, Spring (Committee member) / Lee, Hyunglae (Committee member) / Marvi, Hamidreza (Committee member) / Arizona State University (Publisher)
Created2017
Description
The advancements in the technology of MEMS fabrication has been phenomenal in recent years. In no mean measure this has been the result of continued demand from the consumer electronics market to make devices smaller and better. MEMS inertial measuring units (IMUs) have found revolutionary applications in a wide array of fields like medical instrumentation, navigation, attitude stabilization and virtual reality. It has to be noted though that for advanced applications of motion tracking, navigation and guidance the cost of the IMUs is still pretty high. This is mainly because the process of calibration and signal processing used to get highly stable results from MEMS IMU is an expensive and time-consuming process. Also to be noted is the inevitability of using external sensors like GPS or camera for aiding the IMU data due to the error propagation in IMU measurements adds to the complexity of the system.
First an efficient technique is proposed to acquire clean and stable data from unaided IMU measurements and then proceed to use that system for tracking human motion. First part of this report details the design and development of the low-cost inertial measuring system ‘yIMU’. This thesis intends to bring together seemingly independent techniques that were highly application specific into one monolithic algorithm that is computationally efficient for generating reliable orientation estimates. Second part, systematically deals with development of a tracking routine for human limb movements. The validity of the system has then been verified.
The central idea is that in most cases the use of expensive MEMS IMUs is not warranted if robust smart algorithms can be deployed to gather data at a fraction of the cost. A low-cost prototype has been developed comparable to tactical grade performance for under $15 hardware. In order to further the practicability of this device we have applied it to human motion tracking with excellent results. The commerciality of device has hence been thoroughly established.
First an efficient technique is proposed to acquire clean and stable data from unaided IMU measurements and then proceed to use that system for tracking human motion. First part of this report details the design and development of the low-cost inertial measuring system ‘yIMU’. This thesis intends to bring together seemingly independent techniques that were highly application specific into one monolithic algorithm that is computationally efficient for generating reliable orientation estimates. Second part, systematically deals with development of a tracking routine for human limb movements. The validity of the system has then been verified.
The central idea is that in most cases the use of expensive MEMS IMUs is not warranted if robust smart algorithms can be deployed to gather data at a fraction of the cost. A low-cost prototype has been developed comparable to tactical grade performance for under $15 hardware. In order to further the practicability of this device we have applied it to human motion tracking with excellent results. The commerciality of device has hence been thoroughly established.
ContributorsShetty, Yatiraj K (Author) / Redkar, Sangram (Thesis advisor) / Sugar, Thomas (Committee member) / Berman, Spring (Committee member) / Lee, Hyunglae (Committee member) / Arizona State University (Publisher)
Created2016
Description
Over the past several years, the density of integrated circuits has been increasing at a very fast rate, following Moore’s law. The advent of three dimensional (3D) packaging technologies enable the increase in density of integrated circuits without necessarily shrinking the dimensions of the device. Under such constraints, the solder volume necessary to join the various layers of the package is also extremely small. At smaller length scales, the local cooling rates are higher, so the microstructures are much finer than that obtained in larger joints (BGA, C4). The fraction of intermetallic compounds (IMCs) present in solder joints in these volumes will be larger. The Cu6Sn5 precipitate size and spacing, and Sn grain structure and crystallography will be different at very small volumes. These factors will most certainly affect the performance of the solder. Examining the mechanical behavior and reliability of Pb-free solders is difficult, primarily because a methodology to characterize the microstructure and the mechanics of deformation at these extremely small length scales has yet to be developed.
In this study, Sn grain orientation and Cu6Sn5 IMC fraction, size, and morphology are characterized in 3D, in pure Sn based solder joints. The obtained results show differences in morphology of Sn grains and IMC precipitates as a function of location within the solder joint indicating influence of local cooling rate differences. Ex situ and in situ electromigration tests done on 250 um and 500 um pure Sn solder joints elucidate the evolution of microstructure, specifically Sn grain growth, IMC segregation and surface degradation. This research implements 3D quantification of microstructural features over micro and nano-scales, thereby enabling a multi-scale / multi-characterization approach.
In this study, Sn grain orientation and Cu6Sn5 IMC fraction, size, and morphology are characterized in 3D, in pure Sn based solder joints. The obtained results show differences in morphology of Sn grains and IMC precipitates as a function of location within the solder joint indicating influence of local cooling rate differences. Ex situ and in situ electromigration tests done on 250 um and 500 um pure Sn solder joints elucidate the evolution of microstructure, specifically Sn grain growth, IMC segregation and surface degradation. This research implements 3D quantification of microstructural features over micro and nano-scales, thereby enabling a multi-scale / multi-characterization approach.
ContributorsKirubanandham, Antony (Author) / Chawla, Nikhilesh (Thesis advisor) / Jiao, Yang (Committee member) / Lu, Minhua (Committee member) / Rajagopalan, Jagannathan (Committee member) / Arizona State University (Publisher)
Created2016
Description
An accurate knowledge of the complex microstructure of a heterogeneous material is crucial for quantitative structure-property relations establishment and its performance prediction and optimization. X-ray tomography has provided a non-destructive means for microstructure characterization in both 3D and 4D (i.e., structural evolution over time). Traditional reconstruction algorithms like filtered-back-projection (FBP) method or algebraic reconstruction techniques (ART) require huge number of tomographic projections and segmentation process before conducting microstructural quantification. This can be quite time consuming and computationally intensive.
In this thesis, a novel procedure is first presented that allows one to directly extract key structural information in forms of spatial correlation functions from limited x-ray tomography data. The key component of the procedure is the computation of a “probability map”, which provides the probability of an arbitrary point in the material system belonging to specific phase. The correlation functions of interest are then readily computed from the probability map. Using effective medium theory, accurate predictions of physical properties (e.g., elastic moduli) can be obtained.
Secondly, a stochastic optimization procedure that enables one to accurately reconstruct material microstructure from a small number of x-ray tomographic projections (e.g., 20 - 40) is presented. Moreover, a stochastic procedure for multi-modal data fusion is proposed, where both X-ray projections and correlation functions computed from limited 2D optical images are fused to accurately reconstruct complex heterogeneous materials in 3D. This multi-modal reconstruction algorithm is proved to be able to integrate the complementary data to perform an excellent optimization procedure, which indicates its high efficiency in using limited structural information.
Finally, the accuracy of the stochastic reconstruction procedure using limited X-ray projection data is ascertained by analyzing the microstructural degeneracy and the roughness of energy landscape associated with different number of projections. Ground-state degeneracy of a microstructure is found to decrease with increasing number of projections, which indicates a higher probability that the reconstructed configurations match the actual microstructure. The roughness of energy landscape can also provide information about the complexity and convergence behavior of the reconstruction for given microstructures and projection number.
In this thesis, a novel procedure is first presented that allows one to directly extract key structural information in forms of spatial correlation functions from limited x-ray tomography data. The key component of the procedure is the computation of a “probability map”, which provides the probability of an arbitrary point in the material system belonging to specific phase. The correlation functions of interest are then readily computed from the probability map. Using effective medium theory, accurate predictions of physical properties (e.g., elastic moduli) can be obtained.
Secondly, a stochastic optimization procedure that enables one to accurately reconstruct material microstructure from a small number of x-ray tomographic projections (e.g., 20 - 40) is presented. Moreover, a stochastic procedure for multi-modal data fusion is proposed, where both X-ray projections and correlation functions computed from limited 2D optical images are fused to accurately reconstruct complex heterogeneous materials in 3D. This multi-modal reconstruction algorithm is proved to be able to integrate the complementary data to perform an excellent optimization procedure, which indicates its high efficiency in using limited structural information.
Finally, the accuracy of the stochastic reconstruction procedure using limited X-ray projection data is ascertained by analyzing the microstructural degeneracy and the roughness of energy landscape associated with different number of projections. Ground-state degeneracy of a microstructure is found to decrease with increasing number of projections, which indicates a higher probability that the reconstructed configurations match the actual microstructure. The roughness of energy landscape can also provide information about the complexity and convergence behavior of the reconstruction for given microstructures and projection number.
ContributorsLi, Hechao (Author) / Jiao, Yang (Thesis advisor) / Chawla, Nikhilesh (Committee member) / Liu, Yongming (Committee member) / Ren, Yi (Committee member) / Mu, Bin (Committee member) / Arizona State University (Publisher)
Created2017
Description
This thesis work presents two separate studies:The first study assesses standing balance under various 2-dimensional (2D) compliant environments simulated using a dual-axis robotic platform and vision conditions. Directional virtual time-to-contact (VTC) measures were introduced to better characterize postural balance from both temporal and spatial aspects, and enable prediction of fall-relevant directions. Twenty healthy young adults were recruited to perform quiet standing tasks on the platform. Conventional stability measures, namely center-of-pressure (COP) path length and COP area, were also adopted for further comparisons with the proposed VTC. The results indicated that postural balance was adversely impacted, evidenced by significant decreases in VTC and increases in COP path length/area measures, as the ground compliance increased and/or in the absence of vision (ps < 0.001). Interaction effects between environment and vision were observed in VTC and COP path length measures (ps ≤ 0.05), but not COP area (p = 0.103). The estimated likelihood of falls in anterior-posterior (AP) and medio-lateral (ML) directions converged to nearly 50% (almost independent of the foot setting) as the experimental condition became significantly challenging.
The second study introduces a deep learning approach using convolutional neural network (CNN) for predicting environments based on instant observations of sway during balance tasks. COP data were collected from fourteen subjects while standing on the 2D compliant environments. Different window sizes for data segmentation were examined to identify its minimal length for reliable prediction. Commonly-used machine learning models were also tested to compare their effectiveness with that of the presented CNN model. The CNN achieved above 94.5% in the overall prediction accuracy even with 2.5-second length data, which cannot be achieved by traditional machine learning models (ps < 0.05). Increasing data length beyond 2.5 seconds slightly improved the accuracy of CNN but substantially increased training time (60% longer). Importantly, averaged normalized confusion matrices revealed that CNN is much more capable of differentiating the mid-level environmental condition.
These two studies provide new perspectives in human postural balance, which cannot be
interpreted by conventional stability analyses. Outcomes of these studies contribute to the advancement of human interactive robots/devices for fall prevention and rehabilitation.
ContributorsPhan, Vu Nguyen (Author) / Lee, Hyunglae (Thesis advisor) / Peterson, Daniel (Committee member) / Marvi, Hamidreza (Committee member) / Arizona State University (Publisher)
Created2021
Description
Glasses have many applications such as containers, substrates of displays, high strength fibers and portable electronic display panels. Their excellent mechanical properties such as high hardness, good forming ability and scratch resistance make glasses ideal for these applications. Many factors affect the selection of one glass over another for a given purpose such as cost, ingredients, scalability of manufacturing, etc. Typically, silicate based glasses are often selected because they satisfy most of the selection criteria. However, with the recent abundant use of these glasses in touch-based applications, understanding their abilities to dissipate energy due to surface contact loads has become increasingly desirable. The most common silicate glasses worldwide are glassy silica and soda lime. Calcium aluminosilicates are also gaining popularity due to their importance as substrates for display screens in electronic devices. The surface energy dissipation and strength of these glasses are based on several factors, but predominantly rely on ingredient composition and the so-called Indentation Size Effect (ISE), where the strength depends on the maximum surface force. Both the composition and ISE alter the strength and favored energy dissipation mechanisms of the glass. Unlocking the contribution of these mechanisms and elucidating their dependence on composition and force is the underlining goal of this thesis.Prior to cracking, silicate glasses can inelastically deform by shear and densification. However, the link between the mechanical properties, strength, glass structure and maximum force and the propensity by which either of these mechanisms are favored still remains unclear. In this study, the first aim is to elucidate the causes of the ISE and
i
explore the relationships between the ISE and the dissipation mechanisms, and identify what feature(s) of the glass can be used to infer their behavior. All glasses have shown a strong link between the ISE and shear flow and densification. Second, the link between composition and the dissipation mechanisms will be elucidated. This is accomplished by performing indentation tests coupled with an annealing method to independently quantify the amount of volume associated with each dissipation mechanism and elucidate relationships with ingredients and structure of the glasses. Some conclusions will then be presented that link all these behaviors together.
ContributorsKazembeyki, Maryam (Author) / Hoover, Christian G (Thesis advisor) / Rajan, Subramaniam (Committee member) / Neithalath, Narayanan (Committee member) / Chawla, Nikhilesh (Committee member) / Perreault, Francois (Committee member) / Arizona State University (Publisher)
Created2021
Description
Technological progress in robot sensing, design, and fabrication, and the availability of open source software frameworks such as the Robot Operating System (ROS), are advancing the applications of swarm robotics from toy problems to real-world tasks such as surveillance, precision agriculture, search-and-rescue, and infrastructure inspection. These applications will require the development of robot controllers and system architectures that scale well with the number of robots and that are robust to robot errors and failures. To achieve this, one approach is to design decentralized robot control policies that require only local sensing and local, ad-hoc communication. In particular, stochastic control policies can be designed that are agnostic to individual robot identities and do not require a priori information about the environment or sophisticated computation, sensing, navigation, or communication capabilities. This dissertation presents novel swarm control strategies with these properties for detecting and mapping static targets, which represent features of interest, in an
unknown, bounded, obstacle-free environment. The robots move on a finite spatial grid according to
the time-homogeneous transition probabilities of a Discrete-Time Discrete-State (DTDS) Markov chain model, and they exchange information with other robots within their communication range using a consensus (agreement) protocol. This dissertation extend theoretical guarantees on multi-robot consensus over fixed and time-varying communication networks with known connectivity properties to consensus over the networks that have Markovian switching dynamics and no presumed connectivity. This dissertation develops such swarm consensus strategies for detecting a single feature in the environment, tracking multiple features, and reconstructing a discrete distribution of features modeled as an occupancy grid map.
The proposed consensus approaches are validated in numerical simulations and in 3D physics-based simulations of quadrotors in Gazebo. The scalability of the proposed approaches is examined through extensive numerical simulation studies over different swarm populations and environment sizes.
ContributorsShirsat, Aniket (Author) / Berman, Spring (Thesis advisor) / Lee, Hyunglae (Committee member) / Marvi, Hamid (Committee member) / Saripalli, Srikanth (Committee member) / Gharavi, Lance (Committee member) / Arizona State University (Publisher)
Created2022
Description
Applications such as heat exchangers, surface-based cellular structures, rotating blades, and waveguides rely on thin metal walls as crucial constituent elements of the structure. The design freedom enabled by laser powder bed fusion has led to an interest in exploiting this technology to further the performance of these components, many of which retain their as-built surface morphologies on account of their design complexity. However, there is limited understanding of how and why mechanical properties vary by wall thickness for specimens that are additively manufactured and maintain an as-printed surface finish. Critically, the contributions of microstructure and morphology to the mechanical behavior of thin wall laser powder bed fusion structures have yet to be systematically identified and decoupled. This work focuses on elucidating the room temperature quasi-static tensile and high cycle fatigue properties of as-printed, thin-wall Inconel 718 fabricated using laser powder bed fusion, with the aim of addressing this critical gap in the literature. Wall thicknesses studied range from 0.3 - 2.0 mm, and the effects of Hot Isostatic Pressing are also examined, with sheet metal specimens used as a baseline for comparison. Statistical analyses are conducted to identify the significance of the dependence of properties on wall thickness and Hot Isostatic Pressing, as well as to examine correlations of these properties to section area, porosity, and surface roughness. A thorough microstructural study is complemented with a first-of-its-kind study of surface morphology to decouple their contributions and identify underlying causes for observed changes in mechanical properties. This thesis finds that mechanical properties in the quasi-static and fatigue framework do not see appreciable declines until specimen thickness is under 0.75 mm in thickness. The added Hot Isostatic Pressing heat treatment effectively closed pores, recrystallized the grain structure, and provided a more homogenous microstructure that benefits the modulus, tensile strength, elongation, and fatigue performance at higher stresses. Stress heterogeneities, primarily caused by surface defects, negatively affected the thinner specimens disproportionately. Without the use of the Hot Isostatic Pressing, the grain structure remained much more refined and benefitted the yield strength and fatigue endurance limit.
ContributorsParadise, Paul David (Author) / Bhate, Dhruv (Thesis advisor) / Chawla, Nikhilesh (Committee member) / Azeredo, Bruno (Committee member) / Jiao, Yang (Committee member) / Arizona State University (Publisher)
Created2022