Matching Items (56)
Filtering by

Clear all filters

156712-Thumbnail Image.png
Description
Fatigue is a degradation process of materials that would lead to failure when materials are subjected to cyclic loadings. During past centuries, various of approaches have been proposed and utilized to help researchers understand the underlying theories of fatigue behavior of materials, as well as design engineering structures so that

Fatigue is a degradation process of materials that would lead to failure when materials are subjected to cyclic loadings. During past centuries, various of approaches have been proposed and utilized to help researchers understand the underlying theories of fatigue behavior of materials, as well as design engineering structures so that catastrophic disasters that arise from fatigue failure could be avoided. The stress-life approach is the most classical way that academia applies to analyze fatigue data, which correlates the fatigue lifetime with stress amplitudes during cyclic loadings. Fracture mechanics approach is another well-established way, by which people regard the cyclic stress intensity factor as the driving force during fatigue crack nucleation and propagation, and numerous models (such as the well-known Paris’ law) are developed by researchers.

The significant drawback of currently widely-used fatigue analysis approaches, nevertheless, is that they are all cycle-based, limiting researchers from digging into sub-cycle regime and acquiring real-time fatigue behavior data. The missing of such data further impedes academia from validating hypotheses that are related to real-time observations of fatigue crack nucleation and growth, thus the existence of various phenomena, such as crack closure, remains controversial.

In this thesis, both classical stress-life approach and fracture-mechanics-based approach are utilized to study the fatigue behavior of alloys. Distinctive material characterization instruments are harnessed to help collect and interpret key data during fatigue crack growth. Specifically, an investigation on the sub-cycle fatigue crack growth behavior is enabled by in-situ SEM mechanical testing, and a non-uniform growth mechanism within one loading cycle is confirmed by direct observation as well as image interpretation. Predictions based on proposed experimental procedure and observations show good match with cycle-based data from references, which indicates the credibility of proposed methodology and model, as well as their capability of being applied to a wide range of materials.
ContributorsLiu, Siying (Author) / Liu, Yongming (Thesis advisor) / Jiao, Yang (Committee member) / Nian, Qiong (Committee member) / Arizona State University (Publisher)
Created2018
156902-Thumbnail Image.png
Description
Pipeline infrastructure forms a vital aspect of the United States economy and standard of living. A majority of the current pipeline systems were installed in the early 1900’s and often lack a reliable database reporting the mechanical properties, and information about manufacturing and installation, thereby raising a concern for their

Pipeline infrastructure forms a vital aspect of the United States economy and standard of living. A majority of the current pipeline systems were installed in the early 1900’s and often lack a reliable database reporting the mechanical properties, and information about manufacturing and installation, thereby raising a concern for their safety and integrity. Testing for the aging pipe strength and toughness estimation without interrupting the transmission and operations thus becomes important. The state-of-the-art techniques tend to focus on the single modality deterministic estimation of pipe strength and do not account for inhomogeneity and uncertainties, many others appear to rely on destructive means. These gaps provide an impetus for novel methods to better characterize the pipe material properties. The focus of this study is the design of a Bayesian Network information fusion model for the prediction of accurate probabilistic pipe strength and consequently the maximum allowable operating pressure. A multimodal diagnosis is performed by assessing the mechanical property variation within the pipe in terms of material property measurements, such as microstructure, composition, hardness and other mechanical properties through experimental analysis, which are then integrated with the Bayesian network model that uses a Markov chain Monte Carlo (MCMC) algorithm. Prototype testing is carried out for model verification, validation and demonstration and data training of the model is employed to obtain a more accurate measure of the probabilistic pipe strength. With a view of providing a holistic measure of material performance in service, the fatigue properties of the pipe steel are investigated. The variation in the fatigue crack growth rate (da/dN) along the direction of the pipe wall thickness is studied in relation to the microstructure and the material constants for the crack growth have been reported. A combination of imaging and composition analysis is incorporated to study the fracture surface of the fatigue specimen. Finally, some well-known statistical inference models are employed for prediction of manufacturing process parameters for steel pipelines. The adaptability of the small datasets for the accuracy of the prediction outcomes is discussed and the models are compared for their performance.
ContributorsDahire, Sonam (Author) / Liu, Yongming (Thesis advisor) / Jiao, Yang (Committee member) / Ren, Yi (Committee member) / Arizona State University (Publisher)
Created2018
157142-Thumbnail Image.png
Description
Collective cell migration in the 3D fibrous extracellular matrix (ECM) is crucial to many physiological and pathological processes such as tissue regeneration, immune response and cancer progression. A migrating cell also generates active pulling forces, which are transmitted to the ECM fibers via focal adhesion complexes. Such active forces consistently

Collective cell migration in the 3D fibrous extracellular matrix (ECM) is crucial to many physiological and pathological processes such as tissue regeneration, immune response and cancer progression. A migrating cell also generates active pulling forces, which are transmitted to the ECM fibers via focal adhesion complexes. Such active forces consistently remodel the local ECM (e.g., by re-orienting the collagen fibers, forming fiber bundles and increasing the local stiffness of ECM), leading to a dynamically evolving force network in the system that in turn regulates the collective migration of cells.

In this work, this novel mechanotaxis mechanism is investigated, i.e., the role of the ECM mediated active cellular force propagation in coordinating collective cell migration via computational modeling and simulations. The work mainly includes two components: (i) microstructure and micromechanics modeling of cellularized ECM (collagen) networks and (ii) modeling collective cell migration and self-organization in 3D ECM. For ECM modeling, a procedure for generating realizations of highly heterogeneous 3D collagen networks with prescribed microstructural statistics via stochastic optimization is devised. Analysis shows that oriented fibers can significantly enhance long-range force transmission in the network. For modeling collective migratory behaviors of the cells, a minimal active-particle-on-network (APN) model is developed, in which reveals a dynamic transition in the system as the particle number density ρ increases beyond a critical value ρc, from an absorbing state in which the particles segregate into small isolated stationary clusters, to a dynamic state in which the majority of the particles join in a single large cluster undergone constant dynamic reorganization. The results, which are consistent with independent experimental results, suggest a robust mechanism based on ECM-mediated mechanical coupling for collective cell behaviors in 3D ECM.

For the future plan, further substantiate the minimal cell migration model by incorporating more detailed cell-ECM interactions and relevant sub-cellular mechanisms is needed, as well as further investigation of the effects of fiber alignment, ECM mechanical properties and externally applied mechanical cues on collective migration dynamics.
ContributorsNan, Hanqing (Author) / Jiao, Yang (Thesis advisor) / Alford, Terry (Committee member) / Zhuang, Houlong (Committee member) / Arizona State University (Publisher)
Created2019
156953-Thumbnail Image.png
Description
Advanced material systems refer to materials that are comprised of multiple traditional constituents but complex microstructure morphologies, which lead to their superior properties over conventional materials. This dissertation is motivated by the grand challenge in accelerating the design of advanced material systems through systematic optimization with respect to material microstructures

Advanced material systems refer to materials that are comprised of multiple traditional constituents but complex microstructure morphologies, which lead to their superior properties over conventional materials. This dissertation is motivated by the grand challenge in accelerating the design of advanced material systems through systematic optimization with respect to material microstructures or processing settings. While optimization techniques have mature applications to a large range of engineering systems, their application to material design meets unique challenges due to the high dimensionality of microstructures and the high costs in computing process-structure-property (PSP) mappings. The key to addressing these challenges is the learning of material representations and predictive PSP mappings while managing a small data acquisition budget. This dissertation thus focuses on developing learning mechanisms that leverage context-specific meta-data and physics-based theories. Two research tasks will be conducted: In the first, we develop a statistical generative model that learns to characterize high-dimensional microstructure samples using low-dimensional features. We improve the data efficiency of a variational autoencoder by introducing a morphology loss to the training. We demonstrate that the resultant microstructure generator is morphology-aware when trained on a small set of material samples, and can effectively constrain the microstructure space during material design. In the second task, we investigate an active learning mechanism where new samples are acquired based on their violation to a theory-driven constraint on the physics-based model. We demonstrate using a topology optimization case that while data acquisition through the physics-based model is often expensive (e.g., obtaining microstructures through simulation or optimization processes), the evaluation of the constraint can be far more affordable (e.g., checking whether a solution is optimal or equilibrium). We show that this theory-driven learning algorithm can lead to much improved learning efficiency and generalization performance when such constraints can be derived. The outcomes of this research is a better understanding of how physics knowledge about material systems can be integrated into machine learning frameworks, in order to achieve more cost-effective and reliable learning of material representations and predictive models, which are essential to accelerate computational material design.
ContributorsCang, Ruijin (Author) / Ren, Yi (Thesis advisor) / Liu, Yongming (Committee member) / Jiao, Yang (Committee member) / Nian, Qiong (Committee member) / Zhuang, Houlong (Committee member) / Arizona State University (Publisher)
Created2018
133654-Thumbnail Image.png
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.

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

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
154719-Thumbnail Image.png
Description
Stress corrosion cracking (SCC) is a materials degradation phenomena resulting from a combination of stress and a corrosive environment. Among the alphabet soup of proposed mechanism of SCC the most important are film-rupture, film-induced cleavage and hydrogen embrittlement.

This work examines various aspects of film-induced cleavage in gold alloys for which

Stress corrosion cracking (SCC) is a materials degradation phenomena resulting from a combination of stress and a corrosive environment. Among the alphabet soup of proposed mechanism of SCC the most important are film-rupture, film-induced cleavage and hydrogen embrittlement.

This work examines various aspects of film-induced cleavage in gold alloys for which the operation of hydrogen embrittlement processes can be strictly ruled out on thermodynamic grounds. This is so because in such alloys SCC occurs under electrochemical conditions within which water is stable to hydrogen gas evolution. The alloy system examined in this work is AgAu since the corrosion processes in this system occur by a dealloying mechanism that results in the formation of nanoporous gold. The physics behind the dealloying process as well as the resulting formation of nanoporous gold is today well understood.

Two important aspects of the film-induced cleavage mechanism are examined in this work: dynamic fracture in monolithic nanoporous gold and crack injection. In crack injection there is a finite thickness dealloyed layer formed on a AgAu alloy sample and the question of whether or not a crack that nucleates within this layer can travel for some finite distance into the un-corroded parent phase alloy is addressed. Dynamic fracture tests were performed on single edge-notched monolithic nanoporous gold samples as well as “infinite strip” sample configurations for which the stress intensity remains constant over a significant portion of the crack length. High-speed photography was used to measure the crack velocity. In the dynamic fracture experiments cracks were observed to travel at speeds as large as 270 m/s corresponding to about 68% of the Raleigh wave velocity. Crack injection experiments were performed on single crystal Ag77Au23, polycrystalline Ag72Au28 and pure gold, all of which had thin nanoporous gold layers on the surface of samples. Through-thickness fracture was seen in both the single crystal and polycrystalline samples and there was an indication of ~ 1 μm injected cracks into pure gold. These results have important implications for the operation of the film-induced cleavage mechanism and represent a first step in the development of a fundamental model of SCC.
ContributorsChen, Xiying (Author) / Sieradzki, Karl (Thesis advisor) / Jiao, Yang (Committee member) / Oswald, Jay (Committee member) / Crozier, Peter (Committee member) / Peralta, Pedro (Committee member) / Arizona State University (Publisher)
Created2016
154569-Thumbnail Image.png
Description
Nanolaminate composite materials consist of alternating layers of materials at the nanoscale (≤100 nm). Due to the nanometer scale thickness of their layers, these materials display unique and tailorable properties. This enables us to alter both mechanical attributes such as strength and wear properties, as well as functional characteristics such

Nanolaminate composite materials consist of alternating layers of materials at the nanoscale (≤100 nm). Due to the nanometer scale thickness of their layers, these materials display unique and tailorable properties. This enables us to alter both mechanical attributes such as strength and wear properties, as well as functional characteristics such as biocompatibility, optical, and electronic properties. This dissertation focuses on understanding the mechanical behavior of the Al-SiC system. From a practical perspective, these materials exhibit a combination of high toughness and strength which is attractive for many applications. Scientifically, these materials are interesting due to the large elastic modulus mismatch between the layers. This, paired with the small layer thickness, allows a unique opportunity for scientists to study the plastic deformation of metals under extreme amounts of constraint.

Previous studies are limited in scope and a more diverse range of mechanical characterization is required to understand both the advantages and limitations of these materials. One of the major challenges with testing these materials is that they are only able to be made in thicknesses on the order of micrometers so the testing methods are limited to small volume techniques. This work makes use of both microscale testing techniques from the literature as well as novel methodologies. Using these techniques we are able to gain insight into aspects of the material’s mechanical behavior such as the effects of layer orientation, flaw dependent fracture, tension-compression asymmetry, fracture toughness as a function of layer thickness, and shear behavior as a function of layer thickness.
ContributorsMayer, Carl Randolph (Author) / Chawla, Nikhilesh (Thesis advisor) / Jiang, Hanqing (Committee member) / Molina-Aldareguia, Jon (Committee member) / Rajagopalan, Jagannathan (Committee member) / Arizona State University (Publisher)
Created2016
154679-Thumbnail Image.png
Description
Mechanical behavior of metallic thin films at room temperature (RT) is relatively well characterized. However, measuring the high temperature mechanical properties of thin films poses several challenges. These include ensuring uniformity in sample temperature and minimizing temporal fluctuations due to ambient heat loss, in addition to difficulties involved in mechanical

Mechanical behavior of metallic thin films at room temperature (RT) is relatively well characterized. However, measuring the high temperature mechanical properties of thin films poses several challenges. These include ensuring uniformity in sample temperature and minimizing temporal fluctuations due to ambient heat loss, in addition to difficulties involved in mechanical testing of microscale samples. To address these issues, we designed and analyzed a MEMS-based high temperature tensile testing stage made from single crystal silicon. The freestanding thin film specimens were co-fabricated with the stage to ensure uniaxial loading. Multi-physics simulations of Joule heating, incorporating both radiation and convection heat transfer, were carried out using COMSOL to map the temperature distribution across the stage and the specimen. The simulations were validated using temperature measurements from a thermoreflectance microscope.
ContributorsEswarappa Prameela, Suhas (Author) / Rajagopalan, Jagannathan (Thesis advisor) / Wang, Liping (Committee member) / Jiao, Yang (Committee member) / Arizona State University (Publisher)
Created2016
155111-Thumbnail Image.png
Description
Nanocrystalline (NC) materials experience inherent microstructural instability when exposed to elevated temperature, deformation rates or loads over long periods of time which limits its applications as well as processing. The instability arises due to the predominance of grain boundary (GB) diffusional processes which hastens coarsening. This dissertation aims to provide

Nanocrystalline (NC) materials experience inherent microstructural instability when exposed to elevated temperature, deformation rates or loads over long periods of time which limits its applications as well as processing. The instability arises due to the predominance of grain boundary (GB) diffusional processes which hastens coarsening. This dissertation aims to provide a solution for the very first time, through the development and characterization of a bulk NC alloy system. The NC-Cu-Ta discussed here offers exceptional thermal stability in addition to superior strength and creep resistance. The systematic study of the behavior of this material will pave the way for future development of NC materials with a multitude of optimized properties for extreme applications.

In-situ and ex-situ TEM characterization, multiple strain-rate compression testing and atomistic modeling were employed to investigate the behavior of NC-Cu-Ta under intense heating, stress/strain-rate and creep conditions. Results reveal, that temperature influences the misfit strain, leading to a significant change in flow stress, despite which (strength) remains greater than all known NC metals. Further, this alloy was found to achieve and retain strengths which were over two orders of magnitude higher than most NC metals under elevated temperature conditions. Dislocation-based slip was found to predominate at elevated temperatures for both high- and low-strain rate testing whereas twinning was favored during low temperature high-strain rate testing. The solute concentration was also found to play a role in dictating the deformation where heterogeneous twinnability was found to decrease with an increase in Ta concentration.

A paradigm-shift in the creep response of NC-materials with unprecedented property combinations is also reported, i.e., high strength with extremely high temperature creep resistance (6-8 orders higher than other NC materials), in this NC-Cu-Ta-alloy. The unique combination of properties in these NC-alloys is achieved through a processing route that creates distinct GB-pinning nanoclusters of the solute that favor kinetic stability of grains.

Overall, this dissertation provides an understanding of the mechanical response of a stable alloy system to extreme conditions, which was previously unattainable, and a perspective on the design of a new class of NC alloys exhibiting a multitude of optimized high temperature properties.
ContributorsRajagopalan, Mansa (Author) / Solanki, Kiran N. (Thesis advisor) / Alford, Terry L. (Committee member) / Jiao, Yang (Committee member) / Darling, Kris A. (Committee member) / Arizona State University (Publisher)
Created2016