Theses and Dissertations
This collection includes both ASU Theses and Dissertations, submitted by graduate students, and the Barrett, Honors College theses submitted by undergraduate students.
Displaying 1 - 4 of 4
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- All Subjects: Fatigue
- All Subjects: Damage Prognosis
Description
There is a concerted effort in developing robust systems health monitoring/management (SHM) technology as a means to reduce the life cycle costs, improve availability, extend life and minimize downtime of various platforms including aerospace and civil infrastructure. The implementation of a robust SHM system requires a collaborative effort in a variety of areas such as sensor development, damage detection and localization, physics based models, and prognosis models for residual useful life (RUL) estimation. Damage localization and prediction is further complicated by geometric, material, loading, and environmental variabilities. Therefore, it is essential to develop robust SHM methodologies by taking into account such uncertainties. In this research, damage localization and RUL estimation of two different physical systems are addressed: (i) fatigue crack propagation in metallic materials under complex multiaxial loading and (ii) temporal scour prediction near bridge piers. With little modifications, the methodologies developed can be applied to other systems.
Current practice in fatigue life prediction is based on either physics based modeling or data-driven methods, and is limited to predicting RUL for simple geometries under uniaxial loading conditions. In this research, crack initiation and propagation behavior under uniaxial and complex biaxial fatigue loading is addressed. The crack propagation behavior is studied by performing extensive material characterization and fatigue testing under in-plane biaxial loading, both in-phase and out-of-phase, with different biaxiality ratios. A hybrid prognosis model, which combines machine learning with physics based modeling, is developed to account for the uncertainties in crack propagation and fatigue life prediction due to variabilities in material microstructural characteristics, crack localization information and environmental changes. The methodology iteratively combines localization information with hybrid prognosis models using sequential Bayesian techniques. The results show significant improvements in the localization and prediction accuracy under varying temperature.
For civil infrastructure, especially bridges, pier scour is a major failure mechanism. Currently available techniques are developed from a design perspective and provide highly conservative scour estimates. In this research, a fully probabilistic scour prediction methodology is developed using machine learning to accurately predict scour in real-time under varying flow conditions.
Current practice in fatigue life prediction is based on either physics based modeling or data-driven methods, and is limited to predicting RUL for simple geometries under uniaxial loading conditions. In this research, crack initiation and propagation behavior under uniaxial and complex biaxial fatigue loading is addressed. The crack propagation behavior is studied by performing extensive material characterization and fatigue testing under in-plane biaxial loading, both in-phase and out-of-phase, with different biaxiality ratios. A hybrid prognosis model, which combines machine learning with physics based modeling, is developed to account for the uncertainties in crack propagation and fatigue life prediction due to variabilities in material microstructural characteristics, crack localization information and environmental changes. The methodology iteratively combines localization information with hybrid prognosis models using sequential Bayesian techniques. The results show significant improvements in the localization and prediction accuracy under varying temperature.
For civil infrastructure, especially bridges, pier scour is a major failure mechanism. Currently available techniques are developed from a design perspective and provide highly conservative scour estimates. In this research, a fully probabilistic scour prediction methodology is developed using machine learning to accurately predict scour in real-time under varying flow conditions.
ContributorsNeerukatti, Rajesh Kumar (Author) / Chattopadhyay, Aditi (Thesis advisor) / Jiang, Hanqing (Committee member) / Liu, Yongming (Committee member) / Rajadas, John (Committee member) / Yekani Fard, Masoud (Committee member) / Arizona State University (Publisher)
Created2016
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
Interstitial impurity atoms can significantly alter the chemical and physical properties of the host material. Oxygen impurity in HCP titanium is known to have a considerable strengthening effect mainly through interactions with dislocations. To better understand such an effect, first the role of oxygen on various slip planes in titanium is examined using generalized stacking fault energies (GSFE) computed by the first principles calculations. It is shown that oxygen can significantly increase the energy barrier to dislocation motion on most of the studied slip planes. Then the Peierls-Nabbaro model is utilized in conjunction with the GSFE to estimate the Peierls stress ratios for different slip systems. Using such information along with a set of tension and compression experiments, the parameters of a continuum scale crystal plasticity model, namely CRSS values, are calibrated. Effect of oxygen content on the macroscopic stress-strain response is further investigated through experiments on oxygen-boosted samples at room temperature. It is demonstrated that the crystal plasticity model can very well capture the effect of oxygen content on the global response of the samples. It is also revealed that oxygen promotes the slip activity on the pyramidal planes.
The effect of oxygen impurity on titanium is further investigated under high cycle fatigue loading. For that purpose, a two-step hierarchical crystal plasticity for fatigue predictions is presented. Fatigue indicator parameter is used as the main driving force in an energy-based crack nucleation model. To calculate the FIPs, high-resolution full-field crystal plasticity simulations are carried out using a spectral solver. A nucleation model is proposed and calibrated by the fatigue experimental data for notched titanium samples with different oxygen contents and under two load ratios. Overall, it is shown that the presented approach is capable of predicting the high cycle fatigue nucleation time. Moreover, qualitative predictions of microstructurally small crack growth rates are provided. The multi-scale methodology presented here can be extended to other material systems to facilitate a better understanding of the fundamental deformation mechanisms, and to effectively implement such knowledge in mesoscale-macroscale investigations.
The effect of oxygen impurity on titanium is further investigated under high cycle fatigue loading. For that purpose, a two-step hierarchical crystal plasticity for fatigue predictions is presented. Fatigue indicator parameter is used as the main driving force in an energy-based crack nucleation model. To calculate the FIPs, high-resolution full-field crystal plasticity simulations are carried out using a spectral solver. A nucleation model is proposed and calibrated by the fatigue experimental data for notched titanium samples with different oxygen contents and under two load ratios. Overall, it is shown that the presented approach is capable of predicting the high cycle fatigue nucleation time. Moreover, qualitative predictions of microstructurally small crack growth rates are provided. The multi-scale methodology presented here can be extended to other material systems to facilitate a better understanding of the fundamental deformation mechanisms, and to effectively implement such knowledge in mesoscale-macroscale investigations.
ContributorsGholami Bazehhour, Benyamin (Author) / Solanki, Kiran N (Thesis advisor) / Liu, Yongming (Committee member) / Oswald, Jay J (Committee member) / Rajagopalan, Jagannathan (Committee member) / Jiao, Yang (Committee member) / Arizona State University (Publisher)
Created2018
Description
Special thermal interface materials are required for connecting devices that operate at high temperatures up to 300°C. Because devices used in power electronics, such as GaN, SiC, and other wide bandgap semiconductors, can reach very high temperatures (beyond 250°C), a high melting point, and high thermal & electrical conductivity are required for the thermal interface material. Traditional solder materials for packaging cannot be used for these applications as they do not meet these requirements. Sintered nano-silver is a good candidate on account of its high thermal and electrical conductivity and very high melting point. The high temperature operating conditions of these devices lead to very high thermomechanical stresses that can adversely affect performance and also lead to failure. A number of these devices are mission critical and, therefore, there is a need for very high reliability. Thus, computational and nondestructive techniques and design methodology are needed to determine, characterize, and design the packages. Actual thermal cycling tests can be very expensive and time consuming. It is difficult to build test vehicles in the lab that are very close to the production level quality and therefore making comparisons or making predictions becomes a very difficult exercise. Virtual testing using a Finite Element Analysis (FEA) technique can serve as a good alternative. In this project, finite element analysis is carried out to help achieve this objective. A baseline linear FEA is performed to determine the nature and magnitude of stresses and strains that occur during the sintering step. A nonlinear coupled thermal and mechanical analysis is conducted for the sintering step to study the behavior more accurately and in greater detail. Damage and fatigue analysis are carried out for multiple thermal cycling conditions. The results are compared with the actual results from a prior study. A process flow chart outlining the FEA modeling process is developed as a template for the future work. A Coffin-Manson type relationship is developed to help determine the accelerated aging conditions and predict life for different service conditions.
ContributorsAmla, Tarun (Author) / Chawla, Nikhilesh (Thesis advisor) / Jiao, Yang (Committee member) / Liu, Yongming (Committee member) / Zhuang, Houlong (Committee member) / Jiang, Hanqing (Committee member) / Arizona State University (Publisher)
Created2020