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 - 10 of 22
Filtering by
- Creators: Jiang, Hanqing
Description
Recently, the use of zinc oxide (ZnO) nanowires as an interphase in composite materials has been demonstrated to increase the interfacial shear strength between carbon fiber and an epoxy matrix. In this research work, the strong adhesion between ZnO and carbon fiber is investigated to elucidate the interactions at the interface that result in high interfacial strength. First, molecular dynamics (MD) simulations are performed to calculate the adhesive energy between bare carbon and ZnO. Since the carbon fiber surface has oxygen functional groups, these were modeled and MD simulations showed the preference of ketones to strongly interact with ZnO, however, this was not observed in the case of hydroxyls and carboxylic acid. It was also found that the ketone molecules ability to change orientation facilitated the interactions with the ZnO surface. Experimentally, the atomic force microscope (AFM) was used to measure the adhesive energy between ZnO and carbon through a liftoff test by employing highly oriented pyrolytic graphite (HOPG) substrate and a ZnO covered AFM tip. Oxygen functionalization of the HOPG surface shows the increase of adhesive energy. Additionally, the surface of ZnO was modified to hold a negative charge, which demonstrated an increase in the adhesive energy. This increase in adhesion resulted from increased induction forces given the relatively high polarizability of HOPG and the preservation of the charge on ZnO surface. It was found that the additional negative charge can be preserved on the ZnO surface because there is an energy barrier since carbon and ZnO form a Schottky contact. Other materials with the same ionic properties of ZnO but with higher polarizability also demonstrated good adhesion to carbon. This result substantiates that their induced interaction can be facilitated not only by the polarizability of carbon but by any of the materials at the interface. The versatility to modify the magnitude of the induced interaction between carbon and an ionic material provides a new route to create interfaces with controlled interfacial strength.
ContributorsGalan Vera, Magdian Ulises (Author) / Sodano, Henry A (Thesis advisor) / Jiang, Hanqing (Committee member) / Solanki, Kiran (Committee member) / Oswald, Jay (Committee member) / Speyer, Gil (Committee member) / Arizona State University (Publisher)
Created2013
Description
Shock loading is a complex phenomenon that can lead to failure mechanisms such as strain localization, void nucleation and growth, and eventually spall fracture. Studying incipient stages of spall damage is of paramount importance to accurately determine initiation sites in the material microstructure where damage will nucleate and grow and to formulate continuum models that account for the variability of the damage process due to microstructural heterogeneity. The length scale of damage with respect to that of the surrounding microstructure has proven to be a key aspect in determining sites of failure initiation. Correlations have been found between the damage sites and the surrounding microstructure to determine the preferred sites of spall damage, since it tends to localize at and around the regions of intrinsic defects such as grain boundaries and triple points. However, considerable amount of work still has to be done in this regard to determine the physics driving the damage at these intrinsic weak sites in the microstructure. The main focus of this research work is to understand the physical mechanisms behind the damage localization at these preferred sites. A crystal plasticity constitutive model is implemented with different damage criteria to study the effects of stress concentration and strain localization at the grain boundaries. A cohesive zone modeling technique is used to include the intrinsic strength of the grain boundaries in the simulations. The constitutive model is verified using single elements tests, calibrated using single crystal impact experiments and validated using bicrystal and multicrystal impact experiments. The results indicate that strain localization is the predominant driving force for damage initiation and evolution. The microstructural effects on theses damage sites are studied to attribute the extent of damage to microstructural features such as grain orientation, misorientation, Taylor factor and the grain boundary planes. The finite element simulations show good correlation with the experimental results and can be used as the preliminary step in developing accurate probabilistic models for damage nucleation.
ContributorsKrishnan, Kapil (Author) / Peralta, Pedro (Thesis advisor) / Mignolet, Marc (Committee member) / Sieradzki, Karl (Committee member) / Jiang, Hanqing (Committee member) / Oswald, Jay (Committee member) / Arizona State University (Publisher)
Created2013
Description
This research focuses on the benefits of using nanocomposites in aerospace structural components to prevent or delay the onset of unique composite failure modes, such as delamination. Analytical, numerical, and experimental analyses were conducted to provide a comprehensive understanding of how carbon nanotubes (CNTs) can provide additional structural integrity when they are used in specific hot spots within a structure. A multiscale approach was implemented to determine the mechanical and thermal properties of the nanocomposites, which were used in detailed finite element models (FEMs) to analyze interlaminar failures in T and Hat section stringers. The delamination that first occurs between the tow filler and the bondline between the stringer and skin was of particular interest. Both locations are considered to be hot spots in such structural components, and failures tend to initiate from these areas. In this research, nanocomposite use was investigated as an alternative to traditional methods of suppressing delamination. The stringer was analyzed under different loading conditions and assuming different structural defects. Initial damage, defined as the first drop in the load displacement curve was considered to be a useful variable to compare the different behaviors in this study and was detected via the virtual crack closure technique (VCCT) implemented in the FE analysis.
Experiments were conducted to test T section skin/stringer specimens under pull-off loading, replicating those used in composite panels as stiffeners. Two types of designs were considered: one using pure epoxy to fill the tow region and another that used nanocomposite with 5 wt. % CNTs. The response variable in the tests was the initial damage. Detailed analyses were conducted using FEMs to correlate with the experimental data. The correlation between both the experiment and model was satisfactory. Finally, the effects of thermal cure and temperature variation on nanocomposite structure behavior were studied, and both variables were determined to influence the nanocomposite structure performance.
Experiments were conducted to test T section skin/stringer specimens under pull-off loading, replicating those used in composite panels as stiffeners. Two types of designs were considered: one using pure epoxy to fill the tow region and another that used nanocomposite with 5 wt. % CNTs. The response variable in the tests was the initial damage. Detailed analyses were conducted using FEMs to correlate with the experimental data. The correlation between both the experiment and model was satisfactory. Finally, the effects of thermal cure and temperature variation on nanocomposite structure behavior were studied, and both variables were determined to influence the nanocomposite structure performance.
ContributorsHasan, Zeaid (Author) / Chattopadhyay, Aditi (Thesis advisor) / Dai, Lenore (Committee member) / Jiang, Hanqing (Committee member) / Rajadas, John (Committee member) / Liu, Yongming (Committee member) / Arizona State University (Publisher)
Created2014
Description
Hydrogen embrittlement (HE) is a phenomenon that affects both the physical and chemical properties of several intrinsically ductile metals. Consequently, understanding the mechanisms behind HE has been of particular interest in both experimental and modeling research. Discrepancies between experimental observations and modeling results have led to various proposals for HE mechanisms. Therefore, to gain insights into HE mechanisms in iron, this dissertation aims to investigate several key issues involving HE such as: a) the incipient crack tip events; b) the cohesive strength of grain boundaries (GBs); c) the dislocation-GB interactions and d) the dislocation mobility.
The crack tip, which presents a preferential trap site for hydrogen segregation, was examined using atomistic methods and the continuum based Rice-Thompson criterion as sufficient concentration of hydrogen can alter the crack tip deformation mechanism. Results suggest that there is a plausible co-existence of the adsorption induced dislocation emission and hydrogen enhanced decohesion mechanisms. In the case of GB-hydrogen interaction, we observed that the segregation of hydrogen along the interface leads to a reduction in cohesive strength resulting in intergranular failure. A methodology was further developed to quantify the role of the GB structure on this behavior.
GBs play a fundamental role in determining the strengthening mechanisms acting as an impediment to the dislocation motion; however, the presence of an unsurmountable barrier for a dislocation can generate slip localization that could further lead to intergranular crack initiation. It was found that the presence of hydrogen increases the strain energy stored within the GB which could lead to a transition in failure mode. Finally, in the case of body centered cubic metals, understanding the complex screw dislocation motion is critical to the development of an accurate continuum description of the plastic behavior. Further, the presence of hydrogen has been shown to drastically alter the plastic deformation, but the precise role of hydrogen is still unclear. Thus, the role of hydrogen on the dislocation mobility was examined using density functional theory and atomistic simulations. Overall, this dissertation provides a novel atomic-scale understanding of the HE mechanism and development of multiscale tools for future endeavors.
The crack tip, which presents a preferential trap site for hydrogen segregation, was examined using atomistic methods and the continuum based Rice-Thompson criterion as sufficient concentration of hydrogen can alter the crack tip deformation mechanism. Results suggest that there is a plausible co-existence of the adsorption induced dislocation emission and hydrogen enhanced decohesion mechanisms. In the case of GB-hydrogen interaction, we observed that the segregation of hydrogen along the interface leads to a reduction in cohesive strength resulting in intergranular failure. A methodology was further developed to quantify the role of the GB structure on this behavior.
GBs play a fundamental role in determining the strengthening mechanisms acting as an impediment to the dislocation motion; however, the presence of an unsurmountable barrier for a dislocation can generate slip localization that could further lead to intergranular crack initiation. It was found that the presence of hydrogen increases the strain energy stored within the GB which could lead to a transition in failure mode. Finally, in the case of body centered cubic metals, understanding the complex screw dislocation motion is critical to the development of an accurate continuum description of the plastic behavior. Further, the presence of hydrogen has been shown to drastically alter the plastic deformation, but the precise role of hydrogen is still unclear. Thus, the role of hydrogen on the dislocation mobility was examined using density functional theory and atomistic simulations. Overall, this dissertation provides a novel atomic-scale understanding of the HE mechanism and development of multiscale tools for future endeavors.
ContributorsAdlakha, Ilaksh (Author) / Solanki, Kiran (Thesis advisor) / Mignolet, Marc (Committee member) / Chawla, Nikhilesh (Committee member) / Jiang, Hanqing (Committee member) / Liu, Yongming (Committee member) / Arizona State University (Publisher)
Created2015
Description
Multiaxial mechanical fatigue of heterogeneous materials has been a significant cause of concern in the aerospace, civil and automobile industries for decades, limiting the service life of structural components while increasing time and costs associated with inspection and maintenance. Fiber reinforced composites and light-weight aluminum alloys are widely used in aerospace structures that require high specific strength and fatigue resistance. However, studying the fundamental crack growth behavior at the micro- and macroscale as a function of loading history is essential to accurately predict the residual fatigue life of components and achieve damage tolerant designs. The issue of mechanical fatigue can be tackled by developing reliable in-situ damage quantification methodologies and by comprehensively understanding fatigue damage mechanisms under a variety of complex loading conditions. Although a multitude of uniaxial fatigue loading studies have been conducted on light-weight metallic materials and composites, many service failures occur from components being subjected to variable amplitude, mixed-mode multiaxial fatigue loadings. In this research, a systematic approach is undertaken to address the issue of fatigue damage evolution in aerospace materials by:
(i) Comprehensive investigation of micro- and macroscale crack growth behavior in aerospace grade Al 7075 T651 alloy under complex biaxial fatigue loading conditions. The effects of variable amplitude biaxial loading on crack growth characteristics such as crack acceleration and retardation were studied in detail by exclusively analyzing the influence of individual mode-I, mixed-mode and mode-II overload and underload fatigue cycles in an otherwise constant amplitude mode-I baseline load spectrum. The micromechanisms governing crack growth behavior under the complex biaxial loading conditions were identified and correlated with the crack growth behavior and fracture surface morphology through quantitative fractography.
(ii) Development of novel multifunctional nanocomposite materials with improved fatigue resistance and in-situ fatigue damage detection and quantification capabilities. A state-of-the-art processing method was developed for producing sizable carbon nanotube (CNT) membranes for multifunctional composites. The CNT membranes were embedded in glass fiber laminates and in-situ strain sensing and damage quantification was achieved by exploiting the piezoresistive property of the CNT membrane. In addition, improved resistance to fatigue crack growth was observed due to the embedded CNT membrane.
(i) Comprehensive investigation of micro- and macroscale crack growth behavior in aerospace grade Al 7075 T651 alloy under complex biaxial fatigue loading conditions. The effects of variable amplitude biaxial loading on crack growth characteristics such as crack acceleration and retardation were studied in detail by exclusively analyzing the influence of individual mode-I, mixed-mode and mode-II overload and underload fatigue cycles in an otherwise constant amplitude mode-I baseline load spectrum. The micromechanisms governing crack growth behavior under the complex biaxial loading conditions were identified and correlated with the crack growth behavior and fracture surface morphology through quantitative fractography.
(ii) Development of novel multifunctional nanocomposite materials with improved fatigue resistance and in-situ fatigue damage detection and quantification capabilities. A state-of-the-art processing method was developed for producing sizable carbon nanotube (CNT) membranes for multifunctional composites. The CNT membranes were embedded in glass fiber laminates and in-situ strain sensing and damage quantification was achieved by exploiting the piezoresistive property of the CNT membrane. In addition, improved resistance to fatigue crack growth was observed due to the embedded CNT membrane.
ContributorsDatta, Siddhant (Author) / Chattopadhyay, Aditi (Thesis advisor) / Liu, Yongming (Committee member) / Jiang, Hanqing (Committee member) / Marvi, Hamidreza (Committee member) / Tang, Pingbo (Committee member) / Yekani Fard, Masoud (Committee member) / Iyyer, Nagaraja (Committee member) / Arizona State University (Publisher)
Created2018
Description
This investigation focuses on the development of uncertainty modeling methods applicable to both the structural and thermal models of heated structures as part of an effort to enable the design under uncertainty of hypersonic vehicles. The maximum entropy-based nonparametric stochastic modeling approach is used within the context of coupled structural-thermal Reduced Order Models (ROMs). Not only does this strategy allow for a computationally efficient generation of samples of the structural and thermal responses but the maximum entropy approach allows to introduce both aleatoric and some epistemic uncertainty into the system.
While the nonparametric approach has a long history of applications to structural models, the present investigation was the first one to consider it for the heat conduction problem. In this process, it was recognized that the nonparametric approach had to be modified to maintain the localization of the temperature near the heat source, which was successfully achieved.
The introduction of uncertainty in coupled structural-thermal ROMs of heated structures was addressed next. It was first recognized that the structural stiffness coefficients (linear, quadratic, and cubic) and the parameters quantifying the effects of the temperature distribution on the structural response can be regrouped into a matrix that is symmetric and positive definite. The nonparametric approach was then applied to this matrix allowing the assessment of the effects of uncertainty on the resulting temperature distributions and structural response.
The third part of this document focuses on introducing uncertainty using the Maximum Entropy Method at the level of finite element by randomizing elemental matrices, for instance, elemental stiffness, mass and conductance matrices. This approach brings some epistemic uncertainty not present in the parametric approach (e.g., by randomizing the elasticity tensor) while retaining more local character than the operation in ROM level.
The last part of this document focuses on the development of “reduced ROMs” (RROMs) which are reduced order models with small bases constructed in a data-driven process from a “full” ROM with a much larger basis. The development of the RROM methodology is motivated by the desire to optimally reduce the computational cost especially in multi-physics situations where a lack of prior understanding/knowledge of the solution typically leads to the selection of ROM bases that are excessively broad to ensure the necessary accuracy in representing the response. It is additionally emphasized that the ROM reduction process can be carried out adaptively, i.e., differently over different ranges of loading conditions.
While the nonparametric approach has a long history of applications to structural models, the present investigation was the first one to consider it for the heat conduction problem. In this process, it was recognized that the nonparametric approach had to be modified to maintain the localization of the temperature near the heat source, which was successfully achieved.
The introduction of uncertainty in coupled structural-thermal ROMs of heated structures was addressed next. It was first recognized that the structural stiffness coefficients (linear, quadratic, and cubic) and the parameters quantifying the effects of the temperature distribution on the structural response can be regrouped into a matrix that is symmetric and positive definite. The nonparametric approach was then applied to this matrix allowing the assessment of the effects of uncertainty on the resulting temperature distributions and structural response.
The third part of this document focuses on introducing uncertainty using the Maximum Entropy Method at the level of finite element by randomizing elemental matrices, for instance, elemental stiffness, mass and conductance matrices. This approach brings some epistemic uncertainty not present in the parametric approach (e.g., by randomizing the elasticity tensor) while retaining more local character than the operation in ROM level.
The last part of this document focuses on the development of “reduced ROMs” (RROMs) which are reduced order models with small bases constructed in a data-driven process from a “full” ROM with a much larger basis. The development of the RROM methodology is motivated by the desire to optimally reduce the computational cost especially in multi-physics situations where a lack of prior understanding/knowledge of the solution typically leads to the selection of ROM bases that are excessively broad to ensure the necessary accuracy in representing the response. It is additionally emphasized that the ROM reduction process can be carried out adaptively, i.e., differently over different ranges of loading conditions.
ContributorsSong, Pengchao (Author) / Mignolet, Marc P (Thesis advisor) / Smarslok, Benjamin (Committee member) / Chattopadhyay, Aditi (Committee member) / Liu, Yongming (Committee member) / Jiang, Hanqing (Committee member) / Berman, Spring (Committee member) / Arizona State University (Publisher)
Created2019
Description
Polymer matrix composites (PMCs) are attractive structural materials due to their high stiffness to low weight ratio. However, unidirectional PMCs have low shear strength and failure can occur along kink bands that develop on compression due to plastic microbuckling that carry strains large enough to induce nonlinear matrix deformation. Reviewing the literature, a large fraction of the existing work is for uniaxial compression, and the effects of stress gradients, such as those present during bending, have not been as well explored, and these effects are bound to make difference in terms of kink band nucleation and growth. Furthermore, reports on experimental measurements of strain fields leading to and developing inside these bands in the presence of stress gradients are also scarce and need to be addressed to gain a full understanding of their behavior when UDCs are used under bending and other spatially complex stress states.
In a light to bridge the aforementioned gaps, the primary focus of this work is to understand mechanisms for kink band evolution under an influence of stress-gradients induced during bending. Digital image correlation (DIC) is used to measure strains inside and around the kink bands during 3-point bending of samples with 0°/90° stacking made of Ultra-High Molecular Weight Polyethylene Fibers. Measurements indicate bands nucleate at the compression side and propagate into the sample carrying a mixture of large shear and normal strains (~33%), while also decreasing its bending stiffness. Failure was produced by a combination of plastic microbuckling and axial splitting. The microstructure of the kink bands was studied and used in a microstructurally explicit finite element model (FEM) to analyze stresses and strains at ply level in the samples during kink band evolution, using cohesive zone elements to represent the interfaces between plies. Cohesive element properties were deduced by a combination of delamination, fracture and three-point bending tests used to calibrate the FEMs. Modeling results show that the band morphology is sensitive to the shear and opening properties of the interfaces between the plies.
In a light to bridge the aforementioned gaps, the primary focus of this work is to understand mechanisms for kink band evolution under an influence of stress-gradients induced during bending. Digital image correlation (DIC) is used to measure strains inside and around the kink bands during 3-point bending of samples with 0°/90° stacking made of Ultra-High Molecular Weight Polyethylene Fibers. Measurements indicate bands nucleate at the compression side and propagate into the sample carrying a mixture of large shear and normal strains (~33%), while also decreasing its bending stiffness. Failure was produced by a combination of plastic microbuckling and axial splitting. The microstructure of the kink bands was studied and used in a microstructurally explicit finite element model (FEM) to analyze stresses and strains at ply level in the samples during kink band evolution, using cohesive zone elements to represent the interfaces between plies. Cohesive element properties were deduced by a combination of delamination, fracture and three-point bending tests used to calibrate the FEMs. Modeling results show that the band morphology is sensitive to the shear and opening properties of the interfaces between the plies.
ContributorsPatel, Jay K (Author) / Peralta, Pedro D (Thesis advisor) / Oswald, Jay (Committee member) / Jiang, Hanqing (Committee member) / Solanki, Kiran (Committee member) / Ayyar, Adarsh (Committee member) / Arizona State University (Publisher)
Created2016
Description
All structures suffer wear and tear because of impact, excessive load, fatigue, corrosion, etc. in addition to inherent defects during their manufacturing processes and their exposure to various environmental effects. These structural degradations are often imperceptible, but they can severely affect the structural performance of a component, thereby severely decreasing its service life. Although previous studies of Structural Health Monitoring (SHM) have revealed extensive prior knowledge on the parts of SHM processes, such as the operational evaluation, data processing, and feature extraction, few studies have been conducted from a systematical perspective, the statistical model development.
The first part of this dissertation, the characteristics of inverse scattering problems, such as ill-posedness and nonlinearity, reviews ultrasonic guided wave-based structural health monitoring problems. The distinctive features and the selection of the domain analysis are investigated by analytically searching the conditions of the uniqueness solutions for ill-posedness and are validated experimentally.
Based on the distinctive features, a novel wave packet tracing (WPT) method for damage localization and size quantification is presented. This method involves creating time-space representations of the guided Lamb waves (GLWs), collected at a series of locations, with a spatially dense distribution along paths at pre-selected angles with respect to the direction, normal to the direction of wave propagation. The fringe patterns due to wave dispersion, which depends on the phase velocity, are selected as the primary features that carry information, regarding the wave propagation and scattering.
The following part of this dissertation presents a novel damage-localization framework, using a fully automated process. In order to construct the statistical model for autonomous damage localization deep-learning techniques, such as restricted Boltzmann machine and deep belief network, are trained and utilized to interpret nonlinear far-field wave patterns.
Next, a novel bridge scour estimation approach that comprises advantages of both empirical and data-driven models is developed. Two field datasets from the literature are used, and a Support Vector Machine (SVM), a machine-learning algorithm, is used to fuse the field data samples and classify the data with physical phenomena. The Fast Non-dominated Sorting Genetic Algorithm (NSGA-II) is evaluated on the model performance objective functions to search for Pareto optimal fronts.
The first part of this dissertation, the characteristics of inverse scattering problems, such as ill-posedness and nonlinearity, reviews ultrasonic guided wave-based structural health monitoring problems. The distinctive features and the selection of the domain analysis are investigated by analytically searching the conditions of the uniqueness solutions for ill-posedness and are validated experimentally.
Based on the distinctive features, a novel wave packet tracing (WPT) method for damage localization and size quantification is presented. This method involves creating time-space representations of the guided Lamb waves (GLWs), collected at a series of locations, with a spatially dense distribution along paths at pre-selected angles with respect to the direction, normal to the direction of wave propagation. The fringe patterns due to wave dispersion, which depends on the phase velocity, are selected as the primary features that carry information, regarding the wave propagation and scattering.
The following part of this dissertation presents a novel damage-localization framework, using a fully automated process. In order to construct the statistical model for autonomous damage localization deep-learning techniques, such as restricted Boltzmann machine and deep belief network, are trained and utilized to interpret nonlinear far-field wave patterns.
Next, a novel bridge scour estimation approach that comprises advantages of both empirical and data-driven models is developed. Two field datasets from the literature are used, and a Support Vector Machine (SVM), a machine-learning algorithm, is used to fuse the field data samples and classify the data with physical phenomena. The Fast Non-dominated Sorting Genetic Algorithm (NSGA-II) is evaluated on the model performance objective functions to search for Pareto optimal fronts.
ContributorsKim, Inho (Author) / Chattopadhyay, Aditi (Thesis advisor) / Jiang, Hanqing (Committee member) / Liu, Yongming (Committee member) / Mignolet, Marc (Committee member) / Rajadas, John (Committee member) / Arizona State University (Publisher)
Created2016
Description
A new critical plane-energy model is proposed in this thesis for multiaxial fatigue life prediction of homogeneous and heterogeneous materials. Brief review of existing methods, especially on the critical plane-based and energy-based methods, are given first. Special focus is on one critical plane approach which has been shown to work for both brittle and ductile metals. The key idea is to automatically change the critical plane orientation with respect to different materials and stress states. One potential drawback of the developed model is that it needs an empirical calibration parameter for non-proportional multiaxial loadings since only the strain terms are used and the out-of-phase hardening cannot be considered. The energy-based model using the critical plane concept is proposed with help of the Mroz-Garud hardening rule to explicitly include the effect of non-proportional hardening under fatigue cyclic loadings. Thus, the empirical calibration for non-proportional loading is not needed since the out-of-phase hardening is naturally included in the stress calculation. The model predictions are compared with experimental data from open literature and it is shown the proposed model can work for both proportional and non-proportional loadings without the empirical calibration. Next, the model is extended for the fatigue analysis of heterogeneous materials integrating with finite element method. Fatigue crack initiation of representative volume of heterogeneous materials is analyzed using the developed critical plane-energy model and special focus is on the microstructure effect on the multiaxial fatigue life predictions. Several conclusions and future work is drawn based on the proposed study.
ContributorsWei, Haoyang (Author) / Liu, Yongming (Thesis advisor) / Jiang, Hanqing (Committee member) / Oswald, Jay (Committee member) / Arizona State University (Publisher)
Created2016
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