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- All Subjects: Mechanical Engineering
- Creators: Liu, Yongming
- Creators: Mechanical and Aerospace Engineering Program
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Description
In-situ fatigue damage diagnosis and prognosis is a challenging problem for both metallic and composite materials and structures. There are various uncertainties arising from material properties, component geometries, measurement noise, feature extraction techniques, and modeling errors. It is essential to manage and incorporate these uncertainties in order to achieve accurate damage detection and remaining useful life (RUL) prediction.
The aim of this study is to develop an integrated fatigue damage diagnosis and prognosis framework for both metallic and composite materials. First, Lamb waves are used as the in-situ damage detection technique to interrogate the damaged structures. Both experimental and numerical analysis for the Lamb wave propagation within aluminum are conducted. The RUL of lap joints under variable and constant fatigue loading is predicted using the Bayesian updating by incorporating damage detection information and various sources of uncertainties. Following this, the effect of matrix cracking and delamination in composite laminates on the Lamb wave propagation is investigated and a generalized probabilistic delamination size and location detection framework using Bayesian imaging method (BIM) is proposed and validated using the composite fatigue testing data. The RUL of the open-hole specimen is predicted using the overall stiffness degradation under fatigue loading. Next, the adjoint method-based damage detection framework is proposed considering the physics of heat conduction or elastic wave propagation. Different from the classical wave propagation-based method, the received signal under pristine condition is not necessary for estimating the damage information. This method can be successfully used for arbitrary damage location and shape profiling for any materials with higher accuracy and resolution. Finally, some conclusions and future work are generated based on the current investigation.
The aim of this study is to develop an integrated fatigue damage diagnosis and prognosis framework for both metallic and composite materials. First, Lamb waves are used as the in-situ damage detection technique to interrogate the damaged structures. Both experimental and numerical analysis for the Lamb wave propagation within aluminum are conducted. The RUL of lap joints under variable and constant fatigue loading is predicted using the Bayesian updating by incorporating damage detection information and various sources of uncertainties. Following this, the effect of matrix cracking and delamination in composite laminates on the Lamb wave propagation is investigated and a generalized probabilistic delamination size and location detection framework using Bayesian imaging method (BIM) is proposed and validated using the composite fatigue testing data. The RUL of the open-hole specimen is predicted using the overall stiffness degradation under fatigue loading. Next, the adjoint method-based damage detection framework is proposed considering the physics of heat conduction or elastic wave propagation. Different from the classical wave propagation-based method, the received signal under pristine condition is not necessary for estimating the damage information. This method can be successfully used for arbitrary damage location and shape profiling for any materials with higher accuracy and resolution. Finally, some conclusions and future work are generated based on the current investigation.
ContributorsPeng, Tishun (Author) / Liu, Yongming (Thesis advisor) / Chattopadhyay, Aditi (Committee member) / Mignolet, Marc (Committee member) / Papandreou-Suppappola, Antonia (Committee member) / Tang, Pingbo (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
An integrated experimental and numerical investigation for laser-generated optoacoustic wave propagation in structural materials is performed. First, a multi-physics simulation model is proposed to simulate the pulsed laser as a point heat source which hits the surface of an aluminum sheet. The pulsed laser source can generate a localized heating on the surface of the plate and induce an in-plane stress wave. ANSYS – a finite element analysis software – is used to build the 3D model and a coupled thermal-mechanical simulation is performed in which the heat flux is determined by an empirical laser-heat conversion relationship. The displacement and stress field-histories are obtained to get the time of arrival and wave propagation speed of the stress wave. The effect of an added point mass is investigated in detail to observe the local material perturbation and remote wave signals. Following this, the experimental investigation of optoacoustic wave is also performed. A new experimental setup and control is developed and assembled in-house. Various laser firing parameters are investigated experimentally and the optimal combination is used for the experimental testing. Matrix design for different testing conditions is also proposed to include the effect of wave path, sampling procedure, and local point mass on the optoacoustic wave propagation. The developed numerical simulation results are validated with experimental observations. It is shown that the proposed experimental setup can offer a potential fast scanning method for damage detection (local property change) for plate-like structural component.
ContributorsLiu, Chen (Author) / Liu, Yongming (Thesis advisor) / Wang, Liping (Committee member) / Jiao, Yang (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
Description
In this paper, at first, analytical formulation of J-integral for a non-local particle model (VCPM) using atomic scale finite element method is proposed for fracture analysis of 2D solids. A brief review of classical continuum-based J-integral and anon-local lattice particle method is given first. Following this, detailed derivation for the J-integral in discrete particle system is given using the energy equivalence and stress-tensor mapping between the continuum mechanics and lattice-particle system.With the help of atomistic finite element method, the J-integral is expressed as a summation of the corresponding terms in the particle system.
Secondly, a coupling algorithm between a non-local particle method (VCPM) and the classical finite element method (FEM) is discussed to gain the advantages of both methods for fracture analysis in large structures. In this algorithm, the discrete VCPM particle and the continuum FEM domains are solved within a unified theoretical framework. A transitional element technology is developed to smoothly link the 10-particles element with the traditional FEM elements to guaranty the continuity and consistency at the coupling interface. An explicit algorithm for static simulation is developed.
Finally, numerical examples are illustrated for the accuracy, convergence, and path-independence of the derived J-integral formulation. Discussions on the comparison with alternative estimation methods and potential application for fracture simulation are given. The accuracy and efficiency of the coupling algorithm are tested by several benchmark problems such as static crack simulation.
Secondly, a coupling algorithm between a non-local particle method (VCPM) and the classical finite element method (FEM) is discussed to gain the advantages of both methods for fracture analysis in large structures. In this algorithm, the discrete VCPM particle and the continuum FEM domains are solved within a unified theoretical framework. A transitional element technology is developed to smoothly link the 10-particles element with the traditional FEM elements to guaranty the continuity and consistency at the coupling interface. An explicit algorithm for static simulation is developed.
Finally, numerical examples are illustrated for the accuracy, convergence, and path-independence of the derived J-integral formulation. Discussions on the comparison with alternative estimation methods and potential application for fracture simulation are given. The accuracy and efficiency of the coupling algorithm are tested by several benchmark problems such as static crack simulation.
ContributorsZope, Jayesh (Author) / Liu, Yongming (Thesis advisor) / Oswald, Jay (Committee member) / Jiang, Hanqing (Committee member) / Arizona State University (Publisher)
Created2016
Description
Finite element simulations modeling the hydrodynamic impact loads subjected to an elastomeric coating were performed to develop an understanding of the performance and failure mechanisms of protective coatings for cavitating environments.
In this work, two major accomplishments were achieved: 1) scaling laws were developed from hydrodynamic principles and numerical simulations to allow conversion of measured distributions of pressure peaks in a cavitating flow to distributions of microscopic impact loadings modeling individual bubble collapse events, and 2) a finite strain, thermo-mechanical material model for polyurea-based elastomers was developed using a logarithmic rate formulation and implemented into an explicit finite element code.
Combining the distribution of microscopic impact loads and finite element modeling, a semi-quantitative predictive framework is created to calculate the energy dissipation within the coating which can further the understanding of temperature induced coating failures.
The influence of coating thickness and elastomer rheology on the dissipation of impact energies experienced in cavitating flows has also been explored.
The logarithmic formulation has many desired features for the polyurea constitutive model, such as objectivity, integrability, and additive decomposition compatibility.
A review and discussion on the kinematics in large deformation, including a comparison between Lagrangian and Eulerian descriptions, are presented to explain the issues in building rate-dependent constitutive models in finite strains.
When comparing the logarithmic rate with other conventional rates in test examples, the logarithmic rate shows a better conservation of objectivity and integrability.
The modeling framework was validated by comparing predictions against temperatures measured within coatings subjected to a cavitating jet.
Both the experiments and models show that the temperatures generated, even under mild flow conditions, raise the coating temperature by a significant amount, suggesting that the failure of these coatings under more aggressive flows is thermally induced.
The models show that thin polyurea coatings synthesized with shorter molecular weight soft segments dissipate significantly less energy per impact and conduct heat more efficiently.
This work represents an important step toward understanding thermally induced failure in elastomers subjected to cavitating flows, which provides a foundation for design and optimization of coatings with enhanced erosion resistance.
In this work, two major accomplishments were achieved: 1) scaling laws were developed from hydrodynamic principles and numerical simulations to allow conversion of measured distributions of pressure peaks in a cavitating flow to distributions of microscopic impact loadings modeling individual bubble collapse events, and 2) a finite strain, thermo-mechanical material model for polyurea-based elastomers was developed using a logarithmic rate formulation and implemented into an explicit finite element code.
Combining the distribution of microscopic impact loads and finite element modeling, a semi-quantitative predictive framework is created to calculate the energy dissipation within the coating which can further the understanding of temperature induced coating failures.
The influence of coating thickness and elastomer rheology on the dissipation of impact energies experienced in cavitating flows has also been explored.
The logarithmic formulation has many desired features for the polyurea constitutive model, such as objectivity, integrability, and additive decomposition compatibility.
A review and discussion on the kinematics in large deformation, including a comparison between Lagrangian and Eulerian descriptions, are presented to explain the issues in building rate-dependent constitutive models in finite strains.
When comparing the logarithmic rate with other conventional rates in test examples, the logarithmic rate shows a better conservation of objectivity and integrability.
The modeling framework was validated by comparing predictions against temperatures measured within coatings subjected to a cavitating jet.
Both the experiments and models show that the temperatures generated, even under mild flow conditions, raise the coating temperature by a significant amount, suggesting that the failure of these coatings under more aggressive flows is thermally induced.
The models show that thin polyurea coatings synthesized with shorter molecular weight soft segments dissipate significantly less energy per impact and conduct heat more efficiently.
This work represents an important step toward understanding thermally induced failure in elastomers subjected to cavitating flows, which provides a foundation for design and optimization of coatings with enhanced erosion resistance.
ContributorsLiao, Xiao (Author) / Oswald, Jay (Thesis advisor) / Liu, Yongming (Committee member) / Jiang, Hanqing (Committee member) / Rajan, Subramaniam D. (Committee member) / Platte, Rodrigo (Committee member) / Arizona State University (Publisher)
Created2016
Description
A previously developed small time scale fatigue crack growth model is improved, modified and extended with an emphasis on creating the simplest models that maintain the desired level of accuracy for a variety of materials. The model provides a means of estimating load sequence effects by continuously updating the crack opening stress every cycle, in a simplified manner. One of the significant phenomena of the crack opening stress under negative stress ratio is the residual tensile stress induced by the applied compressive stress. A modified coefficient is introduced to determine the extent to which residual stress impact the crack closure and is observed to vary for different materials. Several other literature models for crack closure under constant loading are also reviewed and compared with the proposed model. The modified model is then shown to predict several sets of published test results under constant loading for a variety of materials.
The crack opening stress is formalized as a function of the plastic zone sizes at the crack tip and the current crack length, which provided a means of approximation, accounting for both acceleration and retardation effects in a simplified manner. A sensitivity parameter is introduced to modify the enlarged plastic zone due to overload, to better fit the delay cycles with the test data and is observed to vary for different materials. Furthermore, the interaction effect induced by the combination of overload and underload sequence is modeled by depleting the compressive plastic zone due to an overload with the tensile plastic zone due to an underload. A qualitative analysis showed the simulation capacity of the small time scale model under different load types. A good agreement between prediction and test data for several irregular load types proved the applicability of the small time scale model under variable amplitude loading.
The crack opening stress is formalized as a function of the plastic zone sizes at the crack tip and the current crack length, which provided a means of approximation, accounting for both acceleration and retardation effects in a simplified manner. A sensitivity parameter is introduced to modify the enlarged plastic zone due to overload, to better fit the delay cycles with the test data and is observed to vary for different materials. Furthermore, the interaction effect induced by the combination of overload and underload sequence is modeled by depleting the compressive plastic zone due to an overload with the tensile plastic zone due to an underload. A qualitative analysis showed the simulation capacity of the small time scale model under different load types. A good agreement between prediction and test data for several irregular load types proved the applicability of the small time scale model under variable amplitude loading.
ContributorsVenkatesan, Karthik Rajan (Author) / Liu, Yongming (Thesis advisor) / Oswald, Jay (Committee member) / Jiang, Hanqing (Committee member) / Arizona State University (Publisher)
Created2016
Stochastic multiscale modeling and statistical characterization of complex polymer matrix composites
Description
There are many applications for polymer matrix composite materials in a variety of different industries, but designing and modeling with these materials remains a challenge due to the intricate architecture and damage modes. Multiscale modeling techniques of composite structures subjected to complex loadings are needed in order to address the scale-dependent behavior and failure. The rate dependency and nonlinearity of polymer matrix composite materials further complicates the modeling. Additionally, variability in the material constituents plays an important role in the material behavior and damage. The systematic consideration of uncertainties is as important as having the appropriate structural model, especially during model validation where the total error between physical observation and model prediction must be characterized. It is necessary to quantify the effects of uncertainties at every length scale in order to fully understand their impact on the structural response. Material variability may include variations in fiber volume fraction, fiber dimensions, fiber waviness, pure resin pockets, and void distributions. Therefore, a stochastic modeling framework with scale dependent constitutive laws and an appropriate failure theory is required to simulate the behavior and failure of polymer matrix composite structures subjected to complex loadings. Additionally, the variations in environmental conditions for aerospace applications and the effect of these conditions on the polymer matrix composite material need to be considered. The research presented in this dissertation provides the framework for stochastic multiscale modeling of composites and the characterization data needed to determine the effect of different environmental conditions on the material properties. The developed models extend sectional micromechanics techniques by incorporating 3D progressive damage theories and multiscale failure criteria. The mechanical testing of composites under various environmental conditions demonstrates the degrading effect these conditions have on the elastic and failure properties of the material. The methodologies presented in this research represent substantial progress toward understanding the failure and effect of variability for complex polymer matrix composites.
ContributorsJohnston, Joel Philip (Author) / Chattopadhyay, Aditi (Thesis advisor) / Liu, Yongming (Committee member) / Jiang, Hanqing (Committee member) / Dai, Lenore (Committee member) / Rajadas, John (Committee member) / Arizona State University (Publisher)
Created2016
Description
Cohesive zone model is one of the most widely used model for fracture analysis, but still remains open ended field for research. The earlier works using the cohesive zone model and Extended finite element analysis (XFEM) have been briefly introduced followed by an elaborate elucidation of the same concepts. Cohesive zone model in conjugation with XFEM is used for analysis in static condition in order to check its applicability in failure analysis. A real time setup of pipeline failure due to impingement is analyzed along with a detailed parametric study to understand the influence of the prominent design variable. After verifying its good applicability, a creep model is built for analysis where the cohesive zone model with XFEM is used for a time dependent creep loading. The challenge in this simulation was to achieve coupled behavior of cracks initiation and propagation along with creep loading. By using Design of Experiment, the results from numerical simulation were used to build an equation for life prediction for creep loading condition. The work was further extended to account for fatigue damage accumulation for high cycle fatigue loading in cohesive elements. A model was conceived to account for damage due to fatigue loading along within cohesive zone model for cohesive elements in ABAQUS simulation software. The model was verified by comparing numerical modelling of Double cantilever beam under high cycle fatigue loading and experiment results from literature. The model was also applied to a major industrial problem of blistering in Cured-In-Plane liner pipelines and a demonstration of its failure is shown. In conclusion, various models built on cohesive zone to address static and time dependent loading with real time scenarios and future scope of work in this field is discussed.
ContributorsChandrasekhar, Vishal (Author) / Liu, Yongming (Thesis advisor) / Oswald, Jay (Committee member) / Jiang, Hanqing (Committee member) / Arizona State University (Publisher)
Created2016