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- All Subjects: Mechanical Engineering
- Creators: Liu, Yongming
- Creators: Jiang, Hanqing
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. 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. 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, which is the focus of this research. Shock loading experiments were conducted via flyer-plate impact tests for pressures of 2-6 GPa and strain rates of 105/s on copper polycrystals of varying thermomechanical processing conditions. Serial cross sectioning of recovered target disks was performed along with electron microscopy, electron backscattering diffraction (EBSD), focused ion beam (FIB) milling, and 3-D X-ray tomogrpahy (XRT) to gain 2-D and 3-D information on the spall plane and surrounding microstructure. Statistics on grain boundaries (GB) containing damage were obtained from 2-D data and GBs of misorientations 25° and 50° were found to have the highest probability to contain damage in as-received (AR), heat treated (HT), and fully recrystallized (FR) microstructures, while {111} Σ3 GBs were globally strong. The AR microstructure’s probability peak was the most pronounced indicating GB strength is the dominant factor for damage nucleation. 3-D XRT data was used to digitally render the spall planes of the AR, HT, and FR microstructures. From shape fitting the voids to ellipsoids, it was found that the AR microstructure contained greater than 55% intergranular damage, whereas the HT and FR microstructures contained predominantly transgranular and coalesced damage modes, respectively. 3-D reconstructions of large volume damage sites in shocked Cu multicrystals showed preference for damage nucleation at GBs between adjacent grains of a high Taylor factor mismatches as well as an angle between the shock direction and the GB physical normal of ~30°-45°. 3-D FIB sectioning of individual voids led to the discovery of uniform plastic zones ~25-50% the size of the void diameter and plastic deformation directions were characterized via local average misorientation maps. Incipient transgranular voids revealed from the sectioning process were present in grains of high Taylor factors along the shock direction, which is expected as materials with a low Taylor factor along the shock direction are susceptible to growth due their accomodation of plastic deformation. Fabrication of square waves using photolithography and chemical etching was developed to study the nature of plasticity at GBs away from the spall plane. Grains oriented close to <0 1 1> had half the residual amplitudes than grains oriented close to <0 0 1>.
ContributorsBrown, Andrew (Author) / Peralta, Pedro (Committee member) / Mignolet, Marc (Committee member) / Sieradzki, Karl (Committee member) / Solanki, Kiran (Committee member) / Jiang, Hanqing (Committee member) / Arizona State University (Publisher)
Created2015
Description
Origami and Kirigami are two traditional art forms in the world. Origami, from
‘ori’ meaning folding, and ‘kami’ meaning paper is the art of paper folding. Kirigami, from ‘kiri’ meaning cutting, is the art of the combination of paper cutting and paper folding. In this dissertation, Origami and kirigami concepts were successively utilized in making stretchable lithium ion batteries and three-dimensional (3D) silicon structure which both provide excellent mechanical characteristics.
‘ori’ meaning folding, and ‘kami’ meaning paper is the art of paper folding. Kirigami, from ‘kiri’ meaning cutting, is the art of the combination of paper cutting and paper folding. In this dissertation, Origami and kirigami concepts were successively utilized in making stretchable lithium ion batteries and three-dimensional (3D) silicon structure which both provide excellent mechanical characteristics.
ContributorsSong, Zeming (Author) / Jiang, Hanqing (Thesis advisor) / Dai, Lenore (Committee member) / Yu, Hongbin (Committee member) / He, Ximin (Committee member) / Arizona State University (Publisher)
Created2016
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
The present investigation is part of a long-term effort focused on the development of a methodology for the computationally efficient prediction of the dynamic response of structures with multiple joints. The first part of this thesis reports on the dynamic response of nominally identical beams with a single lap joint (“Brake-Reuss” beam). The observed impact responses at different levels clearly demonstrate the occurrence of both micro- and macro-slip, which are reflected by increased damping and a lowering of natural frequencies. Significant beam-to-beam variability of impact responses is also observed.
Based on these experimental results, a deterministic 4-parameter Iwan model of the joint was developed. These parameters were randomized following a previous investigation. The randomness in the impact response predicted from this uncertain model was assessed in a Monte Carlo format through a series of time integrations of the response and found to be consistent with the experimental results.
The availability of an uncertain computational model for the Brake-Reuss beam provides a starting point to analyze and model the response of multi-joint structures in the presence of uncertainty/variability. To this end, a 4-beam frame was designed that is composed of three identical Brake-Reuss beams and a fourth, stretched one. The response of that structure to impact was computed and several cases were identified.
The presence of uncertainty implies that an exact prediction of the response of a particular frame cannot be achieved. Rather, the response can only be predicted to lie within a band reflecting the level of uncertainty. In this perspective, the computational model adopted for the frame is only required to provide a good estimate of this uncertainty band. Equivalently, a relaxation of the model complexity, i.e., the introduction of epistemic uncertainty, can be performed as long as it does not affect significantly the uncertainty band of the predictions. Such an approach, which holds significant promise for the efficient computational of the response of structures with many uncertain joints, is assessed here by replacing some joints by linear spring elements. It is found that this simplification of the model is often acceptable at lower excitation/response levels.
Based on these experimental results, a deterministic 4-parameter Iwan model of the joint was developed. These parameters were randomized following a previous investigation. The randomness in the impact response predicted from this uncertain model was assessed in a Monte Carlo format through a series of time integrations of the response and found to be consistent with the experimental results.
The availability of an uncertain computational model for the Brake-Reuss beam provides a starting point to analyze and model the response of multi-joint structures in the presence of uncertainty/variability. To this end, a 4-beam frame was designed that is composed of three identical Brake-Reuss beams and a fourth, stretched one. The response of that structure to impact was computed and several cases were identified.
The presence of uncertainty implies that an exact prediction of the response of a particular frame cannot be achieved. Rather, the response can only be predicted to lie within a band reflecting the level of uncertainty. In this perspective, the computational model adopted for the frame is only required to provide a good estimate of this uncertainty band. Equivalently, a relaxation of the model complexity, i.e., the introduction of epistemic uncertainty, can be performed as long as it does not affect significantly the uncertainty band of the predictions. Such an approach, which holds significant promise for the efficient computational of the response of structures with many uncertain joints, is assessed here by replacing some joints by linear spring elements. It is found that this simplification of the model is often acceptable at lower excitation/response levels.
ContributorsRobertson, Brett Anthony (Author) / Mignolet, Marc P (Thesis advisor) / Brake, Matt (Committee member) / Liu, Yongming (Committee member) / Arizona State University (Publisher)
Created2016
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
Origami and kirigami, the technique of generating three-dimensional (3D) structures from two-dimensional (2D) flat sheets, are now more and more involved in scientific and engineering fields. Therefore, the development of tools for their theoretical analysis becomes more and more important. Since much effort was paid on calculations based on pure mathematical consideration and only limited effort has been paid to include mechanical properties, the goal of my research is developing a method to analyze the mechanical behavior of origami and kirigami based structures. Mechanical characteristics, including nonlocal effect and fracture of the structures, as well as elasticity and plasticity of materials are studied. For calculation of relative simple structures and building of structures’ constitutive relations, analytical approaches were used. For more complex structures, finite element analysis (FEA), which is commonly applied as a numerical method for the analysis of solid structures, was utilized. The general study approach is not necessarily related to characteristic size of model. I believe the scale-independent method described here will pave a new way to understand the mechanical response of a variety of origami and kirigami based structures under given mechanical loading.
ContributorsLv, Cheng (Author) / Jiang, Hanqing (Thesis advisor) / Yu, Hongbin (Committee member) / Wang, Liping (Committee member) / Mignolet, Marc (Committee member) / Hildreth, Owen (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