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- All Subjects: Mechanical Engineering
- Creators: Jiang, Hanqing
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
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
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
In engineering, buckling is mechanical instability of walls or columns under compression and usually is a problem that engineers try to prevent. In everyday life buckles (wrinkles) on different substrates are ubiquitous -- from human skin to a rotten apple they are a commonly observed phenomenon. It seems that buckles with macroscopic wavelengths are not technologically useful; over the past decade or so, however, thanks to the widespread availability of soft polymers and silicone materials micro-buckles with wavelengths in submicron to micron scale have received increasing attention because it is useful for generating well-ordered periodic microstructures spontaneously without conventional lithographic techniques. This thesis investigates the buckling behavior of thin stiff films on soft polymeric substrates and explores a variety of applications, ranging from optical gratings, optical masks, energy harvest to energy storage. A laser scanning technique is proposed to detect micro-strain induced by thermomechanical loads and a periodic buckling microstructure is employed as a diffraction grating with broad wavelength tunability, which is spontaneously generated from a metallic thin film on polymer substrates. A mechanical strategy is also presented for quantitatively buckling nanoribbons of piezoelectric material on polymer substrates involving the combined use of lithographically patterning surface adhesion sites and transfer printing technique. The precisely engineered buckling configurations provide a route to energy harvesters with extremely high levels of stretchability. This stiff-thin-film/polymer hybrid structure is further employed into electrochemical field to circumvent the electrochemically-driven stress issue in silicon-anode-based lithium ion batteries. It shows that the initial flat silicon-nanoribbon-anode on a polymer substrate tends to buckle to mitigate the lithiation-induced stress so as to avoid the pulverization of silicon anode. Spontaneously generated submicron buckles of film/polymer are also used as an optical mask to produce submicron periodic patterns with large filling ratio in contrast to generating only ~100 nm edge submicron patterns in conventional near-field soft contact photolithography. This thesis aims to deepen understanding of buckling behavior of thin films on compliant substrates and, in turn, to harness the fundamental properties of such instability for diverse applications.
ContributorsMa, Teng (Author) / Jiang, Hanqing (Thesis advisor) / Yu, Hongyu (Committee member) / Yu, Hongbin (Committee member) / Poon, Poh Chieh Benny (Committee member) / Rajagopalan, Jagannathan (Committee member) / Arizona State University (Publisher)
Created2014
Description
ABSTRACT Electronics especially mobile electronics such as smart phones, tablet PCs, notebooks and digital cameras are undergoing rapid development nowadays and have thoroughly changed our lives. With the requirement of more transistors, higher power, smaller size, lighter weight and even bendability, thermal management of these devices became one of the key challenges. Compared to active heat management system, heat pipe, which is a passive fluidic system, is considered promising to solve this problem. However, traditional heat pipes have size, weight and capillary limitation. Thus new type of heat pipe with smaller size, lighter weight and higher capillary pressure is needed. Nanofiber has been proved with superior properties and has been applied in multiple areas. This study discussed the possibility of applying nanofiber in heat pipe as new wick structure. In this study, a needleless electrospinning device with high productivity rate was built onsite to systematically investigate the effect of processing parameters on fiber properties as well as to generate nanofiber mat to evaluate its capability in electronics cooling. Polyethylene oxide (PEO) and Polyvinyl Alcohol (PVA) nanofibers were generated. Tensiometer was used for wettability measurement. The results show that independent parameters including spinneret type, working distance, solution concentration and polymer type are strongly correlated with fiber morphology compared to other parameters. The results also show that the fabricated nanofiber mat has high capillary pressure.
ContributorsSun, Tianwei (Author) / Jiang, Hanqing (Thesis advisor) / Yu, Hongyu (Committee member) / Chen, Kangping (Committee member) / Arizona State University (Publisher)
Created2014
Description
Commercially pure (CP) and extra low interstitial (ELI) grade Ti-alloys present excellent corrosion resistance, lightweight, and formability making them attractive materials for expanded use in transportation and medical applications. However, the strength and toughness of CP titanium are affected by relatively small variations in their impurity/solute content (IC), e.g., O, Al, and V. This increase in strength is due to the fact that the solute either increases the critical stress required for the prismatic slip systems ({10-10}<1-210>) or activates another slip system ((0001)<11-20>, {10-11}<11-20>). In particular, solute additions such as O can effectively strengthen the alloy but with an attendant loss in ductility by changing the behavior from wavy (cross slip) to planar nature. In order to understand the underlying behavior of strengthening by solutes, it is important to understand the atomic scale mechanism. This dissertation aims to address this knowledge gap through a synergistic combination of density functional theory (DFT) and molecular dynamics. Further, due to the long-range strain fields of the dislocations and the periodicity of the DFT simulation cells, it is difficult to apply ab initio simulations to study the dislocation core structure. To alleviate this issue we developed a multiscale quantum mechanics/molecular mechanics approach (QM/MM) to study the dislocation core. We use the developed QM/MM method to study the pipe diffusion along a prismatic edge dislocation core. Complementary to the atomistic simulations, the Semi-discrete Variational Peierls-Nabarro model (SVPN) was also used to analyze the dislocation core structure and mobility. The chemical interaction between the solute/impurity and the dislocation core is captured by the so-called generalized stacking fault energy (GSFE) surface which was determined from DFT-VASP calculations. By taking the chemical interaction into consideration the SVPN model can predict the dislocation core structure and mobility in the presence and absence of the solute/impurity and thus reveal the effect of impurity/solute on the softening/hardening behavior in alpha-Ti. Finally, to study the interaction of the dislocation core with other planar defects such as grain boundaries (GB), we develop an automated method to theoretically generate GBs in HCP type materials.
ContributorsBhatia, Mehul Anoopkumar (Author) / Solanki, Kiran N (Thesis advisor) / Peralta, Pedro (Committee member) / Jiang, Hanqing (Committee member) / Neithalath, Narayanan (Committee member) / Rajagopalan, Jagannathan (Committee member) / Arizona State University (Publisher)
Created2014
Description
Damage detection in heterogeneous material systems is a complex problem and requires an in-depth understanding of the material characteristics and response under varying load and environmental conditions. A significant amount of research has been conducted in this field to enhance the fidelity of damage assessment methodologies, using a wide range of sensors and detection techniques, for both metallic materials and composites. However, detecting damage at the microscale is not possible with commercially available sensors. A probable way to approach this problem is through accurate and efficient multiscale modeling techniques, which are capable of tracking damage initiation at the microscale and propagation across the length scales. The output from these models will provide an improved understanding of damage initiation; the knowledge can be used in conjunction with information from physical sensors to improve the size of detectable damage. In this research, effort has been dedicated to develop multiscale modeling approaches and associated damage criteria for the estimation of damage evolution across the relevant length scales. Important issues such as length and time scales, anisotropy and variability in material properties at the microscale, and response under mechanical and thermal loading are addressed. Two different material systems have been studied: metallic material and a novel stress-sensitive epoxy polymer.
For metallic material (Al 2024-T351), the methodology initiates at the microscale where extensive material characterization is conducted to capture the microstructural variability. A statistical volume element (SVE) model is constructed to represent the material properties. Geometric and crystallographic features including grain orientation, misorientation, size, shape, principal axis direction and aspect ratio are captured. This SVE model provides a computationally efficient alternative to traditional techniques using representative volume element (RVE) models while maintaining statistical accuracy. A physics based multiscale damage criterion is developed to simulate the fatigue crack initiation. The crack growth rate and probable directions are estimated simultaneously.
Mechanically sensitive materials that exhibit specific chemical reactions upon external loading are currently being investigated for self-sensing applications. The "smart" polymer modeled in this research consists of epoxy resin, hardener, and a stress-sensitive material called mechanophore The mechanophore activation is based on covalent bond-breaking induced by external stimuli; this feature can be used for material-level damage detections. In this work Tris-(Cinnamoyl oxymethyl)-Ethane (TCE) is used as the cyclobutane-based mechanophore (stress-sensitive) material in the polymer matrix. The TCE embedded polymers have shown promising results in early damage detection through mechanically induced fluorescence. A spring-bead based network model, which bridges nanoscale information to higher length scales, has been developed to model this material system. The material is partitioned into discrete mass beads which are linked using linear springs at the microscale. A series of MD simulations were performed to define the spring stiffness in the statistical network model. By integrating multiple spring-bead models a network model has been developed to represent the material properties at the mesoscale. The model captures the statistical distribution of crosslinking degree of the polymer to represent the heterogeneous material properties at the microscale. The developed multiscale methodology is computationally efficient and provides a possible means to bridge multiple length scales (from 10 nm in MD simulation to 10 mm in FE model) without significant loss of accuracy. Parametric studies have been conducted to investigate the influence of the crosslinking degree on the material behavior. The developed methodology has been used to evaluate damage evolution in the self-sensing polymer.
For metallic material (Al 2024-T351), the methodology initiates at the microscale where extensive material characterization is conducted to capture the microstructural variability. A statistical volume element (SVE) model is constructed to represent the material properties. Geometric and crystallographic features including grain orientation, misorientation, size, shape, principal axis direction and aspect ratio are captured. This SVE model provides a computationally efficient alternative to traditional techniques using representative volume element (RVE) models while maintaining statistical accuracy. A physics based multiscale damage criterion is developed to simulate the fatigue crack initiation. The crack growth rate and probable directions are estimated simultaneously.
Mechanically sensitive materials that exhibit specific chemical reactions upon external loading are currently being investigated for self-sensing applications. The "smart" polymer modeled in this research consists of epoxy resin, hardener, and a stress-sensitive material called mechanophore The mechanophore activation is based on covalent bond-breaking induced by external stimuli; this feature can be used for material-level damage detections. In this work Tris-(Cinnamoyl oxymethyl)-Ethane (TCE) is used as the cyclobutane-based mechanophore (stress-sensitive) material in the polymer matrix. The TCE embedded polymers have shown promising results in early damage detection through mechanically induced fluorescence. A spring-bead based network model, which bridges nanoscale information to higher length scales, has been developed to model this material system. The material is partitioned into discrete mass beads which are linked using linear springs at the microscale. A series of MD simulations were performed to define the spring stiffness in the statistical network model. By integrating multiple spring-bead models a network model has been developed to represent the material properties at the mesoscale. The model captures the statistical distribution of crosslinking degree of the polymer to represent the heterogeneous material properties at the microscale. The developed multiscale methodology is computationally efficient and provides a possible means to bridge multiple length scales (from 10 nm in MD simulation to 10 mm in FE model) without significant loss of accuracy. Parametric studies have been conducted to investigate the influence of the crosslinking degree on the material behavior. The developed methodology has been used to evaluate damage evolution in the self-sensing polymer.
ContributorsZhang, Jinjun (Author) / Chattopadhyay, Aditi (Thesis advisor) / Dai, Lenore (Committee member) / Jiang, Hanqing (Committee member) / Papandreou-Suppappola, Antonia (Committee member) / Rajadas, John (Committee member) / Arizona State University (Publisher)
Created2014
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