Matching Items (4)
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- All Subjects: Composite Materials
- Creators: Liu, Yongming
Description
The objective of this research is to develop robust, accurate, and adaptive algorithms in the framework of the extended finite element method (XFEM) for fracture analysis of highly heterogeneous materials with complex internal geometries. A key contribution of this work is the creation of novel methods designed to automate the incorporation of high-resolution data, e.g. from X-ray tomography, that can be used to better interpret the enormous volume of data generated in modern in-situ experimental testing. Thus new algorithms were developed for automating analysis of complex microstructures characterized by segmented tomographic images.
A centrality-based geometry segmentation algorithm was developed to accurately identify discrete inclusions and particles in composite materials where limitations in imaging resolution leads to spurious connections between particles in close contact.To allow for this algorithm to successfully segment geometry independently of particle size and shape, a relative centrality metric was defined to allow for a threshold centrality criterion for removal of voxels that spuriously connect distinct geometries.
To automate incorporation of microstructural information from high-resolution images, two methods were developed that initialize signed distance fields on adaptively-refined finite element meshes. The first method utilizes a level set evolution equation that is directly solved on the finite element mesh through Galerkins method. The evolution equation is formulated to produce a signed distance field that matches geometry defined by a set of voxels segmented from tomographic images. The method achieves optimal convergence for the order of elements used. In a second approach, the fast marching method is employed to initialize a distance field on a uniform grid which is then projected by least squares onto a finite element mesh. This latter approach is shown to be superior in speed and accuracy.
Lastly, extended finite element method simulations are performed for the analysis of particle fracture in metal matrix composites with realistic particle geometries initialized from X-ray tomographic data. In the simulations, particles fracture probabilistically through a Weibull strength distribution. The model is verified through comparisons with the experimentally-measured stress-strain response of the material as well as analysis of the fracture. Further, simulations are then performed to analyze the effect of mesh sensitivity, the effect of fracture of particles on their neighbors, and the role of a particles shape on its fracture probability.
A centrality-based geometry segmentation algorithm was developed to accurately identify discrete inclusions and particles in composite materials where limitations in imaging resolution leads to spurious connections between particles in close contact.To allow for this algorithm to successfully segment geometry independently of particle size and shape, a relative centrality metric was defined to allow for a threshold centrality criterion for removal of voxels that spuriously connect distinct geometries.
To automate incorporation of microstructural information from high-resolution images, two methods were developed that initialize signed distance fields on adaptively-refined finite element meshes. The first method utilizes a level set evolution equation that is directly solved on the finite element mesh through Galerkins method. The evolution equation is formulated to produce a signed distance field that matches geometry defined by a set of voxels segmented from tomographic images. The method achieves optimal convergence for the order of elements used. In a second approach, the fast marching method is employed to initialize a distance field on a uniform grid which is then projected by least squares onto a finite element mesh. This latter approach is shown to be superior in speed and accuracy.
Lastly, extended finite element method simulations are performed for the analysis of particle fracture in metal matrix composites with realistic particle geometries initialized from X-ray tomographic data. In the simulations, particles fracture probabilistically through a Weibull strength distribution. The model is verified through comparisons with the experimentally-measured stress-strain response of the material as well as analysis of the fracture. Further, simulations are then performed to analyze the effect of mesh sensitivity, the effect of fracture of particles on their neighbors, and the role of a particles shape on its fracture probability.
ContributorsYuan, Rui (Author) / Oswald, Jay (Thesis advisor) / Chawla, Nikhilesh (Committee member) / Liu, Yongming (Committee member) / Solanki, Kiran (Committee member) / Chen, Kangping (Committee member) / Arizona State University (Publisher)
Created2015
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
A method for modelling the interactions of dislocations with inclusions has been developed to analyse toughening mechanisms in alloys. This method is different from the superposition method in that infinite domain solutions and image stress fields are not superimposed. The method is based on the extended finite element method (XFEM) in which the dislocations are modelled according to the Volterra dislocation model. Interior discontinuities are introduced across dislocation glide planes using enrichment functions and the resulting boundary value problem is solved through the standard finite element variational approach. The level set method is used to describe the geometry of the dislocation glide planes without any explicit treatment of the interface geometry which provides a convenient and an appealing means for describing the dislocation. A method for estimating the Peach-Koehler force by the domain form of J-integral is considered. The convergence and accuracy of the method are studied for an edge dislocation interacting with a free surface where analytical solutions are available. The force converges to the exact solution at an optimal rate for linear finite elements. The applicability of the method to dislocation interactions with inclusions is illustrated with a system of Aluminium matrix containing Aluminium-copper precipitates. The effect of size, shape and orientation of the inclusions on an edge dislocation for a difference in stiffness and coefficient of thermal expansion of the inclusions and matrix is considered. The force on the dislocation due to a hard inclusion increased by 8% in approaching the sharp corners of a square inclusion than a circular inclusion of equal area. The dislocation experienced 24% more force in moving towards the edges of a square shaped inclusion than towards its centre. When the areas of the inclusions were halved, 30% less force was exerted on the dislocation. This method was used to analyse interfaces with mismatch strains. Introducing eigenstrains equal to 0.004 to the elastic mismatch increased the force by 15 times for a circular inclusion. The energy needed to move an edge dislocation through a domain filled with circular inclusions is 4% more than that needed for a domain with square shaped inclusions.
ContributorsVeeresh, Pawan (Author) / Oswald, Jay (Thesis advisor) / Jiang, Hanqing (Committee member) / Liu, Yongming (Committee member) / Arizona State University (Publisher)
Created2016
Description
An orthotropic elasto-plastic damage material model (OEPDMM) suitable for impact simulations has been developed through a joint research project funded by the Federal Aviation Administration (FAA) and the National Aeronautics and Space Administration (NASA). Development of the model includes derivation of the theoretical details, implementation of the theory into LS-DYNA®, a commercially available nonlinear transient dynamic finite element code, as material model MAT 213, and verification and validation of the model. The material model is comprised of three major components: deformation, damage, and failure. The deformation sub-model is used to capture both linear and nonlinear deformations through a classical plasticity formulation. The damage sub-model is used to account for the reduction of elastic stiffness of the material as the degree of plastic strain is increased. Finally, the failure sub-model is used to predict the onset of loss of load carrying capacity in the material. OEPDMM is driven completely by tabulated experimental data obtained through physically meaningful material characterization tests, through high fidelity virtual tests, or both. The tabulated data includes stress-strain curves at different temperatures and strain rates to drive the deformation sub-model, damage parameter-total strain curves to drive the damage sub-model, and the failure sub-model can be driven by the data required for different failure theories implemented in the computer code. The work presented herein focuses on the experiments used to obtain the data necessary to drive as well as validate the material model, development and implementation of the damage model, verification of the deformation and damage models through single element (SE) and multi-element (ME) finite element simulations, development and implementation of experimental procedure for modeling delamination, and finally validation of the material model through low speed impact simulations and high speed impact simulations.
ContributorsKhaled, Bilal Marwan (Author) / Rajan, Subramaniam D. (Thesis advisor) / Mobasher, Barzin (Committee member) / Neithalath, Narayanan (Committee member) / Liu, Yongming (Committee member) / Goldberg, Robert K. (Committee member) / Arizona State University (Publisher)
Created2019