Theses and Dissertations
This collection includes both ASU Theses and Dissertations, submitted by graduate students, and the Barrett, Honors College theses submitted by undergraduate students.
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- All Subjects: Extended finite element
- All Subjects: Liquid-Liquid System
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
A comprehensive and systematic investigation on the diffusion and phase behaviors of nanoparticles and macromolecules in two component liquid-liquid systems via Molecule Dynamic (MD) simulations is presented in this dissertation.
The interface of biphasic liquid systems has attracted great attention because it offers a simple, flexible, and highly reproducible template for the assembly of a variety of nanoscale objects. However, certain important fundamental issues at the interface have not been fully explored, especially when the size of the object is comparable with the liquid molecules. In the first MD simulation system, the diffusion and self-assembly of nanoparticles with different size, shape and surface composition were studied in an oil/water system. It has been found that a highly symmetrical nanoparticle with uniform surface (e.g. buckyball) can lead to a better-defined solvation shell which makes the “effective radius” of the nanoparticle larger than its own radius, and thus, lead to slower transport (diffusion) of the nanoparticles across the oil-water interface. Poly(N-isopropylacrylamide) (PNIPAM) is a thermoresponsive polymer with a Lower Critical Solution Temperature (LCST) of 32°C in pure water. It is one of the most widely studied stimulus-responsive polymers which can be fabricated into various forms of smart materials. However, current understanding about the diffusive and phase behaviors of PNIPAM in ionic liquids/water system is very limited. Therefore, two biphasic water-ionic liquids (ILs) systems were created to investigate the interfacial behavior of PNIPAM in such unique liquid-liquid interface. It was found the phase preference of PNIPAM below/above its LCST is dependent on the nature of ionic liquids. This potentially allows us to manipulate the interfacial behavior of macromolecules by tuning the properties of ionic liquids and minimizing the need for expensive polymer functionalization. In addition, to seek a more comprehensive understanding of the effects of ionic liquids on the phase behavior of PNIPAM, PNIPAM was studied in two miscible ionic liquids/water systems. The thermodynamic origin causes the reduction of LCST of PNIPAM in imidazolium based ionic liquids/water system was found. Energy analysis, hydrogen boding calculation and detailed structural quantification were presented in this study to support the conclusions.
The interface of biphasic liquid systems has attracted great attention because it offers a simple, flexible, and highly reproducible template for the assembly of a variety of nanoscale objects. However, certain important fundamental issues at the interface have not been fully explored, especially when the size of the object is comparable with the liquid molecules. In the first MD simulation system, the diffusion and self-assembly of nanoparticles with different size, shape and surface composition were studied in an oil/water system. It has been found that a highly symmetrical nanoparticle with uniform surface (e.g. buckyball) can lead to a better-defined solvation shell which makes the “effective radius” of the nanoparticle larger than its own radius, and thus, lead to slower transport (diffusion) of the nanoparticles across the oil-water interface. Poly(N-isopropylacrylamide) (PNIPAM) is a thermoresponsive polymer with a Lower Critical Solution Temperature (LCST) of 32°C in pure water. It is one of the most widely studied stimulus-responsive polymers which can be fabricated into various forms of smart materials. However, current understanding about the diffusive and phase behaviors of PNIPAM in ionic liquids/water system is very limited. Therefore, two biphasic water-ionic liquids (ILs) systems were created to investigate the interfacial behavior of PNIPAM in such unique liquid-liquid interface. It was found the phase preference of PNIPAM below/above its LCST is dependent on the nature of ionic liquids. This potentially allows us to manipulate the interfacial behavior of macromolecules by tuning the properties of ionic liquids and minimizing the need for expensive polymer functionalization. In addition, to seek a more comprehensive understanding of the effects of ionic liquids on the phase behavior of PNIPAM, PNIPAM was studied in two miscible ionic liquids/water systems. The thermodynamic origin causes the reduction of LCST of PNIPAM in imidazolium based ionic liquids/water system was found. Energy analysis, hydrogen boding calculation and detailed structural quantification were presented in this study to support the conclusions.
ContributorsGao, Wei (Author) / Dai, Lenore (Thesis advisor) / Jiao, Yang (Committee member) / Liu, Yongming (Committee member) / Green, Matthew (Committee member) / Emady, Heather (Committee member) / Arizona State University (Publisher)
Created2017