ASU Electronic Theses and Dissertations
This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.
In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.
Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.
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- Creators: Chawla, Nikhilesh
Description
Increased priority on the minimization of environmental impacts of conventional construction materials in recent years has motivated increased use of waste materials or bi-products such as fly ash, blast furnace slag with a view to reduce or eliminate the manufacturing/consumption of ordinary portland cement (OPC) which accounts for approximately 5-7% of global carbon dioxide emission. The current study explores, for the first time, the possibility of carbonating waste metallic iron powder to develop carbon-negative sustainable binder systems for concrete. The fundamental premise of this work is that metallic iron will react with aqueous CO2 under controlled conditions to form complex iron carbonates which have binding capabilities. The compressive and flexural strengths of the chosen iron-based binder systems increase with carbonation duration and the specimens carbonated for 4 days exhibit mechanical properties that are comparable to those of companion ordinary portland cement systems. The optimal mixture proportion and carbonation regime for this non-conventional sustainable binder is established based on the study of carbonation efficiency of a series of mixtures using thermogravimetric analysis. The pore- and micro-structural features of this novel binding material are also evaluated. The fracture response of this novel binder is evaluated using strain energy release rate and measurement of fracture process zone using digital image correlation (DIC). The iron-based binder system exhibits significantly higher strain energy release rates when compared to those of the OPC systems in both the unreinforced and glass fiber reinforced states. The iron-based binder also exhibits higher amount of area of fracture process zone due to its ability to undergo inelastic deformation facilitated by unreacted metallic iron particle inclusions in the microstructure that helps crack bridging /deflection. The intrinsic nano-mechanical properties of carbonate reaction product are explored using statistical nanoindentation technique coupled with a stochastic deconvolution algorithm. Effect of exposure to high temperature (up to 800°C) is also studied. Iron-based binder shows significantly higher residual flexural strength after exposure to high temperatures. Results of this comprehensive study establish the viability of this binder type for concrete as an environment-friendly and economical alternative to OPC.
ContributorsDas, Sumanta (Author) / Neithalath, Narayanan (Thesis advisor) / Rajan, S.D. (Committee member) / Mobasher, Barzin (Committee member) / Marzke, Robert (Committee member) / Chawla, Nikhilesh (Committee member) / Stone, David (Committee member) / Arizona State University (Publisher)
Created2015
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