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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.


Cavitation erosion is a significant cause of wear in marine components, such as impellers, propellers or rudders. While the erosion process has been widely studied on metals, the effect of cavitation on polymers is not well-understood. The stress response in metals differs greatly from that of polymers, e.g. rate and temperature effects are far more important, thus damage and wear mechanisms of polymers under cavitating flows are significantly different. In this work, heat-driven failure caused by viscous dissipation and void nucleation resulting from tensile stresses arising from stress wave reflections are investigated as two possible material failure mechanisms. As a …

Contributors
Panwar, Ajay, Oswald, Jay, Dooley, Kevin, et al.
Created Date
2015

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 …

Contributors
Yuan, Rui, Oswald, Jay, Chawla, Nikhilesh, et al.
Created Date
2015