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: Mobasher, Barzin
The current method of measuring thermal conductivity requires flat plates. For most common civil engineering materials, creating or extracting such samples is difficult. A prototype thermal conductivity experiment had been developed at Arizona State University (ASU) to test cylindrical specimens but proved difficult for repeated testing. In this study, enhancements to both testing methods were made. Additionally, test results of cylindrical testing were correlated with the results from identical materials tested by the Guarded Hot&ndashPlate; method, which uses flat plate specimens. In validating the enhancements made to the Guarded Hot&ndashPlate; and Cylindrical Specimen methods, 23 tests were ran on five different materials. The percent difference shown for the Guarded Hot&ndashPlate; method was less than 1%. This gives strong evidence that the enhanced Guarded Hot-Plate apparatus in itself is now more accurate for measuring thermal conductivity. The correlation between the thermal conductivity values of the Guarded Hot&ndashPlate; to those of the enhanced Cylindrical Specimen method was excellent. The conventional concrete mixture, due to much higher thermal conductivity values compared to the other mixtures, yielded a P&ndashvalue; of 0.600 which provided confidence in the performance of the enhanced Cylindrical Specimen Apparatus. Several recommendations were made for the future implementation of both test methods. The work in this study fulfills the research community and industry desire for a more streamlined, cost effective, and inexpensive means to determine the thermal conductivity of various civil engineering materials.
ML algorithms for classification of cementitious phases are found to require only the intensities of Ca, Si, and Al as inputs to generate accurate predictions for more homogeneous cement pastes. When applied to more complex UHP systems, the overlapping chemical intensities in the three dominant phases – Ultra High Stiffness (UHS), unreacted cementitious replacements, and clinker – led to ML models misidentifying these three phases. Similarly, a reduced amount of data available on the hard and stiff UHS phases prevents accurate ML regression predictions of the microstructural phase stiffness using only chemical information. The use of generic virtual two-phase microstructures coupled with finite element analysis is also adopted to train MLs to predict composite mechanical properties. This approach applied to three different representations of composite materials produces accurate predictions, thus providing an avenue for image-based microstructural characterization of multi-phase composites such UHP binders. This thesis provides insights into the microstructure of the complex, heterogeneous UHP binders and the utilization of big-data methods such as ML to predict their properties. These results are expected to provide means for rational, first-principles design of UHP mixtures.