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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- All Subjects: Micromechanical
- All Subjects: Three-dimensional printing
- Creators: Mobasher, Barzin
Description
Ultra High Performance (UHP) cementitious binders are a class of cement-based materials with high strength and ductility, designed for use in precast bridge connections, bridge superstructures, high load-bearing structural members like columns, and in structural repair and strengthening. This dissertation aims to elucidate the chemo-mechanical relationships in complex UHP binders to facilitate better microstructure-based design of these materials and develop machine learning (ML) models to predict their scale-relevant properties from microstructural information.To establish the connection between micromechanical properties and constitutive materials, nanoindentation and scanning electron microscopy experiments are performed on several cementitious pastes. Following Bayesian statistical clustering, mixed reaction products with scattered nanomechanical properties are observed, attributable to the low degree of reaction of the constituent particles, enhanced particle packing, and very low water-to-binder ratio of UHP binders. Relating the phase chemistry to the micromechanical properties, the chemical intensity ratios of Ca/Si and Al/Si are found to be important parameters influencing the incorporation of Al into the C-S-H gel.
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.
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.
ContributorsFord, Emily Lucile (Author) / Neithalath, Narayanan (Thesis advisor) / Rajan, Subramaniam D. (Committee member) / Mobasher, Barzin (Committee member) / Chawla, Nikhilesh (Committee member) / Hoover, Christian G. (Committee member) / Maneparambil, Kailas (Committee member) / Arizona State University (Publisher)
Created2020
Description
This dissertation aims at developing novel materials and processing routes using alkali activated aluminosilicate binders for porous (lightweight) geopolymer matrices and 3D-printing concrete applications. The major research objectives are executed in different stages. Stage 1 includes developing synthesis routes, microstructural characterization, and performance characterization of a family of economical, multifunctional porous ceramics developed through geopolymerization of an abundant volcanic tuff (aluminosilicate mineral) as the primary source material. Metakaolin, silica fume, alumina powder, and pure silicon powder are also used as additional ingredients when necessary and activated by potassium-based alkaline agents. In Stage 2, a processing route was developed to synthesize lightweight geopolymer matrices from fly ash through carbonate-based activation. Sodium carbonate (Na2CO3) was used in this study to produce controlled pores through the release of CO2 during the low-temperature decomposition of Na2CO3. Stage 3 focuses on 3D printing of binders using geopolymeric binders along with several OPC-based 3D printable binders. In Stage 4, synthesis and characterization of 3D-printable foamed fly ash-based geopolymer matrices for thermal insulation is the focus. A surfactant-based foaming process, multi-step mixing that ensures foam jamming transition and thus a dry foam, and microstructural packing to ensure adequate skeletal density are implemented to develop foamed suspensions amenable to 3D-printing. The last stage of this research develops 3D-printable alkali-activated ground granulated blast furnace slag mixture. Slag is used as the source of aluminosilicate and shows excellent mechanical properties when activated by highly alkaline activator (NaOH + sodium silicate solution). However, alkali activated slag sets and hardens rapidly which is undesirable for 3D printing. Thus, a novel mixing procedure is developed to significantly extend the setting time of slag activated with an alkaline activator to suit 3D printing applications without the use of any retarding admixtures. This dissertation, thus advances the field of sustainable and 3D-printable matrices and opens up a new avenue for faster and economical construction using specialized materials.
ContributorsAlghamdi, Hussam Suhail G (Author) / Neithalath, Narayanan (Thesis advisor) / Rajan, Subramaniam D. (Committee member) / Mobasher, Barzin (Committee member) / Abbaszadegan, Morteza (Committee member) / Bhate, Dhruv (Committee member) / Arizona State University (Publisher)
Created2019