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
Description
The alkali activation of aluminosilicate materials as binder systems derived from industrial byproducts have been extensively studied due to the advantages they offer in terms enhanced material properties, while increasing sustainability by the reuse of industrial waste and byproducts and reducing the adverse impacts of OPC production. Fly ash and ground granulated blast furnace slag are commonly used for their content of soluble silica and aluminate species that can undergo dissolution, polymerization with the alkali, condensation on particle surfaces and solidification. The following topics are the focus of this thesis: (i) the use of microwave assisted thermal processing, in addition to heat-curing as a means of alkali activation and (ii) the relative effects of alkali cations (K or Na) in the activator (powder activators) on the mechanical properties and chemical structure of these systems. Unsuitable curing conditions instigate carbonation, which in turn lowers the pH of the system causing significant reductions in the rate of fly ash activation and mechanical strength development. This study explores the effects of sealing the samples during the curing process, which effectively traps the free water in the system, and allows for increased aluminosilicate activation. The use of microwave-curing in lieu of thermal-curing is also studied in order to reduce energy consumption and for its ability to provide fast volumetric heating. Potassium-based powder activators dry blended into the slag binder system is shown to be effective in obtaining very high compressive strengths under moist curing conditions (greater than 70 MPa), whereas sodium-based powder activation is much weaker (around 25 MPa). Compressive strength decreases when fly ash is introduced into the system. Isothermal calorimetry is used to evaluate the early hydration process, and to understand the reaction kinetics of the alkali powder activated systems. A qualitative evidence of the alkali-hydroxide concentration of the paste pore solution through the use of electrical conductivity measurements is also presented, with the results indicating the ion concentration of alkali is more prevalent in the pore solution of potassium-based systems. The use of advanced spectroscopic and thermal analysis techniques to distinguish the influence of studied parameters is also discussed.
ContributorsChowdhury, Ussala (Author) / Neithalath, Narayanan (Thesis advisor) / Rajan, Subramanium D. (Committee member) / Mobasher, Barzin (Committee member) / Arizona State University (Publisher)
Created2013
Description
A comprehensive study was performed on non-proprietary ultra-high-performance concrete (UHPC) material and several design methods were suggested based on numerous experimental results. Several sets of compression tests, direct tensile tests, and flexural tests were performed on UHPC to provide a better understanding of the mechanisms involved in the mechanical behavior of the fiber reinforced material. In addition to compressive tests, flexural tests, based on ASTM C1609 and EN 14651, were performed. The effect of the strain rate on the UHPC material was also investigated through the high-speed tensile tests at different strain rates. Alongside the usual measurement tools such as linear variable differential transformers (LVDT) and clip gages, digital image correlation (DIC) method was also used to capture the full-range deformations in the samples and localized crack propagations. Analytical approaches were suggested, based on the experimental results of the current research and other research groups, to provide design solutions for different applications and design approaches for UHPC and hybrid reinforced concrete (HRC) sections. The suggested methods can be used both in the ultimate limit state (ULS) and the serviceability limit state (SLS) design methods. Closed form relationships, based on the non-linear design of reinforced concrete, were used in the calculation of the load-deflection response of UHPC. The procedures were used in obtaining material properties from the flexural data using procedures that are based on back-calculation of material properties from the experimental results. Model simulations were compared with other results available in the literature. Performance of flexural reinforced UHPC concrete beam sections tested under different types of loading was addressed using a combination of fibers and rebars. The same analytical approach was suggested for the fiber reinforced concrete (FRC) sections strengthened (rehabilitated) by fiber reinforced polymers (FRP) and textile reinforced concrete (TRC). The objective is to validate the proper design procedures for flexural members as well as connection elements. The proposed solutions can be used to reduce total reinforcement by means of increasing the ductility of the FRC, HRC, and UHPC members in order to meet the required flexural reinforcement, which in some cases leads to total elimination of rebars.
ContributorsKianmofrad, Farrokh (Author) / Mobasher, Barzin (Thesis advisor) / Rajan, Subramaniam Dharma (Committee member) / Hoover, Christian G. (Committee member) / Arizona State University (Publisher)
Created2018
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