Date on Master's Thesis/Doctoral Dissertation

8-2019

Document Type

Doctoral Dissertation

Degree Name

Ph. D.

Department

Civil and Environmental Engineering

Degree Program

Civil Engineering, PhD

Committee Chair

Kim, Young Hoon

Committee Co-Chair (if applicable)

Sun, Zhihui

Committee Member

McGinley, William Mark

Committee Member

Sumanasekera, Gamini

Author's Keywords

Carbon nanotubes; cementitious materials; mechanical properties; durability; dispersion; probabilistic model

Abstract

Recently, Carbon Nanotubes (CNTs) are drawing considerable attention of researchers for reinforcing cementitious materials due to their excellent mechanical properties and high aspect ratio (length-to-diameter ratio). However, CNTs might not disperse well within the cement matrix, resulting in little improvement or even degradation of concrete properties. The uncertainty in producing the consistent results in different studies might be attributed to multiple interactions between the experimental variables affecting the nanotube dispersion and the final properties of CNT-cement nanocomposites. Therefore, this research mainly focused on proposing equations that can reliably capture these interactions in order to correlate CNT dispersion with the mechanical properties. The main experimental variables studied included CNT concentration, aspect ratio, ultrasonication energy, ultrasonication amplitude, surfactant-to-CNTs ratio, water-to-cement ratio, sand-to-cement ratio, and hydration age of specimen. The study reported in this research was conducted in two parts: experimental program and modeling. In the experimental part of this research, a total of 63 different mix proportions were used to evaluate the flowability, mechanical properties, and durability characteristics of cement pastes and mortars containing CNTs. Using experimental test results reported in this study and the literature, three critical relations were proposed to consider the CNT dispersion, cement matrix composition, and hydration age of cement. The proposed critical relations were then added to available theoretical models in the literature. The flexural strength and elastic modulus of CNT-cement nanocomposites were predicted through a state-of-the-art probabilistic model using a Bayesian methodology. Finally, the developed probabilistic models were used to identify the optimum ranges of the experimental variables to maximize the mechanical properties. This was done through computing the conditional probability of not meeting the specified design requirement. The experimental results indicated that addition of CNTs could significantly improve different properties of cementitious materials, if the optimum range of each variable was used. Also, to achieve the desired mechanical properties, various combinations of the experimental variables might be used. The proposed prediction models were shown to capture the interactions between the experimental variables for predicting the mechanical properties within ±15% and ±18% of the experimental test results for flexural strength and elastic modulus, respectively. Based on the findings of this research, contour plots were developed to provide practical guidelines for future engineers to design CNT-cement nanocomposites.

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