A comprehensive probabilistic prediction and Monte-Carlo simulation of the flexural strength of hybrid graphene oxide/carbon nanotube cementitious nanocomposite

Abstract

Using the Kelly-Tyson theory, a probabilistic model is proposed to predict the flexural strength of hybrid cement composite reinforced by graphene oxide (GO) and carbon nanotube (CNT). The model evaluates the effects of several parameters, including the GO content, the CNT content and aspect ratio, the water-cement ratio, and the age of sample. The predictions are compared with experimental data sets. Good agreements are achieved, so that the model predicts the flexural strength with the error of 8% compared to the experimental data sets. Furthermore, the failure probability is evaluated to identify the optimum range of the variables to achieve the maximum flexural strength. The results show that increasing the CNT content and aspect leads to an increase in the flexural strength. However, with an increase in the water-cement ratio, the GO content, and the age of sample, the flexural strength decreases. It is found that, compared to the reference sample, by adding 0.06 wt% GO, the flexural strength decreases about 3.65% while the addition of 0.06 wt% CNT leads to 9.6% increase in the flexural strength. Moreover, when the CNT content increases from 0 to 0.05 wt%, the corresponding failure probability decreases about 26.6%. The failure probability increases about 30% correspondingly as the GO content varies from 0 to 0.05 wt%, too.