Preliminary model development for predicting strength and stiffness of cement-stabilized soils using artificial neural networks

This paper presents ongoing work on data collection and collation from a large number of laboratory cement-stabilization projects worldwide. The aim is to employ Artificial Neural Networks (ANN) to establish relationships between variables, which define the properties of cement-stabilized soils, and the two parameters determined by the Unconfined Compression Test, the Unconfined Compressive Strength (UCS), and stiffness, using E50 calculated from UCS results. Bayesian predictive neural network models are developed to predict the UCS values of cement-stabilized inorganic clays/silts, as well as sands as a function of selected soil mix variables, such as grain size distribution, water content, cement content and curing time. A model which can predict the stiffness values of cement-stabilized clays/silts is also developed and compared to the UCS model. The UCS model results emulate known trends better and provide more accurate estimates than the results from the E50 stiffness model. © 2013 American Society of Civil Engineers.

Strength and hydration products of reactive MgO-silica pastes

The reaction between MgO and microsilica has been studied by many researchers, who confirmed the formation of magnesium silicate hydrate. The blend was reported to have the potential as a novel material for construction and environment purposes. However, the characteristics of MgO vary significantly, e.g., reactivity and purity, which would have an effect on the hydration process of MgO-silica blend. This paper investigated the strength and hydration products of reactive MgO and silica blend at room temperature up to 90 days. The existence of magnesium silicate hydrate after 7 days' curing was confirmed with the help of infrared spectroscopy, thermogravimetric analysis and X-ray diffraction. The microstructural and elemental analysis of the resulting magnesium silicate hydrate was conducted using scanning electron microscopy and energy dispersive spectroscopy. In addition, the effect of characteristics of MgO on the hydration process was discussed. It was found that the synthesis of magnesium silicate hydrate was highly dependent on the reactivity of the precursors. MgO and silica with higher reactivity resulted in higher formation rate of magnesium silicate hydrate. In addition, the impurity in the MgO affects the pH value of the blends, which in turn determines the solubility of silica and the formation of magnesium silicate hydrate. © 2014 Elsevier Ltd. All rights reserved.