Compressive Strength of Sandy Soils Stabilized with Alkali-Activated Volcanic Ash and Slag

Abstract

In recent years, compared to the traditional Portland cement, environmentally friendly geo-polymers have gained more attention as construction materials. In this paper, volcanic ash (VA) and ground granulated blast furnace slag (GGBFS) in different percentages (0%, 3%, 7%, and 10%) are considered as a replacement for the conventionally used Portland cement to stabilize sandy soils. NaOH and Na2SiO3 in different concentrations (4M, 8M, and 12M) and alkali to binder ratios (1, 1.5, 2, and 3) are used as alkali activator solutions to build new geopolymers. Samples are cured in both ambient and oven temperatures and in 1-, 7-and 28-days curing condition.Unconfined compressive strength (UCS) of samples is then evaluated. Two predictive approaches, artificial neural network (ANN) modeling and evolutionary polynomial regression technique (EPR) are applied to model UCS of geo-polymerized sand samples. Regarding the high value of the coefficient of determination of the proposed ANN, 97%, and acceptable prediction errors, RMSE of 0.0439 and MAE of 0.0336, an 8-5-10-1 ANN is introduced as a more accurate tool for the prediction of UCS. Next, three-dimensional parametrical studies are conducted to investigate effects of simultaneous changes in alkali solution, binder and curing condition parameters on UCS values of geo-polymerized samples. Sensitivity analysis based on the Cosine amplitude method has also introduced Si/Al ratio as the most and VA content as the least affecting parameters on the compressive strength of samples. Results attained are further analyzed using pH and electrical conductivity tests and interpreted based on the microstructural investigations throughout scanning electron microscopy (SEM) images, and X-ray diffraction analysis.

Liquefaction Potential of Saturated Sand Reinforced by Cement-Grouted Micropiles: An Evolutionary Approach Based on Shaking Table Tests

“…It is widely applied to a variety of geotechnical engineering problems to find the relationship between a complex function and its affecting parameters [ 47 , 83 , 84 , 85 , 86 , 87 , 88 ]. In this paper, to predict the excess pore water pressure ratio and the required cycles to achieve the peak EPWP ratio values, an evolutionary polynomial regression (EPR) model is developed, and the effectiveness of each parameter on the output models are obtained using sensitivity analyses.…”

Compressive Strength Prediction of Alkali‐Activated Slag Concretes by Using Artificial Neural Network (ANN) and Alternating Conditional Expectation (ACE)

“…Error increases with the increase of MAE and RMSE values. Calculations of MAE and RMSE are given in formulae (8) and ( 9) according to the literature [2][3][4][5][6]. Furthermore, agreement between predicted and measured values together with coefficient of determination was also applied to better assess the applicability of the proposed networks.…”

“…Finally, relatively lower MAE of 1.78, mean squared error (MSE) of 5.98, RMSE of 2.45, and average absolute error (AAE) of 0.04 were obtained, respectively. Shariatmadari et al [5] used alkali-activated volcanic ash-slag-PC to stabilize sandy soil, and developed ANN and evolutionary polynomial regression (EPR) models based on their own experimental results. Replacements of volcanic ash and slag in PC, concentration of alkali activator, alkali to binder ratio, Na/Al, Si/Al, curing time, and curing temperature were employed as input parameters.…”

Effect of Seawater on the Mechanical Strength of Geopolymer/Cement Stabilized Sandy Soils

“…According to previous research, an eco-friendly Portland cement substitute is required due to the insufficient mechanical qualities of Portland cement in stabilizing saline soils under marine conditions [8,9]. Geopolymers are a type of alkali activated cements used as novel construction materials in various applications [10][11][12][13]. A previous study explored the possibility of using seawater to produce alkali activated cements [14].…”