Prediction of Subgrade Strength from Index Properties of Expansive Soil Stabilized with Bagasse Ash and Calcined Termite Clay Powder Using Artificial Neural Network and Regression

Abstract

When moisture levels fluctuate, expansive soils lose a large amount of volume. During the rainy and dry seasons, this type of soil expands and contracts, respectively. As a result, such problematic soils should be avoided or appropriately managed when encountered as subgrade materials. The strength of the subgrade is measured in terms of its California Bearing Ratio (CBR) value which is tiresome, uneconomical, and time-consuming to determine in the laboratory. In the present study, the effect of bagasse ash (BA) and calcined termite clay powder (CTCP) on the strength, index, and microstructural properties of expansive soil was investigated. Laboratory tests such as Atterberg’s limits, particle size analysis, moisture-density relationship, and CBR tests were performed on the highly expansive soil and blended with 3%, 5%, 7%, 9%, and 11% bagasse ash (BA), and 5%, 10%, 15%, 20%, and 25% CTCP separately and in combination. In addition, the microstructural properties of the raw highly expansive soil and the soil stabilized with the optimum BA-CTCP combination were analyzed using the Scanning Electron Microscopy (SEM) machine. Soaked CBR prediction models were also developed using multiple linear regression (MLR) and artificial neural networks (ANNs) from the BA fraction (BAF), CTCP fraction (CTCPF), liquid limit (LL), plasticity index (PI), optimum moisture content (OMC), and maximum dry density (MDD). The soil understudy was very weak having a CBR value of 2.2% and a group index (GI) of 64.37 (reported as 20) and highly expansive with a PI of 51.61% and LL of 104.32%. The addition of both BA and CTCP separately and in combination had resulted in the reduction of PI and increased the strength of the soil under study. As compared with the individual effect, the combined effect of BA and CTCP was quite significant. The optimum BA and CTCP combination was determined from the free-swell index test result; a 72.5% reduction was observed when it was blended with a combination of 9% BA and 20% CTCP. Thus, 9% BA and 20% CTCP compositions could be the optimum percentage combination to stabilize the highly expansive soil under study. The PI was decreased by 85.75%, and the CBR became 5.5 times greater when it was stabilized with 11% BA + 25% CTCP. The SEM micrographs showed that the morphology and fabric of the control specimen (raw soil) were significantly changed when the soil was stabilized with the optimum BA-CTCP combination (9% BA + 20% CTCP). The MLR prediction model was shown to be less efficient and accurate than the ANN model.