Strength and Stiffness Forecasting of mechanically altered Black Cotton Soil and Red Soil using ANN Principles

Abstract

In recent years, in developing nations, importance of village roads with sustainable and low-cost are gaining importance. In this study an attempt has been made to understand the strength and stiffness of mechanically altered soils. The locally available Lateritic soil and black cotton soil can be used in the construction field to improve the properties of soils for building foundations, roadways, and other engineering structures. The main goal of this study was to investigate the effects of mixing different percentages of red soil and black cotton soils on the physical and mechanical properties of the blended soil. Experimental investigation was carried to determine various properties such as shear strength, compressibility, water content, and differential swell index, of blended soils. The results of these tests were then compared to the properties of the individual soils to determine the effects of mechanically alteration on the overall properties of the soil. This experiment is important in the construction field as it allows engineers and contractors to determine the optimal mix of soils for specific construction projects. This experiment can be used to improve the overall soil quality in construction sites, which can lead to cost savings and improved durability of structures built on the site. Finally, the results thus obtained are trained to an Artificial Neural Network (ANN) and the relation between the engineering properties, UCS, and CBR are obtained. The prediction models show higher performance with correlation coefficients of 0.986 and 0.980, respectively. Overall, the blending of red soil and black cotton soil is an important experiment in the construction field that provides valuable information on the properties of blended soils and how they can be used in construction projects to improve the overall quality, durability, and stability of engineering structures.