Artificial neural network modelling and economic analysis of soil subgrade stabilized with flyash and geotextile

Introduction The strength characteristics of flyash stabilized clays are measured by means of unconfined compressive strength (CBR) or California Bearing Ratio (CBR) values. Based upon the soil type, the effective flyash content for improving the engineering properties of the soil varies between 15 to 30% 1,2,3,4,5,6,7,8,9,10&11 . Geosynthetics is a class of geomaterials that are used to improve soil conditions for a number of applications. They consist of manufactured polymeric materials used in contact with soil materials or pavements to act as a separator and reinforcing material like steel bars in concrete. Geosynthetics has been increasingly used in geotechnical and environmental engineering for the last 5 decades. Over the years, these had helped designers and contractors to solve several types of engineering problems where the use of conventional construction materials would be restricted or considerably more expensive. There are a significant number of geosynthetic types and geosynthetic applications in geotechnical and environmental engineering 12&13 . In this study, characteristics of soil stabilized with flyash are studied and reinforcing effects of geosynthetics are also studied 14&15 . An Artificial Neural Network model that could predict CBR value based on Atterberg’s limit, OMC, MDD, Flyash content, and number of layers of geotextile has also been developed 16,17,18,19& 20 . To know the economic beneficial of stabilized subgrade, cost analysis have been done 21&22 .