Shear strength characteristics of binary mixture sand-carpet fibre using experimental study and machine learning

ABSTRACT

Mixing carpet fibre in sand offers great potential for enhancing soil properties. In this study, direct shear tests were conducted on two different sands mixed with varying carpet fibre percentages to investigate the effects on soil strength, stiffness, and deformation. Artificial intelligence techniques were used to analyse the data and develop predictive models, including an empirical equation that predicts the shear strength. The results showed that the addition of carpet fibre improved soil properties, with increased strength, stiffness, and reduced deformation. The AI models, including the empirical equation, accurately predicted the mixture's shear strength. Furthermore, this study investigated the importance of each input parameter in predicting the mixture's shear strength. The input parameters are normal stress, void ratio, mean particle size, and the ratio of carpet fibre content to specific gravity. According to the results, normal stress is the most important parameter, and mean particle size is the least important.

KEYWORDS:

• Direct shear
• shear strength
• sand
• carpet fibre
• waste material
• machine learning

Disclosure statement

No potential conflict of interest was reported by the author(s).