Empirical and soft computing approaches for estimation of residual friction angle of clays using toughness limit

Abstract

The residual friction angle is an important parameter in soil mechanics, since it is a widely used parameter in long-term stability analysis and a fair descriptor of post-failure strength. In this regard, a database was constituted including Atterberg limits, clay fraction, effective normal stress and residual friction angle. Relationships among the above-mentioned parameters were investigated, and an empirical equation for estimation of tangent of residual friction angle based on effective normal stress and coefficients depending on Atterberg limits was proposed. Later, relationships between residual friction angle and toughness limit; residual friction angle and a combined index parameter based on clay fraction and toughness limit were obtained. Finally, back-propagation neural networks and sensitivity analyses were employed to find out the best combination of inputs, for prediction of residual friction angle. These methods are capable of estimating residual friction angle by use of toughness limit, with a high accuracy.