Probabilistic characterization of cyclic shear modulus reduction for normally to moderately over-consolidated clays

Abstract

Evaluation of the cyclic shear modulus of soils is a crucial but challenging task for many geotechnical earthquake engineering and soil dynamic issues. Improper determination of this property unnecessarily drives up design and maintenance costs or even leads to the construction of unsafe structures. Due to the complexities involved in the direct measurement, empirical curves for estimating the cyclic shear modulus have been commonly adopted in practice for simplicity and economical considerations. However, a systematic and robust approach for formulating a reliable model and empirical curve for cyclic shear modulus prediction for clayey soils is still lacking. In this study, the Bayesian model class selection approach is utilized to identify the most significant soil parameters affecting the normalized cyclic shear modulus and a reliable predictive model for normally to moderately over-consolidated clays is proposed. Results show that the predictability and reliability of the proposed model out performs the well-known empirical models. Finally, a new design chart is established for practical usage.