Bayesian estimation of small-strain shear modulus from offshore CPT tests in the North Sea

Abstract

The rapid expansion of offshore wind energy requires accurate and cost-effective site characterisation. The dynamic response of offshore wind turbine structures installed on monopile foundations strongly depends on the stiffness of the subsoil where the small-strain shear modulus governs the behaviour during operational loading. Direct measurement of the small-strain shear modulus with the seismic CPT (S-PCPT) is increasingly performed offshore. However, the additional cost associated with this test leads to incomplete data coverage. In the past, correlations between cone tip resistance and small-strain shear modulus have been developed for onshore conditions. The increasing availability of offshore site data has allowed a unique dataset of over 2000 small-strain shear modulus measurements from S-PCPT to be created for North Sea soil units. The comparison of the small-strain shear modulus inferred from the S-PCPT data to the corresponding cone tip resistance allows recalibration of the existing correlations. This paper proposes a Bayesian approach to update the correlation model for sands proposed in the literature based on the developed dataset for offshore conditions in the North Sea.