Bayesian framework for the deformability modulus updating in an underground structure

Abstract

The collection of geomechanical information is a complex and dynamic process. As new information is available, the geotechnical model can be updated. However, this is not a straightforward process since the information sources may have different characteristics and reliability levels. This is a process based on judgment and experience. It lacks a systematic and mathematically valid process to deal with this problem and use new information to update the model parameters in order to reduce uncertainties. In this paper, it is intended to provide a contribution on this subject. A generic Bayesian framework for the updating of geomechanical parameters is presented. Emphasis is given to the theoretical aspects of uncertainty and to the Bayesian formulation. This framework is applied to the case of the deformability modulus updating in an underground structure. The prior distribution of the parameter was obtained through de application of analytical solutions based on the empirical classification systems. This distribution was then updated using the framework together with the results of a high quality in situ test. The Bayesian framework showed to be a mathematically valid way to deal with the problem of the geomechanical parameters updating and mostly in the uncertainty reduction related to the parameter real value.