Identification of Statistical Characteristics of Deformation Modulus Parameters Based on Rock Mass Classification Index
The statistical characteristics of deformation modulus parameters are important design parameters in the risk assessment of reservoir bank slopes in hydropower stations.In early warning of hazards on bank slopes during con-struction period,direct measurements of the deformation modulus on site are time-consuming and sometimes it is impos-sible to be implemented.When the data from direct in-situ measurements are limited or unavailable,various indirect in-formation is usually available in the preliminary stages of engineering to estimate deformation moduli,such as rock mass classification indices.This paper proposes a Bayesian updating framework that can combine various indirect information to estimate the statistical characteristics of deformation modulus.The mean,standard deviation and fluctuation range of de-formation modulus parameters are updated by three rock mass classification indices.Comparing direct measurements,as well as changes in random field statistical characteristics,a Bayesian update scheme using various rock mass classification indices shows a more efficient identification of the parameters.
deformation modulusBayesian updating frameworkuncertaintyrock mass classification indicesran-dom field
万方数据
维普
