The influence of different back analysis conditions on the stochastic back analysis of arch dam material Parameters: A case study

Abstract

It is very important to back analyse arch dam material parameters through monitoring data. The selection of the monitoring points, prior distribution of the material parameters and likelihood function have a significant impact on the stochastic back analysis of arch dam material parameters based on Bayesian inference. In this paper, the sensitivity analysis method is used, and the sensitivity of the comprehensive elastic modulus of dam concrete and bedrock for arch dam deformation is analysed. Through high-sensitivity monitoring points and all monitoring points in the arch dam, the influence of the monitoring point selection on the stochastic back analysis of the arch dam material parameters is studied. Considering the prior distribution of the material parameters and likelihood function forms, the influence of different prior distributions and likelihood function forms on the stochastic back analysis of the arch dam material parameters is studied based on high sensitivity measuring points. The example have shown that the sensitivity analysis can be used for optimizing the selection of monitoring points. Different parameter prior distributions and likelihood function forms have certain influences on the stochastic back analysis of the arch dam material parameters. This paper provides a reference for selecting the stochastic inversion conditions for the arch dam material parameters.