Stochastic back analysis of material parameters of tailings dams using Bayesian updating approach

To obtain accurate values of the material parameters of tailings dams based on the limited data, a stochastic back analysis approach considering the uncertainties of the material parameters of tailings dams is proposed under the framework of Bayesian updating and finite element analysis. To improve the computational efficiency of back analysis, a polynomial chaos expansion is adopted to replace the implicit function between the displacements of tailing dams at the representative monitoring points and uncertain input parameters. A real tailings dam is taken as an example to demonstrate the effectiveness of the proposed approach for stochastic back analysis of parameters of multi-layered tailings materials based on the monitoring data of displacements. The results indicate that the proposed approach can effectively reduce the estimation in the uncertainties of the material parameters of tailings dams, accurately infer the probability distributions of the material parameters, and identify the influence degree of different material parameters (e.g., elastic modulus, Poisson’s ratio) on the deformation of the tailings dams.