Stochastic Inversion Method for Concrete Dams on the Basis of Bayesian Back Analysis Theory

Inverse analysis is necessary for concrete dams in normal operation to overcome the discrepancy between the true mechanical parameters and test results. In view of the uncertain characteristics of concrete dams, a stochastic inverse model is proposed in this study to solve the undetermined mechanical parameters with sequential and spatial randomness using measured displacement data and Bayesian back analysis theory. An inversion method for the mechanical parameters of concrete dams is proposed. Fast Fourier transform algorithm is introduced to generate random fields for SFEM analysis. The case study shows that the proposed inversion method can reflect the random characteristics of concrete dams, the mechanical parameters obtained are reasonable, and the inverse model is feasible.

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