A finite element model updating method for aqueduct structures based on Bayesian theory

The structural condition of aqueducts changes over time due to various influencing factors. Consequently, parameters used in finite element analysis may not reflect the real-time state of the structure. Therefore, it is necessary to update the finite element model parameters by monitoring the dynamic response of the structure to accurately assess its operational state. This paper proposes a finite element model updating method based on Bayesian theory. The method uses deterministic model updating results as the initial parameters for the uncertain model update. The posterior distribution of model parameters is obtained using the Metropolis-Hastings (MH) algorithm. By integrating ABAQUS finite element models with MATLAB updating programs, automatic parameter updating for complex structural finite element models is achieved. An aqueduct model test was conducted to validate this method. Results indicate that using deterministic updating results as initial parameters for Bayesian updating improves computational efficiency by 25%, with an updated error range of 0.19% to 6.42%. This updating method effectively enhances the predictive capability of finite element models.