Identification of the scour depth of continuous girder bridges based on model updating and improved genetic algorithm

Scour is one of the primary reasons for the collapse of bridges, as it severely reduces the stability of their piers. This study developed a model updating method based on an improved genetic algorithm (GA) to identify scour depth, combined with a parallel computing technique to accelerate the model updating procedure. The proposed GA adopted a gradient-like calculation as the mutation operation, while the population in GA was initialized based on the exponential distribution. A finite element model of a continuous girder bridge, whose soil-structure interaction was simulated by winkle beam theory, was established to give a sensitivity analysis of the scour effect. A moving mass-spring model was used to simulate the vehicle-bridge interaction, and dynamic responses under various scour damages were generated to verify the method's performance. The results of the numerical simulation indicated that the transverse vibration modes of a continuous girder bridge were sensitive to the scour effect, and the proposed method can identify the scour depth with an error of less than 0.31 m.

Automated summary

The study developed a model updating method based on an improved genetic algorithm to identify scour depth, combined with a parallel computing technique to accelerate the process. Numerical simulations showed that the proposed method is sensitive to the scour effect on continuous girder bridges and can accurately identify the scour depth.