A new model developed by multigene genetic programming for the temporal evolution of bridge pier scour

Forecasting the time development of scour depth at bridge pier foundations is of great significance to mitigate or avoid the potential failure of bridges. Presently, several models have been developed to predict the scour depth at the base of bridge piers in the case of flood events. This study summarizes existing models for the temporal evolution of bridge pier scour and divides these studies into semiempirical models and empirical models, as well as artificial intelligence models. Several experimental data sets collected from previous studies, 665 points in total, are used to develop a new multigene genetic programming (MGGP) model for temporal scour depth at a circular bridge pier. In addition, independent data, 899 points in total, from previous studies and new physical modeling tests are applied to evaluate the behaviours of existing models, as well as the newly developed MGGP model. It is shown that the MGGP model has good prediction capability when compared with existing empirical and mathematical models.

Automated summary

Forecasting the time development of scour depth at bridge pier foundations is essential for mitigating or avoiding potential bridge failures. This study categorizes existing models for bridge pier scour into semiempirical, empirical, and artificial intelligence models, and develops a new multigene genetic programming (MGGP) model for predicting temporal scour depth. Experimental data from previous studies and new physical modeling tests are used to evaluate the performance of existing models and the newly developed MGGP model. Results demonstrate that the MGGP model has superior prediction capability compared to existing empirical and mathematical models.