Finite element model updating based on a Kriging surrogate model for bridge performance evaluation

Abstract

In order to evaluate the performance of a bridge structure, finite element (FE) model updating methods have been frequently used in these days. In conventional FE model updating approaches, a precise initial FE model is used for obtaining accurate results. However, a precise FE model causes the considerable computational burden such as excessive calculation time. This paper presents a new FE model updating strategy based on a surrogate model, which is able to significantly reduce the calculation time without sacrificing the accuracy. In this study, a Kriging model (or response surface model) is selected as a surrogate model. The sequential sampling strategy is introduced for more efficient construction of an accurate Kriging surrogate model. The performance and efficiency of the proposed FE model updating approach are verified with the field-Test data obtained from an in-service bridge structure in Korea. It is demonstrated that the proposed FE model updating method has better performance in the calculation time than the conventional one.