Modal identification and finite element model updating of railway bridges considering boundary conditions using artificial neural networks

Abstract

Two-part study, with the evaluation of the variation in modal identification of two railway bridges located in Northern Norway based on free decay responses after the passage of different types of trains. In addition, performing the neural network based finite element model updating considering both rotational and translational stiffnesses of the boundary conditions to present the aging and constraining effect of the boundary conditions. The modal parameters of the finalized calibrated model were compared with the field-measured modal parameters to quantify the success of the model updating process.