Condition assessment of a concrete filled steel tube arch bridge using in-situ vibration measurements and an Improved Artificial Fish Swarm Algorithm

Abstract

This study aims to assess the condition of a Concrete-Filled Steel Tube (CFST) arch bridge using in-situ vibration measurements, Finite Element Model Updating (FEMU) and an Improved Artificial Fish Swarm Algorithm (IAFSA). Dynamic coefficients, derailment coefficients and wheel unloading rates are extracted from the responses of running safety assessment. An updated finite element model using a kriging model and IAFSA is employed to evaluate the strength and rigidity of the structures. The results indicate that the natural frequencies and damping ratios of the CFST arch bridge meet the requirements of design code. The maximum bridge dynamic coefficient is found to be 1.085, indicating that the bridge dynamic performance is good. The wheel unloading rates of vehicle and locomotive exceed the specification limit, indicating that the track condition has to be improved before the bridge is operated. By updating an initial FE model, the errors between the predicted and the measured parameters are reduced to less than 5%.