Probabilistic fatigue life prediction for bridges using finite element model updating based on structural health monitoring

Abstract

Fatigue is one of the main causes of bridge failures. A bridge is designed to survive for a target period when it is constructed, but its strength degrades over its service life. Thus, it is essential to predict the fatigue life in order to make decisions about effective bridge maintenance and retrofitting. However, this is a very challenging task because fatigue life prediction for a bridge should be based on its current condition and there are various sources of uncertainty such as material properties, anticipated vehicle loads, and environmental conditions. This paper presents a new approach for probabilistic fatigue life prediction for bridges using finite element (FE) model updating based on structural health monitoring data. Recently, various types of structural health monitoring (SHM) systems are being operated to monitor and evaluate long-term structural performance. As one example, SHM data can be applied to estimate the degradation of an in-service bridge, which makes it possible to update the initial FE model. With this technique, the proposed method is three-fold: (1) identifying the modal parameters of a bridge such as mode shapes and natural frequencies based on the ambient vibration under general passing vehicles; (2) updating the structural parameters of an initial FE model using the identified modal parameters; and (3) predicting the probabilistic fatigue life by employing the updated FE model. To demonstrate the proposed method, it is applied to a numerical bridge example, and the impact of the FE model updating to bridge fatigue life is discussed.