Abstract
Fatigue life prediction for a bridge should be based on the current condition of the bridge, and various sources of uncertainty, such as material properties, anticipated vehicle loads and environmental conditions, make the prediction very challenging. This paper presents a new approach for probabilistic fatigue life prediction for bridges using finite element (FE) model updating based on structural health monitoring (SHM) data. Recently, various types of SHM systems have been used to monitor and evaluate the long-term structural performance of bridges. For example, SHM data can be used to estimate the degradation of an in-service bridge, which makes it possible to update the initial FE model. The proposed method consists of three steps: (1) identifying the modal properties of a bridge, such as mode shapes and natural frequencies, based on the ambient vibration under passing vehicles; (2) updating the structural parameters of an initial FE model using the identified modal properties; and (3) predicting the probabilistic fatigue life using the updated FE model. The proposed method is demonstrated by application to a numerical model of a bridge, and the impact of FE model updating on the bridge fatigue life is discussed.
Highlights
Fatigue is one of the major causes of structural failure
The proposed method consists of three steps: (1) identifying the modal properties of a bridge, such as the mode shapes and natural frequencies, based on the ambient vibration measurement; (2) updating the structural parameters of an initial finite element (FE) model using the identified modal properties; and (3) predicting the fatigue life probabilistically using the updated FE
After building an initial FE model of a bridge, the optimal values of the structural parameters, which minimize the difference of the natural frequencies between the measurement and the FE model, are identified using the downhill simplex method to obtain the updated FE model
Summary
Fatigue is one of the major causes of structural failure. Many civil structures are exposed to repeated loading over their life cycles, and fatigue may lead to the failure of various types of structures, including bridges. A bridge is designed to survive for a certain period of time after it is constructed, but its status changes over its service life. It is essential to accurately predict the fatigue life in order to make decisions about effective bridge maintenance and retrofitting. This is a very challenging task, because fatigue life prediction for a bridge should be based on its current structural condition, which includes various sources of uncertainty, including material properties, anticipated vehicle loads and environmental conditions
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