ABSTRACT
Many innovative long-span cable-supported steel bridges have been built around the world. When these bridges are constructed in wind-prone regions, they suffer considerable buffeting-induced vibration. The frequent occurrence of such a buffeting response at relatively large amplitude may cause fatigue damage to steel members and their connections. Long-span bridges also carry highway and/or railway loadings, and these dynamic loadings affect the fatigue life of the bridge as well. The fatigue damage prognosis (FDP) of bridges under multiple fatigue loadings is therefore necessary for bridge safety, maintenance and management. However, it is a challenging task due to the complexity of structural systems, randomness in fatigue loadings and complicated mechanisms of fatigue damage. In recent years, long-term structural health monitoring (SHM) systems have been developed to measure dynamic loadings and structural responses of long-span bridges, and to assess their functionality and safety while tracking the symptoms of operational incidents and potential damage. SHM technology provides a promising means of tackling challenging FDP issues. However, current research on the SHM and FDP of long-span bridges is not interconnected.
This paper therefore proposes an SHM-based FDP framework for long-span bridges under combined traffic and wind loadings. It involves five major tasks: (1) integrate multiscale finite element modeling and model updating with stress analysis for predicting both global and local structural responses of long-span bridges under combined traffic and wind loadings; (2) determine the optimal placement of multi-type sensors for the best global and local response reconstruction of the bridge through the input of measured responses from the SHM system; (3) assess the current health status of the bridge based on the previous loading histories and using the SHM-based damage detection method; (4) develop loading models based on incessant field measurement data from the SHM system so that the previous loading histories can be analyzed and future loadings can be forecast; and (5) conduct fatigue damage prognosis and predict the remaining fatigue life of the bridge. Although not all the five tasks have been completed yet in a systematic way, some relevant works which have been done by the author and his research team are presented in this paper with reference to the Tsing Ma suspension bridge in Hong Kong.
