Data-based models for fatigue reliability assessment and life prediction of orthotropic steel deck details considering pavement temperature and traffic loads

Considering the effects of long-term moving vehicle loads and ambient temperature on the fatigue life of details in orthotropic steel decks in cable-stayed bridges, a novel fatigue damage regression analysis model was developed and then used with reliability profiles to predict fatigue life. The regression model can characterize the normal correlation pattern between the daily averaged pavement temperatures, the annual average hourly aggregated traffic volume (AAHTV) or annual average hourly traffic weight (AAHTW) and a stress-based performance indicator. Prediction models based on the monitoring outcomes from the structural health monitoring systems installed on a Yangtze River cable-stayed bridge were first developed and used to describe and predict the time-series of the long-term moving vehicle loads and asphalt concrete (AC) pavement temperatures. An exponential regression model was then developed to quantify the relationship between daily averaged pavement temperatures, moving vehicle loads and the stress-based indicator, which is derived using S–N principles from strain measurements. Further, a limit equation based on the exponential regression model mentioned above for the fatigue life prediction, which considers both the traffic conditions and pavement temperature, has been developed. Finally, this methodology was employed to predict the fatigue life of details in orthotropic steel decks.