Fatigue reliability analysis and traffic load control of steel bridges based on artificial neural network

Steel bridges have the advantages of light weight, high strength, prefabricated construction, and short construction time, and therefore have been widely used in many countries. In conventional bridge design, the load bearing capacity of the structure is considered as the most important safety factor. However, as the service life increases, the actual load-carrying capacity of bridges gradually decreases due to the combined action of the environmental corrosion and repeated vehicle loads, resulting in shortened bridge service life. In this paper, the fatigue reliability index of a steel girder bridge over its whole life is investigated based on artificial neural networks. The effects of truck traffic load and environmental corrosivity on the fatigue life of the steel girder bridge are analyzed and measures to control the traffic load are discussed. The research results can serve as a reference for traffic load management of highway steel bridges.