Citation

Saberi MR, Rahai AR, Sanayei M, Vogel RM. Int. J. Civ. Eng. 2016; 15(1): 51-61.

Copyright

(Copyright © 2016, Holtzbrinck Springer Nature Publishing Group)

DOI

10.1007/s40999-016-0036-z

PMID

unavailable

Abstract

Steel bridges play an important role in the transportation system of many countries. To ensure that bridges are structurally sound, engineers monitor their performance, which is known as structural health monitoring. Historical evidence indicates that bridge damage is pervasive and that the service life of bridges is decreasing. To manage safety and costs, engineers must be able to accurately predict the service life of bridges. A statistical method to predict service life for steel bridges is presented, which can assist bridge engineers, bridge owners, and state officials in the objective assessment of deteriorated bridges for retrofit or replacement. Timely repair and retrofit of bridges increase their safety levels and decrease costs. A nonparametric statistical approach based on the bootstrap method for stress analysis for fatigue life prediction of steel bridge components is proposed. The bootstrap provides a simple approach for the reproduction of the extremely complex probability distribution of measured strain data. It is completely automated numerical method which requires no theoretical calculations and it is not based on the asymptotic results. The service life index is introduced which quantifies the fatigue life of steel bridges under daily traffic loads. A regression model is developed for the prediction of remaining service life of steel bridges using a service life function. The predicted remaining service life derived from the function can contribute to effective management of steel bridges.

Language: en