Abstract

This paper presents the application of survival analysis techniques, widely used in medical research, to the development of nonlinear probabilistic S-N curves for fatigue including the effects of other covariates. The number of cycles to failure is treated as a fictitious “time-to-event” parameter. Parametric survival analyses were performed using fatigue test data for steel bridges. The loglogistic accelerated failure time survival model was determined to be best suited for steel bridges. Results indicate that the current linear S-N curves for bridges do not provide a consistent probability of failure. Survival analysis can be a powerful tool for probabilistic fatigue analyses.

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