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A fatigue reliability model which integrates the probability distribution of hot spot stress range with a continuous probabilistic formulation of Miner’s damage cumulative rule is developed for fatigue life and reliability evaluation of steel bridges with long-term monitoring data. By considering both the nominal stress obtained by measurements and the corresponding stress concentration factor (SCF) as random variables, a probabilistic model of the hot spot stress is formulated with the use of the S-N curve and the Miner’s rule, which is then used to evaluate the fatigue life and failure probability with the aid of structural reliability theory. The proposed method is illustrated using the long-term strain monitoring data from the instrumented Tsing Ma Bridge. A standard daily stress spectrum accounting for highway traffic, railway traffic, and typhoon effects is derived by use of the monitoring data. Then global and local finite element models (FEMs) of the bridge are developed for numerically calculating the SCFs at fatigue-susceptible locations, while the stochastic characteristics of SCF for a typical welded T-joint are obtained by full-scale model experiments of a railway beam section of the bridge. A multimodal probability density function (PDF) of the stress range is derived from the monitoring data using the finite mixed Weibull distributions in conjunction with a hybrid parameter estimation algorithm. The failure probability and reliability index versus fatigue life are achieved from the obtained joint PDF of the hot spot stress in terms of the nominal stress and SCF random variables.
Ni et al. (Fri,) studied this question.