Bayesian calibration of a non linear damage model of steel structures with random material property: Sensitivity analysis and reliability assessment

Abstract

For steel structures exposed to environmental loading, Polycyclic fatigue is one of the main causes of mechanical failure. Since a linear damage accumulation does not take into account the loading history, the formulation of a nonlinear accumulation seems to be a particularly suitable approach for minimizing control and maintenance. A deterministic model that takes into account the loading history is therefore chosen and a strategy is proposed to introduce material randomness by Bayesian calibration of the model parameters from random SN-curves. This model is then applied to the case of a tee joint loaded in fatigue for three different loads with random material parameters. On this example, the linear accumulation of damage underestimates the probability of failure compared to the non linear accumulation.