EFFICIENT METHOD FOR RELIABILITY ASSESSMENT UNDER HIGH-CYCLE FATIGUE

Fatigue causes about 90% of service failures in machines. Fatigue analysis involves significant randomness in the loads, material properties and geometry. Designers often use Monte Carlo simulation to estimate fatigue reliability under dynamic, random loads such as those due to ocean waves. Monte Carlo simulation is computationally expensive because it requires calculation of the stresses for thousands of simulated time histories of the loads. This paper presents and demonstrates a method to estimate efficiently the fatigue life of a structure subjected to a dynamic load, which is represented by a stationary, Gaussian random process, for many different spectra of the excitation. The method requires only one Monte Carlo simulation for one power spectral density function of the excitation.

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