Abstract
This paper presents a method for calculating the fatigue damage from a stochastic bimodal process, in which the high frequency (HF) and low frequency (LF) components are narrowband Gaussian processes. Rainflow cycle counting identifies the following: small but numerous cycles, and large but fewer ones. In existing methods, the small-cycle amplitudes are assumed to be identical to that of the HF cycles, whereas the large-cycle amplitudes are approximated as the sum of the HF and LF amplitudes. The novelty of the present approach lies in the recognition and incorporation of two effects, which concern the reduction of the small-cycle amplitudes caused by the LF process, and the offset between the HF and LF peaks. Parametric studies are conducted, investigating a wide range of parameters. Using time domain simulation as a benchmark, the present method is found to provide a vast improvement over existing methods, with a root-mean-square error of ∼1%.
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