Benchmarking of spectral methods for fatigue assessment of mooring systems and dynamic cables in offshore renewable energy technologies

Abstract

Fatigue life estimation methods based on time-domain and rainflow counting techniques are widely recognised and accepted for their reliability. However, applying them in scenarios involving random loads with multiple large-scale time series becomes impractical due to high computational costs. This challenge is particularly significant for offshore renewable energy systems. Therefore, it is essential to employ more efficient frequency domain fatigue life calculation models. This study critically evaluates various spectral fatigue assessment methods for estimating damage caused by stress loads in the offshore environment. In this research, 25 spectral methods are analysed and compared using synthetic tension signals. The evaluation criteria include the results’ reliability and ease of implementation, leading to the development of a scoring scheme as a systematic and straightforward ranking method. The results reveal that the Tovo–Benasciutti method excels in accurately estimating rainflow damage in bimodal processes, closely followed by the empirical 0.75, Han–Ma, Low, Modified Tovo–Benasciutti, Dirlik, and Jun–Park models. Other popular methods, such as the Narrow-band and Wirsching–Light methods, yielded poor results, and their use is discouraged. Furthermore, the spectral methods analysed in the benchmarking study have been implemented in Python, and the code has been released as open source.