Predictive framework for corrosion-fatigue life assessment of large offshore wind turbine monopiles using real environmental data

Corrosion-fatigue is a major challenge for the safe and economical operation of offshore wind turbines supported by large monopiles. This paper presents a new predictive framework that combines real wind and wave data with wind-speed-dependent load modelling, analytical beam theory and finite element analysis, soil-structure interaction for North Sea conditions, and corrosion-fatigue modelling based on pit morphology and mean stress effects. The framework uses cumulative damage assessment to estimate the remaining life and is demonstrated on the IEA 15-megawat turbine with data from Westermost Rough in the UK. Rotor thrust is identified as the dominant load, reaching 2.563 MN at the rated wind speed of 10.59 m/s. Corrosion-induced thickness loss, based on DNVGL-RP-0416 rates, increases stresses over time and shifts the critical region from the submerged zone to the splash zone after about seven years. Tensile stresses rise from 76 to 81 MPa in the submerged zone and from 74 to 87 MPa in the splash zone. The analytical beam theory and finite element models showed close agreement in stress prediction, with an average difference of 3.64%, confirming the reliability and scalability of the adopted methods. A pit corrosion factor (0.332 ≤ f _c ≥ 0.578), derived from X-ray computed tomography measurements and notch theory, is used in a fatigue model validated against welded S355J2+N and S355G10 + M steels, including specimens corroded in seawater for six months and tested to BS EN ISO and ASTM standards. Using 48,379 wind records and North Sea wave conditions, stress cycles reconstructed with Weibull statistics to predict a remaining life of 99.3% after 20 years for typical pits and 91.6 % for aggressive pits. The framework supports predictive maintenance, inspection planning, and life-extension decisions, and can be applied to other offshore structures such as jackets, floating platforms, and substations.