Stress-cycle fatigue design with Kriging applied to offshore wind turbines. (August 2019)

• Record Type: Journal Article
• Authors: Teixeira, Rui; Nogal, Maria; O'Connor, Alan; Nichols, James; Dumas, Antoine
• Is Part Of: International journal of fatigue. Volume 125(2019)
• Page Start: 454
• Page End: 467
• Publication Date: 2019-08
• Subjects: Fatigue design -- Wind energy -- Surrogate modelling -- Offshore wind turbine -- Kriging; Materials -- Fatigue -- Periodicals; Materials -- Fatigue; Periodicals; 620.1122
• DOI: 10.1016/j.ijfatigue.2019.04.012
• Languages: English
• ISSNs: 0142-1123

Abstract

Abstract: The present paper discusses a new methodology to assess stress-cycle fatigue design using meta-modelling. Research on its application is presented for offshore wind turbine towers. Kriging models are used to surrogate the complex time-domain stress-cycle fatigue assessment that demands multiple evaluations in the design phase. The presented development highlights the importance of having a notion of improvement for the problem of meta-modelling. Literature shows that, when meta-modelling complex engineering problems, the idea of improvement is not always considered. To tackle the problem of assessing fatigue in the design phase, a learning criterion is introduced. It has the particularity of relating to the physical description of the stress-cycle fatigue. Results of the proposed criterion are compared with meta-modelling using a Latin hypercube sampling, and with the standard design approach that bins environmental conditions for fatigue design calculations. A full 1 year validation sample is used to study convergence. As surrogate models for stress-cycle fatigue, Kriging models significantly decrease the efforts of the design procedure. Results showed that computational efforts can be reduced consistently by a factor of 5–8 without compromising accuracy. This may correspond to a reduction of up to approximately 85% of the effort needed to assess stress-cycle fatigue in the design phase. To conclude, it is important to highlight that the methodology presented has a universal character. It can be implemented to reduce computational time or assess the probabilistic response with only one requirement, the definition of a single representative indicator. In the case of fatigue, the short-term stress-cycle damage rate was considered.