A novel multi-dimensional reliability approach for floating wind turbines under power production conditions

Abstract

Floating offshore wind turbines (FOWT) generate green renewable energy and are a vital part of the modern offshore wind energy industry. Robust predicting extreme offshore loads during FOWT operations is an important safety concern. Excessive structural bending moments may occur during certain sea conditions, posing an operational risk of structural damage. This paper uses the FAST code to analyze offshore wind turbine structural loads due to environmental loads acting on a specific FOWT under actual local environmental conditions. The work proposes a unique Gaidai-Fu-Xing structural reliability approach that is probably best suited for multi-dimensional structural responses that have been simulated or measured over a long period to produce relatively large ergodic time series. In the context of numerical simulation, unlike existing reliability approaches, the novel methodology does not need to re-start simulation again each time the system fails. As shown in this work, an accurate forecast of the probability of system failure can be made using measured structural response. Furthermore, traditional reliability techniques cannot effectively deal with large dimensionality systems and cross-correction across multiple dimensions. The paper aims to establish a state-of-the-art method for extracting essential information concerning extreme responses of the FOWT through simulated time-history data. Three key components of structural loads are analyzed, including the blade-root out-of-plane bending moment, tower fore-aft bending moment, and mooring line tension. The approach suggested in this study allows predicting failure probability efficiently for a non-linear multi-dimensional dynamic system as a whole.

Novel methods for coupled prediction of extreme wind speeds and wave heights

“…( 5) follows from Eq. ( 1) by neglecting Prob R 1 ≤ η 1 ≈ 1 , as design failure probability must of a small order of magnitude, and N>>k. Equation ( 5) is similar to mean up-crossing rate equation for probability of exceedance [39][40][41][42][43][44][45][46][47][48][49][50][51] . There is convergence with respect to the conditioning parameter k Note that Eq.…”

Offshore tethered platform springing response statistics

“…However, the proposed approach is equally valid for multidirectional seas, leading to a larger eigenvalue problem. Note that, when crossing levels of interest are large, the CPU time needed for exact integration drops rapidly, as compared to the direct Monte Carlo (MC) simulation [1][2][3][4][5][6][7][8][9][10][11][12] . Since extreme up-crossing rates are quite important ones, this is a practical advantage for the exact saddle point integration method, as compared to the direct MC method.…”

“…For the TLP structure studied in this paper, the resonant heave and pitch responses have been influenced by the wave loads generated by combination of the first order and the second order (i.e. sum) frequencies, see [1][2][3][4][5][6][7][8][9][10][11][12][13][14] .…”

A novel statistical method for long-term coronavirus modelling

“…This study outlines a general-purpose, robust and straightforward multidimensional bio-system reliability method. The method introduced in this study has been previously successfully validated by application to a wide range of engineering models, 30,[40][41][42][43][44][45][46][47][48][49] but only for one and two-dimensional system responses and, in general, very accurate predictions were obtained. Both measured and simulated time series responses can be analysed using the proposed method.…”