Reliability assessment of offshore dynamic scour protections using copulas

• Type: Article in International Scientific Journal
• Date: 2019

Authors

T. Fazeres-Ferradosa (Author) Other; Francisco Taveira Pinto (Author) FEUP; Xavier Romão (Author) FEUP; M. T. Reis (Author) Other; Luciana das Neves (Author) FEUP

Journal

Title: Wind Engineering

Vol. 43

Pages: 506-538

ISSN: 0309-524X

Publisher: SAGE

Indexing

ISI Web of Knowledge - 0 Citations

Scopus - 6 Citations

Other information

Authenticus ID: P-00P-WHF

DOI: 10.1177/0309524x18807033

Abstract (EN): This article presents a methodology to assess the reliability of dynamic scour protections used to protect offshore wind turbine foundations. The computed probabilities of failure are based on a dataset of 124 months of hindcast data from the Horns Rev 3 offshore wind farm. Copula-based models are used to obtain the joint distribution function of the significant wave height and spectral peak period and to obtain the probability of failure of scour protections. The sensitivity of the probability of failure to each model is addressed. The influence of the duration of the waves' time series is also studied. A sensitivity analysis of the probability of failure to physical constraints, such as the water depth, current's velocity or the mean diameter of the armour units, is performed. The results show that probability of failure is dependent on the copula used to model the spectral parameters and the associated value of Kendall's tau. It is shown that the copula presenting the best values of Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) did not lead to the probabilities of failure that are closer to the non-parametric estimation, obtained by means of the bivariate version of the Kernel density estimation method. The application to the case study led to annual probabilities of failure, which are comparable with the values applied for other offshore components, according to the current offshore wind industry standards.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 33