Statistical model for fragility estimates of offshore wind turbines subjected to aero-hydro dynamic loads

Jharna Pokhrel, Junwon Seo

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

This paper aims to develop statistical regression-based models to estimate responses of monopile foundation 5 MW Offshore Wind Turbines (OWTs) subjected to multi-wind-and-wave loads and to assess its fragilities. Establishing the regression models began with the use of the Latin Hypercube Sampling (LHS) method incorporating 5 MW OWT input parameters related to structural and loading conditions along with material properties. With the LHS-based input parameters, 120 OWT computational models were created through Fatigue, Aerodynamic, Structures, and Turbulence (FAST) tools developed by the National Renewable Energy Laboratory (NREL). Critical responses, such as tower-top deflection, corresponding to each of the models were determined by performing its FAST aero-hydro dynamic simulations. The regression models involved a series of developed explanatory functions based on a matrix of the FAST responses and LHS parameters under a Stepwise Multiple Linear Regression (SMLR) approach. Multi-wind-and-wave fragilities were estimated for each of the critical responses of the 120 OWT models. Key findings showed that the wind-sensitive blade tip deflection resulted in the fragility of 99% at a critical wind speed of 75 m/s and a wave height of 20m, while the mudline flexural moment resulting from the same wind speed and wave height caused the fragility up to 98%.

Original languageEnglish
Pages (from-to)1495-1507
Number of pages13
JournalRenewable Energy
Volume163
DOIs
StatePublished - Jan 2021

Bibliographical note

Publisher Copyright:
© 2020 Elsevier Ltd

Keywords

  • FAST
  • Fragility
  • Offshore wind turbine
  • Regression model
  • Wave
  • Wind

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment

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