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Gaussian process regression for fatigue reliability analysis of offshore wind turbines
Highlights The fatigue limit state (FLS) often drives the design of offshore wind turbine (OWT) sub-structures. Assessing FLS reliability for OWT sub-structures is computationally expensive. Gaussian process (GP) regressions are proposed to build efficient surrogate models of fatigue damage. The sensitivity of various goodness of fit metrics to different model assumptions is investigated. An illustrative application to three OWT sites is presented.
Abstract The fatigue limit state (FLS) often drives the design of offshore wind turbine (OWT) substructures in European waters. Assessing fatigue damage over the intended design life of an OWT is computationally expensive, primarily as dynamic structural analyses have to be run for a large number of stochastic wind and wave loading conditions. This makes structural reliability assessment for the FLS a challenging task. In addition to evaluating load-induced fatigue damage, simulation-based structural reliability analysis also requires sampling of random variables that model uncertainties in the capacity of OWT structural components. To this aim, we develop and validate a computational framework for OWT fatigue reliability analysis that relies on Gaussian process (GP) regression to build surrogate models of load-induced fatigue damage. We demonstrate that the proposed approach can reduce the computational effort required to evaluate FLS reliability with high accuracy through application to three plausible offshore wind farm sites in Europe. The sensitivity of various goodness-of-fit metrics to different model assumptions is investigated to further reduce the computational effort required to perform GP regression/predictions. The results from this study can provide guidance for practical applications of the proposed framework in OWT projects.
Gaussian process regression for fatigue reliability analysis of offshore wind turbines
Highlights The fatigue limit state (FLS) often drives the design of offshore wind turbine (OWT) sub-structures. Assessing FLS reliability for OWT sub-structures is computationally expensive. Gaussian process (GP) regressions are proposed to build efficient surrogate models of fatigue damage. The sensitivity of various goodness of fit metrics to different model assumptions is investigated. An illustrative application to three OWT sites is presented.
Abstract The fatigue limit state (FLS) often drives the design of offshore wind turbine (OWT) substructures in European waters. Assessing fatigue damage over the intended design life of an OWT is computationally expensive, primarily as dynamic structural analyses have to be run for a large number of stochastic wind and wave loading conditions. This makes structural reliability assessment for the FLS a challenging task. In addition to evaluating load-induced fatigue damage, simulation-based structural reliability analysis also requires sampling of random variables that model uncertainties in the capacity of OWT structural components. To this aim, we develop and validate a computational framework for OWT fatigue reliability analysis that relies on Gaussian process (GP) regression to build surrogate models of load-induced fatigue damage. We demonstrate that the proposed approach can reduce the computational effort required to evaluate FLS reliability with high accuracy through application to three plausible offshore wind farm sites in Europe. The sensitivity of various goodness-of-fit metrics to different model assumptions is investigated to further reduce the computational effort required to perform GP regression/predictions. The results from this study can provide guidance for practical applications of the proposed framework in OWT projects.
Gaussian process regression for fatigue reliability analysis of offshore wind turbines
Wilkie, David (author) / Galasso, Carmine (author)
Structural Safety ; 88
2020-09-04
Article (Journal)
Electronic Resource
English
Optimal structural reliability of offshore wind turbines
| British Library Conference Proceedings | 2005
Reliability Analysis and Design Procedures for Offshore Wind Turbines
| British Library Conference Proceedings | 2008