Offshore wind turbine risk quantification/evaluation under extreme environmental conditions

Alexandros A. Taflanidis, Eva Loukogeorgaki and Demos C. Angelides

Reliability Engineering and System Safety, 2013, vol. 115, issue C, 19-32

Abstract: A simulation-based framework is discussed in this paper for quantification/evaluation of risk and development of automated risk assessment tools, focusing on applications to offshore wind turbines under extreme environmental conditions. The framework is founded on a probabilistic characterization of the uncertainty in the models for the excitation, the turbine and its performance. Risk is then quantified as the expected value of some risk consequence measure over the probability distributions considered for the uncertain model parameters. Stochastic simulation is proposed for the risk assessment, corresponding to the evaluation of some associated probabilistic integral quantifying risk, as it allows for the adoption of comprehensive computational models for describing the dynamic turbine behavior. For improvement of the computational efficiency, a surrogate modeling approach is introduced based on moving least squares response surface approximations. The assessment is also extended to a probabilistic sensitivity analysis that identifies the importance of each of the uncertain model parameters, i.e. risk factors, towards the total risk as well as towards each of the failure modes contributing to this risk. The versatility and computational efficiency of the advocated approaches is finally exploited to support the development of standalone risk assessment applets for automated implementation of the probabilistic risk quantification/assessment.

Keywords: Risk assessment; Sensitivity analysis; Stochastic simulation; Probabilistic uncertainty; Offshore wind turbines; Automated assessment tools (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (11)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:115:y:2013:i:c:p:19-32

DOI: 10.1016/j.ress.2013.02.003

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