Probabilistic Fatigue Evaluation of Floating Wind Turbine using Combination of Surrogate Model and Copula Model
暂无分享,去创建一个
[1] M. Rosenblatt. Remarks on a Multivariate Transformation , 1952 .
[2] R. Montes-Iturrizaga,et al. Environmental contours using copulas , 2015 .
[4] Erik Vanem,et al. Joint statistical models for significant wave height and wave period in a changing climate , 2016 .
[5] Yi Zhang,et al. Long-term performance assessment and design of offshore structures , 2015 .
[6] Frank Sehnke,et al. Wind turbine power curve modeling based on Gaussian Processes and Artificial Neural Networks , 2018, Renewable Energy.
[7] R. Montes-Iturrizaga,et al. Development of environmental contours using Nataf distribution model , 2013 .
[8] J. Jonkman,et al. Definition of a 5-MW Reference Wind Turbine for Offshore System Development , 2009 .
[9] Nicolas Gayton,et al. A combined Importance Sampling and Kriging reliability method for small failure probabilities with time-demanding numerical models , 2013, Reliab. Eng. Syst. Saf..
[10] Alberto Lamberti,et al. Coastal flooding: A copula based approach for estimating the joint probability of water levels and waves , 2015 .
[11] A. Kiureghian,et al. Multivariate distribution models with prescribed marginals and covariances , 1986 .
[12] John Dalsgaard Sørensen,et al. Uncertainty propagation through an aeroelastic wind turbine model using polynomial surrogates , 2018 .
[13] E. Heredia-Zavoni,et al. Assessment of uncertainty in environmental contours due to parametric uncertainty in models of the dependence structure between metocean variables , 2017 .
[14] Hamidreza Jafarnejadsani,et al. Adaptive Control of a Variable-Speed Variable-Pitch Wind Turbine Using Radial-Basis Function Neural Network , 2013, IEEE Transactions on Control Systems Technology.
[15] Jörg R. Seume,et al. Investigation of Site-Specific Wind Field Parameters and Their Effect on Loads of Offshore Wind Turbines , 2012 .
[16] Derek D. Stretch,et al. Simulating a multivariate sea storm using Archimedean copulas , 2013 .
[17] N. Jenkins,et al. Wind Energy Handbook: Burton/Wind Energy Handbook , 2011 .
[18] I. Sobol. On the distribution of points in a cube and the approximate evaluation of integrals , 1967 .
[19] C. Sallaberry,et al. Application of principal component analysis (PCA) and improved joint probability distributions to the inverse first-order reliability method (I-FORM) for predicting extreme sea states , 2016 .
[20] Felice D'Alessandro,et al. Practical guidelines for multivariate analysis and design in coastal and off-shore engineering , 2014 .
[21] Carlos Guedes Soares,et al. Adaptive surrogate model with active refinement combining Kriging and a trust region method , 2017, Reliab. Eng. Syst. Saf..
[22] M. Sklar. Fonctions de repartition a n dimensions et leurs marges , 1959 .
[23] Claudia Czado,et al. Selecting and estimating regular vine copulae and application to financial returns , 2012, Comput. Stat. Data Anal..
[24] Geoffrey E. Hinton,et al. Visualizing Data using t-SNE , 2008 .
[25] Dag Myrhaug,et al. Statistical properties of successive wave heights and successive wave periods , 2004 .
[26] Wei Liu,et al. Bivariate maximum entropy distribution of significant wave height and peak period , 2013 .
[27] D. Zafirakis,et al. The wind energy (r)evolution: A short review of a long history , 2011 .
[28] Philip Jonathan,et al. Modeling the Seasonality of Extreme Waves in the Gulf of Mexico , 2011 .
[29] John Dalsgaard Sørensen,et al. Assessment of Wind Turbine Structural Integrity using Response Surface Methodology , 2016 .
[30] Elzbieta M. Bitner-Gregersen,et al. Joint met-ocean description for design and operations of marine structures , 2015 .
[31] Sancho Salcedo-Sanz,et al. Short-term wind speed prediction in wind farms based on banks of support vector machines , 2011 .