On the Development of an Efficient Surrogate Model for Predicting Long-Term Extreme Loads on a Wave Energy Converter

[1]  Wei Chen,et al.  Assessing the Reliability of Complex Models: Mathematical and Statistical Foundations of Verification, Validation, and Uncertainty Quantification , 2012 .

[2]  G. Stefanou The stochastic finite element method: Past, present and future , 2009 .

[3]  Puneet Agarwal,et al.  On the modeling of nonlinear waves for prediction of long-term offshore wind turbine loads , 2009 .

[4]  Bruno Sudret,et al.  Global sensitivity analysis using polynomial chaos expansions , 2008, Reliab. Eng. Syst. Saf..

[5]  A. Kiureghian,et al.  Multivariate distribution models with prescribed marginals and covariances , 1986 .

[6]  Dongbin Xiu,et al.  The Wiener-Askey Polynomial Chaos for Stochastic Differential Equations , 2002, SIAM J. Sci. Comput..

[7]  Ryan G. Coe,et al.  Alternative approaches to develop environmental contours from metocean data , 2018, Journal of Ocean Engineering and Marine Energy.

[8]  Lance Manuel,et al.  On Assessing the Accuracy of Offshore Wind Turbine Reliability-based Design Loads From the Environmental Contour Method , 2005 .

[9]  Lance Manuel,et al.  A comparison of wind turbine design loads in different environments using inverse reliability techniques , 2004 .

[10]  M. Rosenblatt Remarks on a Multivariate Transformation , 1952 .

[11]  Lance Manuel,et al.  Uncertainty Quantification of Riser Fatigue Damage due to VIV Using a Distributed Wake Oscillator Model , 2017 .

[12]  Lance Manuel,et al.  On Efficient Long-Term Extreme Response Estimation for a Moored Floating Structure , 2018, Volume 3: Structures, Safety, and Reliability.

[13]  Ryan G. Coe,et al.  Full long-term design response analysis of a wave energy converter , 2018 .