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research-article

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

[+] Author and Article Information
Phong T. T. Nguyen

301 E. Dean Keeton St., Stop C1747, Dept. of Civil, Arch., and Env. Engineering Austin, TX 78712 phongnguyen@utmail.utexas.edu

Lance Manuel

Dept. of Civil, Architectural and Environmental Engineering University of Texas at Austin Austin, TX 78712 lmanuel@mail.utexas.edu

Ryan G. Coe

PO BOX 5800, MS 1124 Albuquerque, NM 87106 rcoe@sandia.gov

1Corresponding author.

Contributed by the Ocean, Offshore, and Arctic Engineering Division of ASME for publication in the Journal of Offshore Mechanics and Arctic Engineering. Manuscript received November 22, 2018; final manuscript received February 8, 2019; published online xx xx, xxxx. Assoc. Editor: Zhen Gao.

ASME doi:10.1115/1.4042944 History: Received November 22, 2018; Accepted February 08, 2019

Abstract

Accurate prediction of long-term extreme loads is essential for the design of wave energy converters (WECs), but it is also computationally demanding due to the low probabilities associated with their occurrence. While a full long-term probabilistic analysis using integration over all sea states or Monte Carlo Simulation (MCS) may be used, these methods can be prohibitively expensive when individual response simulations are complex and time-consuming. The application of polynomial chaos expansion (PCE) schemes to allow the propagation of uncertainty from the environment through the stochastic sea surface elevation process and ultimately to WEC extreme load response prediction is the focus in this study. A novel approach that recognizes the role of long-term ocean climate uncertainty (in sea state variables like significant wave height and spectral peak period) as well as short-term response uncertainty arising from the unique random phasing in irregular wave trains is presented and applied to a single-body point-absorber WEC device model. Stochastic simulation results in time series realizations of various response processes for the case-study WEC. We employ environmental data from a possible deployment site in Northern California (NDBC 46022) to assess long-term loads. MCS computations are also performed and represent the “truth” system against which the efficiency and accuracy of the PCE surrogate model is assessed. Results suggest that the PCE approach requires significantly less effort to obtain comparable estimates to MCS.

Copyright © 2019 by ASME
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