Comparative Study of Time-Domain Fatigue Assessments for an Offshore Wind Turbine Jacket Substructure by Using Conventional Grid-Based and Monte Carlo Sampling Methods

Chi-Yu Chian, Yi-Qing Zhao, Tsung-Yueh Lin, Bryan Nelson and Hsin-Haou Huang
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Chi-Yu Chian: Department of Engineering Science and Ocean Engineering, National Taiwan University, Taipei 106, Taiwan
Yi-Qing Zhao: Department of Engineering Science and Ocean Engineering, National Taiwan University, Taipei 106, Taiwan
Tsung-Yueh Lin: R/D Section, Research Department, CR Classification Society, Taipei 10487, Taiwan
Bryan Nelson: R/D Section, Research Department, CR Classification Society, Taipei 10487, Taiwan
Hsin-Haou Huang: Department of Engineering Science and Ocean Engineering, National Taiwan University, Taipei 106, Taiwan

Energies, 2018, vol. 11, issue 11, 1-17

Abstract: Currently, in the design standards for environmental sampling to assess long-term fatigue damage, the grid-based sampling method is used to scan a rectangular grid of meteorological inputs. However, the required simulation cost increases exponentially with the number of environmental parameters, and considerable time and effort are required to characterise the statistical uncertainty of offshore wind turbine (OWT) systems. In this study, a K-type jacket substructure of an OWT was modelled numerically. Time rather than frequency-domain analyses were conducted because of the high nonlinearity of the OWT system. The Monte Carlo (MC) sampling method is well known for its theoretical convergence, which is independent of dimensionality. Conventional grid-based and MC sampling methods were applied for sampling simulation conditions from the probability distributions of four environmental variables. Approximately 10,000 simulations were conducted to compare the computational efficiencies of the two sampling methods, and the statistical uncertainty of the distribution of fatigue damage was assessed. The uncertainty due to the stochastic processes of the wave and wind loads presented considerable influence on the hot-spot stress of welded tubular joints of the jacket-type substructure. This implies that more simulations for each representative short-term environmental condition are required to derive the characteristic fatigue damage. The characteristic fatigue damage results revealed that the MC sampling method yielded the same error level for Grids 1 and 2 (2443 iterations required for both) after 1437 and 516 iterations for K- and KK-joint cases, respectively. This result indicated that the MC method has the potential for a high convergence rate.

Keywords: jacket substructure; fatigue damage; statistical uncertainty; Monte Carlo method; time domain; offshore wind turbine (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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