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- W2346269961 abstract "To harvest more energy from wind, wind turbine size has rapidly increased, entailing the serious concern on the reliability of the wind turbine. Accordingly, the international standard requires turbine designers to estimate the extreme load that could be imposed on a turbine during normal operations. At the design stage, physics-based load simulations can be used for this purpose. However, simulating the extreme load associated with a small load exceedance probability is computationally prohibitive. In this study, we propose using importance sampling combined with order statistics to reduce the computational burden significantly while achieving much better estimation accuracy than existing methods." @default.
- W2346269961 created "2016-06-24" @default.
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- W2346269961 date "2016-06-14" @default.
- W2346269961 modified "2023-09-27" @default.
- W2346269961 title "Computationally Efficient Uncertainty Minimization in Wind Turbine Extreme Load Assessments" @default.
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- W2346269961 doi "https://doi.org/10.1115/1.4033511" @default.
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