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翻訳と辞書　辞書検索 [ 開発暫定版 ] スポンサード リンク Sandia method ： ウィキペディア英語版 Sandia method The Sandia method (also known as Veers method) is a method for generating a turbulent wind profile that can be used in aero-elastic software to evaluate the fatigue imparted on a turbine in a turbulent environment. That is, it generates time series of wind speeds at a set of points on a surface, say the plane of the rotor of a wind turbine. Analysis is performed initially in the frequency domain, where turbulence can be described quantitatively with more ease than the time domain. Then, the time series are obtained by inverse fast Fourier transforms. In its original form, the Sandia method only simulates the u-component of the wind; that is, the wind was modelled as propagating in a direction perpendicular to the plane of the rotor. Work carried out by NREL, specifically Kelley, suggested that a considerable amount of turbulent energy existed in the v-component (the v-component is parallel to both the plane of the rotor and the Earth). As such, the Sandia method was upgraded such that it included the v-component and w-component. Further upgrades have been performed such that the wind profile exhibits cross-axis correlation (turbulent fluctuations in one component being somehow connected to turbulent fluctuations in another). However, these are not considered in this article. == Point-wind speed spectra == Although turbulence leads to unpredictable results in the time domain, it can, to some extent, be characterized in the frequency domain. Turbulent fluctuations are dominated by low frequency components, with higher frequency components having less influence. For further information, see Kolmogorov's theory on turbulence. Several models of frequency domain representations of point wind speeds have been developed: the von Kármán wind turbulence model and Dryden Wind Turbulence Model are examples of such. 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Sandia method」の詳細全文を読む スポンサード リンク 翻訳と辞書 : 翻訳のためのインターネットリソース Copyright(C) kotoba.ne.jp 1997-2016. All Rights Reserved.