Specification of the design wind load based on wind tunnel experiments considering the statistical uncertainties due to limited ensemble sizes

对于基于风洞实验的设计风荷载规范，必须考虑从受限总体获得的统计不确定性。满足所选置信区间的基本策略使用特别取决于系综大小的调整因子。相应的程序例如在欧洲规范DIN-EN 1990：2010-12的附录通过测试设计中实现，用于电阻的设计值的规范。该项目旨在为估算空气动力系数设计值的最佳方法开发调整系数。虽然这些调整因素保证了不安全的解决方案的比例保持不变的合奏大小无关，不经济的解决方案的比例，在相当高估的设计风荷载增加合奏大小减小。这个比值是一个全新的概念，它的目的是为了帮助决策者确定所需的风洞试验次数，并遵循尽可能少的试验次数和尽可能多的试验次数的基本原则。与阻力面相反，气动力系数的设计值没有统一的目标分位值，目标值取决于极值的变化系数。因此，需要取决于系综大小和变化系数的调整因子。有两种方法可用于估算设计值。第一种方法直接使用独立的极值，从单次运行或子集中选取。使用子集的基本优点在于扩大的总体大小，基本上导致增加的统计稳定性。然而，对于子集，目标分位值增加，导致统计稳定性降低。此外，对于越来越短的子集，存在子集不再具有代表性的基本危险。从根本上说，一个扩大的合奏大小得到的峰值超过阈值采样。特别是基于最佳线性无偏估计（BLUE）进行估计。第二种方法使用Rice方法基于等效正态分布估计设计值。这种方法的基本要素是使用CDF映射或Hermite多项式的平移规则的估计，以及使用时间导数的方差或估计的谱密度函数的频率加权积分的循环率的估计。通过比较不同方法所得估计的质量特征，特别是相当多的不经济估计所占的比例，得出最优方法。

For the specification of the design wind load based on wind tunnel experiments statistical uncertainties have to be considered which are obtained from confined ensembles. The basic strategy for meeting a chosen confidence interval uses an adjusting factor which especially depends on the ensemble size. A corresponding procedure is implemented e.g. in the Eurocode DIN-EN 1990:2010-12 in the annex Design by testing for the specification of the design value of the resistance. The project aims in developing the adjusting factors for an optimal method for the estimation of the design value of the aerodynamic coefficient. While these adjusting factors guarantee that the ratio of unsafe solutions remains constant independent of the ensemble size, the ratio of uneconomic solutions in terms of considerable overestimated design wind loads increases for decreasing ensemble size. Fundamentally new, this ratio is developed to obtain an aid to decision-making in regard to the required number of wind tunnel runs following the basic principle as few runs as possible and as many runs as necessary. Opposite to the resistance side, there is no uniform target fractile value for the design value of the aerodynamic coefficients; the target value rather depends on the variation coefficient of the extremes. Consequently, adjusting factors are required depending on the ensemble size and the variation coefficient. Two alternative approaches are available for the estimation of the design value. The first approach directly uses independent extremes, either picked from single runs or from subsets. The basic advantage of using subsets lies in an enlarged ensemble size, basically leading to an increased statistical stability. However, for subsets the target fractile value increases, leading to decreasing statistical stability. Furthermore, for subsets becoming shorter and shorter there is the basic danger that the subset is no longer representative. Fundamentally new, an enlarged ensemble size is obtained by peaks-over-threshold sampling. Estimations especially are performed based on the Best Linear Unbiased Estimator (BLUE). The second approach estimates the design values based on an equivalent normal distribution using the Rice method. The fundamental elements of this approach are the estimation of the translation rule using CDF-mapping or Hermite polynomials, and the estimation of the cycling rate either using the variance of the time derivative or the frequency-weighted integration of the estimated spectral density function. The optimal method is obtained by comparing quality features of the estimations obtained by the different methods, especially the ratio of considerable uneconomic estimations.