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Some observations on the subset simulation related to the wind turbine mechanics

机译：关于与风力发电机力学相关的子集模拟的一些观察

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The subset simulation method is considered to be one of the most powerful methods among the variance reduction Monte Carlo techniques. Potential shortcomings of the method are the bias in its estimations and potential challenges in finding important directions in high dimensional nonlinear problems. The important directions in the n-dimensional space of the problem are those toward which the failure region extends i.e. by moving in those directions the simulation will fall into the safe domain. It is clear that finding these important directions becomes increasingly difficult as the number of the basic random variables of the problem increases. Moreover when the failure domain of the problem is not a simply connected domain, e.g. failure islands, finding the correct direction, or island, becomes even more difficult. This case occurs frequently in time variant dynamic reliability analysis of nonlinear systems. It is interesting to determine applicability of the Subset Simulation (SS) techniques, as a powerful representative of Variance Reduction Monte Carlo (VRMC) methods, on the wind turbine systems specifically with an active controller. Hence in this paper we apply and discuss these methods on a benchmark wind turbine model and analyze the results in view of their applicability.
机译：子集仿真方法被认为是方差减少蒙特卡洛技术中最强大的方法之一。该方法的潜在缺点是其估计存在偏差，并且是在高维非线性问题中寻找重要方向的潜在挑战。问题的n维空间中的重要方向是故障区域向其延伸的方向，即，通过沿这些方向移动，模拟将落入安全域。显然，随着问题的基本随机变量数量的增加，找到这些重要方向变得越来越困难。此外，当问题的故障域不是简单连接的域时，例如失败的孤岛，找到正确的方向或孤岛，变得更加困难。这种情况在非线性系统的时变动态可靠性分析中经常发生。有趣的是，确定子集仿真（SS）技术的适用性，作为方差降低蒙特卡洛（VRMC）方法的有力代表，尤其是在具有主动控制器的风力涡轮机系统上。因此，在本文中，我们将这些方法应用于基准风力涡轮机模型并进行讨论，并鉴于其适用性来分析结果。

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