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Environmental contours for describing extreme ocean wave conditions based on combined datasets

机译:基于组合数据集描述极端海浪条件的环境等值线

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摘要

Environmental contours are often applied in structural reliability assessment and design of ships and other marine structures in order to describe joint extreme values of environmental variables such as significant wave height and wave period. Environmental contours are typically calculated based on a joint probability distribution function established for the relevant input parameters by fitting a parametric model to available data. However, in some situations there might be several datasets available with different probability content, and it may be desirable to make environmental contours that take the combined dataset into account. This paper explores different ways the information contained in such combined datasets can be utilized in order to establish environmental contours. Two different approaches are investigated. The first weights data points according to their probability content when calculating environmental contours directly on the data to obtain weighted contours. The second approach uses the combined dataset for fitting a parametric distribution to the data, where different censoring effects are taken into account, in order to get more accurate estimates of extreme conditions. Both approaches may work well, depending on the type of datasets that are available and can be combined. However, the first approach assumes that the direct sampling method for environmental contours are used, and this method has been used in all examples in this paper. Some examples illustrate the usefulness and drawbacks of the different methods.
机译:为了描述环境变量的联合极端值,例如重要的波浪高度和波浪周期,通常将环境等值线用于船舶和其他海洋结构的结构可靠性评估和设计中。典型地,通过将​​参数模型拟合到可用数据,基于为相关输入参数建立的联合概率分布函数来计算环境轮廓。但是,在某些情况下,可能会有几个具有不同概率内容的数据集,并且可能需要考虑合并的数据集的环境轮廓。本文探索了利用这些组合数据集中包含的信息以建立环境轮廓的不同方法。研究了两种不同的方法。当直接在数据上计算环境轮廓以获得加权轮廓时,第一加权数据点将根据其概率内容进行加权。第二种方法使用组合的数据集将参数分布拟合到数据,其中考虑了不同的检查效果,以便更准确地估计极端条件。这两种方法可能效果很好,这取决于可用的并且可以组合的数据集的类型。但是,第一种方法假定使用的是环境轮廓的直接采样方法,并且此方法已在本文的所有示例中使用。一些示例说明了不同方法的有用性和缺点。

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