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Response-based method for determining the extreme behaviour of floating offshore platforms

机译:基于响应的浮动海上平台极端行为确定方法

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摘要

The accurate prediction of extreme excursion and mooring force of floating offshore structures due to multi-variete environmental conditions which requires the joint probability analysis of environmental conditions for the worst case situation is still impractical as the processing of large amount of met-ocean data is required. On the other hand, the simplified multiple design criteria (e.g. the N-year wave with associated winds and currents) recommended by API known as traditional method does lead neither to the N-year platform response nor to the N-year mooring force. Therefore, in order to reduce the level of conservatism as well as uncertainties involved in the traditional method the response-based method can be used as a reliable alternative approach. In this paper this method is described. In order to perform the calculations- faster using large databases of sea states, Artificial Neural Networks (ANN) is designed and employed. In the paper the response-based method is applied to a 200,000 tdw FPSO and the results are discussed.
机译:由于需要对大量海洋数据进行处理,因此需要对最恶劣情况下的环境条件进行联合概率分析,因此无法准确预测由于多种环境条件而导致的浮动海上结构的极端偏移和系泊力,因此仍然不切实际。 。另一方面,API所推荐的简化的多重设计标准(例如带有相关风和流的N年波浪)被称为传统方法,它既不会导致N年平台响应,也不会导致N年系泊力。因此,为了减少传统方法所涉及的保守性和不确定性,可以将基于响应的方法用作可靠的替代方法。本文介绍了这种方法。为了使用大型海况数据库更快地执行计算,设计并采用了人工神经网络(ANN)。在本文中,基于响应的方法应用于20万吨/天的FPSO,并讨论了结果。

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