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Probabilistic fatigue analysis of marine structures using the univariate dimension-reduction method

机译:单因素降维方法的海洋结构概率疲劳分析

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Probabilistic fatigue analysis of offshore structures requires the numerical simulation of a huge number of loading cases to compute the long-term multi-dimensional integral associated to the fatigue damage assessment. This paper proposes the implementation of the univariate dimension-reduction method developed by Rahman and Xu [1] in order to compute the long-term fatigue damage more efficiently. This method is particularly attractive because it reduces significantly the number of simulations by decomposing the N-dimensional integral associated to expected long-term fatigue damage assessment into the sum of N one-dimensional integrals. In addition, this paper compares the univariate-dimension reduction method with the brute force direct integration methodology and other methods based on Taylor expansions, such as perturbation approach and asymptotic expansion method discussed by Low and Cheung [2]. Two comprehensive examples are included to show the effectiveness of the method. At first, the performance of the univariate dimension-reduction method is evaluated by assessing the fatigue damage of a theoretical structure represented by a single stress response amplitude operator (RAO). Then, in order to show a case of practical application, the fatigue damage is evaluated for a Steel Lazy Wave Riser (SLWR) connected to an FPSO in a water depth of 2200 m. (C) 2016 Elsevier Ltd. All rights reserved.
机译:海洋结构的概率疲劳分析需要对大量载荷工况进行数值模拟,以计算与疲劳损伤评估相关的长期多维积分。本文提出了由Rahman和Xu [1]开发的单变量降维方法的实现,以便更有效地计算长期疲劳损伤。该方法特别有吸引力,因为它通过将与预期的长期疲劳损伤评估相关的N维积分分解为N个一维积分的总和,大大减少了仿真次数。另外,本文将单变量降维方法与蛮力直接积分方法以及其他基于泰勒展开的方法进行了比较,如Low和Cheung [2]讨论的摄动方法和渐近展开方法。包括两个综合示例以说明该方法的有效性。首先,通过评估由单个应力响应幅度算子(RAO)表示的理论结构的疲劳损伤来评估单变量降维方法的性能。然后,为了展示实际应用的情况,对连接到FPSO的水深2200 m的钢懒人冒口(SLWR)进行了疲劳损伤评估。 (C)2016 Elsevier Ltd.保留所有权利。

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