A Benchmarking Exercise on Estimating Extreme Environmental Conditions: Methodology and Baseline Results

Andreas F. Haselsteiner, R. Coe, L. Manuel, P. Nguyen, Nevin Martin, A. Eckert-Gallup
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引用次数: 16

Abstract

A wide range of methods have been proposed for the derivation of environmental contours for marine structures that must meet reliability targets. An environmental contour is a set of joint extremes of environmental conditions associated with a target return period. In general, environmental contour methods help with the prediction of some future critical combinations of environmental conditions (e.g., wind, waves, current) at a location of interest based on a limited dataset, thus allowing designers to ensure a prescribed structural reliability. In fact, some of these contour methods are specifically recommended by technical specifications and standards as part of a design process. This paper outlines the rules and procedures for a collaborative benchmarking exercise — focused on open comparison — in which researchers are invited to develop and present their own contour derivation approaches based on common datasets that will be available to all. Hindcast and observational datasets are considered and two exercises are planned: One focuses on applying environmental contour methods to a wide range of datasets and the other focuses on uncertainty characterization. Besides describing the benchmark’s methodology, this paper presents baseline results of computed contours following current recommendations. The overall goals of this endeavor are: (i) to work towards the development of more robust statistical models and contour construction methods, (ii) to encourage increased discussion in the international research community and among practitioners, and (iii) to support ongoing efforts to improve technical specifications and standards.
估计极端环境条件的基准练习:方法和基线结果
对于必须满足可靠性目标的海洋结构,已经提出了各种各样的方法来推导环境轮廓。环境等高线是一组与目标回报期相关的环境条件的联合极值。一般来说,环境等高线方法有助于基于有限数据集预测感兴趣位置的一些未来关键环境条件组合(例如,风、波浪、电流),从而使设计人员能够确保规定的结构可靠性。事实上,其中一些轮廓方法是技术规范和标准特别推荐的,作为设计过程的一部分。本文概述了协作基准测试练习的规则和程序-重点是公开比较-在该练习中,研究人员被邀请开发并展示他们自己的基于所有人都可以使用的公共数据集的轮廓推导方法。考虑了后投和观测数据集,并计划了两个练习:一个侧重于将环境等高线方法应用于广泛的数据集,另一个侧重于不确定性表征。除了描述基准的方法外,本文还介绍了根据当前建议计算轮廓的基线结果。这项工作的总体目标是:(i)致力于开发更稳健的统计模型和等高线构建方法,(ii)鼓励国际研究界和从业者之间增加讨论,以及(iii)支持不断改进技术规范和标准的努力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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