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      System Reliability Analysis of an Offshore Jacket Platform

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          Abstract

          This study investigates strategies for solving the system reliability of large three-dimensional jacket structures. These structural systems normally fail as a result of a series of different components failures. The failure characteristics are investigated under various environmental conditions and direction combinations. The β-unzipping technique is adopted to determine critical failure components, and the entire system is simplified as a series-parallel system to approximately evaluate the structural system reliability. However, this approach needs excessive computational effort for searching failure components and failure paths. Based on a trained artificial neural network (ANN), which can be used to approximate the implicit limit-state function of a complicated structure, a new alternative procedure is proposed to improve the efficiency of the system reliability analysis method. The failure probability is calculated through Monte Carlo simulation (MCS) with Latin hypercube sampling (LHS). The features and applicability of the above procedure are discussed and compared using an example jacket platform located in Chengdao Oilfield, Bohai Sea, China. This study provides a reference for the evaluation of the system reliability of jacket structures.

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          Author and article information

          Journal
          JOUC
          Journal of Ocean University of China
          Science Press and Springer (China )
          1672-5182
          20 December 2019
          01 February 2020
          : 19
          : 1
          : 47-59
          Affiliations
          1College of Engineering, Ocean University of China, Qingdao 266100, China
          2Centre for Marine Technology and Ocean Engineering (CENTEC), Instituto Superior Técnico, Lisboa 1049-001, Portugal
          Author notes
          *Corresponding author: DONG Sheng, Tel: 0086-532-66781125, E-mail: dongsh@ 123456ouc.edu.cn
          Article
          s11802-020-4181-2
          10.1007/s11802-020-4181-2
          Copyright © Ocean University of China, Science Press and Springer-Verlag GmbH Germany 2020.

          The copyright to this article, including any graphic elements therein (e.g. illustrations, charts, moving images), is hereby assigned for good and valuable consideration to the editorial office of Journal of Ocean University of China, Science Press and Springer effective if and when the article is accepted for publication and to the extent assignable if assignability is restricted for by applicable law or regulations (e.g. for U.S. government or crown employees).

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          Self URI (journal-page): https://www.springer.com/journal/11802

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