• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Reliability Engineering & System Safety >Towards a probabilistic model for predicting ship besetting in ice in Arctic waters
【24h】

Towards a probabilistic model for predicting ship besetting in ice in Arctic waters

机译：建立概率模型以预测北极水域冰中的船舶困扰

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Recently, the melting of sea ice due to global warming has made it possible for merchant ships to navigate through Arctic Waters. However, Arctic Marine Transportation System remains a very demanding, dynamic and complex system due to challenging hydro-meteorological conditions, poorly charted waters and remoteness of the area resulting in lack of appropriate response capacity in case of emergency. In order to ensure a proper safety level for operations such as ship transit within the area, a risk analysis should be carried out, where the relevant factors pertaining to a given operation are defined and organized in a model. Such a model can assist onshore managers or ships' crews in planning and conducting an actual sea passage through Arctic waters. However, research in this domain is scarce, mainly due to lack of data. In this paper, we demonstrate the use of a dataset and expert judgment to determine the risk influencing factors and develop a probabilistic model for a ship besetting in ice along the Northeast Passage. For that purpose, we adopt Bayesian belief Networks (BBNs), due to their predominant feature of reasoning under uncertainty and their ability to accommodate data from various sources. The obtained BBN model has been validated showing good agreement with available state-of-the-art models, and providing good understanding of the analyzed phenomena. (C) 2016 Elsevier Ltd. All rights reserved.
机译：最近，由于全球变暖导致海冰融化，使商船在北极水域中航行成为可能。但是，由于具有挑战性的水文气象条件，水位不佳以及该地区偏远，北极海上运输系统仍然是一个非常苛刻，动态和复杂的系统，导致在紧急情况下缺乏适当的响应能力。为了确保诸如该区域内的船舶过境之类的操作具有适当的安全级别，应进行风险分析，并在模型中定义和组织与给定操作有关的相关因素。这种模型可以帮助陆上管理人员或船员规划和进行实际通过北极水域的海上通道。但是，这方面的研究很少，主要是由于缺乏数据。在本文中，我们演示了如何使用数据集和专家判断来确定风险影响因素，并为沿东北航道在冰层中航行的船舶建立概率模型。为此，我们采用贝叶斯信念网络（BBN），因为它们具有不确定性下推理的主要功能，并且能够容纳来自各种来源的数据。已验证所获得的BBN模型与可用的最新模型具有良好的一致性，并且可以很好地理解所分析的现象。 （C）2016 Elsevier Ltd.保留所有权利。

著录项

  • 来源
    《Reliability Engineering & System Safety》 |2016年第11期|124-136|共13页
  • 作者

    Fu Shanshan; Zhang Di; Montewka Jakub; Yan Xinping; Zio Enrico;

  • 作者单位

    Natl Engn Res Ctr Water Transport Safety, Wuhan, Peoples R China|Wuhan Univ Technol, Intelligent Transport Syst Res Ctr, Wuhan, Peoples R China|Univ Paris Saclay, Cent Supelec, Chair Syst Sci & Energet Challenge Fdn EDF, St Aubin, France;

    Natl Engn Res Ctr Water Transport Safety, Wuhan, Peoples R China|Wuhan Univ Technol, Intelligent Transport Syst Res Ctr, Wuhan, Peoples R China;

    Aalto Univ, Dept Appl Mech, Res Grp Maritime Risk & Safety, Espoo, Finland|Finnish Geospatial Res Inst, Masala, Finland|Gdynia Maritime Univ, Fac Nav, Dept Transport & Logist, PL-81225 Gdynia, Poland;

    Natl Engn Res Ctr Water Transport Safety, Wuhan, Peoples R China|Wuhan Univ Technol, Intelligent Transport Syst Res Ctr, Wuhan, Peoples R China;

    Univ Paris Saclay, Cent Supelec, Chair Syst Sci & Energet Challenge Fdn EDF, St Aubin, France|Politecn Milan, Dept Energy, Milan, Italy;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Ship performance in Arctic waters; Ship stuck in ice; Probabilistic risk assessment; Bayesian belief networks;

    机译：北极水域中的船舶性能;船舶被困在冰中;概率风险评估;贝叶斯信念网络;

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号