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<p>This study presents a novel lifetime assessment technique that may be used in cargo vessel transportation marine engineering applications. onboard measured a 4400 TEU container vessel ship panel stress data was analyzed, the data was measured during numerous trans-Atlantic crossings. The risk of container loss caused by excessive whipping loads is one of the key issues with cargo&#xa0;ship transportation. It is challenging to predict with accuracy excessive vessel deck panel stresses due to the complex nonlinear and nonstationary properties of wave and ship motions. 2nd and higher order vessel motion effects are typically observed when cargo ship is sailing in a severe, stormy environment, and the influence of nonlinearity grows noticeably. Depending on the wave flow characteristics and similarity ratios employed, laboratory testing may also be in dispute. Because of this, information acquired from ships operating in extreme weather conditions offers unique insight into container ship risks evaluation, as a whole. This study highlights novel multidimensional reliability approach, based on inherent qualities of the multivariate raw underlying dataset itself.</p><p>The main objective of the current study had been to benchmark the novel Gaidai multivariate risk assessment approach, using onboard measured cargo ship deck panel areal pressure dynamic system as underlying dataset. Gaidai multivariate risks evaluation methodology enabled efficient assessment of failure, hazard or damage risks for a variety of the non-linear multivariate vessel deck panel and ship hull stress systems.</p>

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Lifetime assessment for container ship by multimodal Gaidai risk evaluation method

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年1月6日

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  • Oleg Gaidai,
  • Alia Ashraf,
  • Yu Cao,
  • Yan Zhu,
  • Jinlu Sheng,
  • Zirui Liu

摘要

This study presents a novel lifetime assessment technique that may be used in cargo vessel transportation marine engineering applications. onboard measured a 4400 TEU container vessel ship panel stress data was analyzed, the data was measured during numerous trans-Atlantic crossings. The risk of container loss caused by excessive whipping loads is one of the key issues with cargo ship transportation. It is challenging to predict with accuracy excessive vessel deck panel stresses due to the complex nonlinear and nonstationary properties of wave and ship motions. 2nd and higher order vessel motion effects are typically observed when cargo ship is sailing in a severe, stormy environment, and the influence of nonlinearity grows noticeably. Depending on the wave flow characteristics and similarity ratios employed, laboratory testing may also be in dispute. Because of this, information acquired from ships operating in extreme weather conditions offers unique insight into container ship risks evaluation, as a whole. This study highlights novel multidimensional reliability approach, based on inherent qualities of the multivariate raw underlying dataset itself.

The main objective of the current study had been to benchmark the novel Gaidai multivariate risk assessment approach, using onboard measured cargo ship deck panel areal pressure dynamic system as underlying dataset. Gaidai multivariate risks evaluation methodology enabled efficient assessment of failure, hazard or damage risks for a variety of the non-linear multivariate vessel deck panel and ship hull stress systems.