Dynamic reliability model for subsea pipeline risk assessment due to third-party interference

IF 4.8 Q2 ENERGY & FUELS
Reza Aulia, Henry Tan, Srinivas Sriramula
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引用次数: 9

Abstract

The accidents of subsea pipelines due to third-party interference often result in catastrophic impacts, therefore, risk assessment has progressively become substantial to ensure the safety and reliability of the systems. However, the current risk analysis approaches are unable to minimize the uncertainties in the analysis due to the high demands of the qualitative inputs. The Bayesian network approach is believed to be able to provide answers to such a problem. The main advantage of this technique is that it allows the inference model and predictive analysis for constructing the current and future performance of the system based on the observed evidence. These can be achieved by introducing the subsea pipeline’s accident history and operational data in the model for developing the conditional probability distribution of each variable in the analysis. This paper proposes a dynamic reliability model for subsea pipeline risk assessment due to third-party interference based on the Bayesian approach. This technique is combined with fault tree and the finite element models for producing a reliable risk assessment framework for subsea pipelines. It is expected that the proposed model will be able to minimize the number of qualitative inputs in the analysis and also provides dynamic results for estimating the risk level of the subsea pipeline throughout its service life.

第三方干扰下海底管道风险评估的动态可靠性模型
由于第三方干扰导致的海底管道事故往往会造成灾难性的影响,因此,为了确保系统的安全性和可靠性,风险评估日益重要。然而,目前的风险分析方法由于对定性输入的要求很高,无法最大限度地减少分析中的不确定性。贝叶斯网络方法被认为能够提供这样一个问题的答案。该技术的主要优点是它允许基于观察到的证据构建系统当前和未来性能的推理模型和预测分析。这可以通过在模型中引入海底管道的事故历史和运行数据来实现,以开发分析中每个变量的条件概率分布。本文提出了一种基于贝叶斯方法的海底管道第三方干扰风险评估动态可靠性模型。该技术与故障树和有限元模型相结合,可为海底管道提供可靠的风险评估框架。预计所提出的模型将能够最大限度地减少分析中定性输入的数量,并为估计海底管道在整个使用寿命期间的风险水平提供动态结果。
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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CiteScore
7.50
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