基于检测和缓解结果的管道应力腐蚀开裂敏感性框架:贝叶斯方法

Oleg Shabarchin, S. Koduru, S. Hassanien
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引用次数: 0

摘要

应力腐蚀开裂(SCC)是一种由敏感材料、拉应力和适当环境相互作用引起的开裂形式。考虑到最近SCC在管道中的故障,以及越来越严格的监管要求,运营商必须制定有效的SCC完整性管理计划。为了实现这一目标,项目不仅要整合影响SCC的多个相互作用因素,而且要整合来自项目缓解行动的证据。本文提出了一个基于贝叶斯方法的框架,将多条证据线合并在一起,同时透明地处理相关的不确定性,以估计更具代表性的SCC发生率和相应的SCC故障率。从行业SCC管理最佳实践和SCC敏感性模型中收集的知识,结合专家知识和ILI研究结果,制定了拟议的框架。该框架由两个部分组成;首先,建立SCC敏感性,以量化管道上的SCC发生率。其次,使用贝叶斯更新将现场证据纳入框架,以改进特定路段SCC发生率和故障率的初始估计。该方法提供了显著的灵活性,可以在程序的任何成熟度级别上,随着额外的数据变得可用而更新所建议的模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Framework for Pipeline Stress Corrosion Cracking Susceptibility Using Inspection & Mitigation Results: A Bayesian Approach
Stress Corrosion Cracking (SCC) is a form of cracking caused by interaction of a susceptible material, tensile stress, and a suitable environment. Considering recent SCC failures in pipelines coupled with increasingly stringent regulatory requirements, it is imperative for an operator to have an effective SCC integrity management program. To accomplish this, it is essential for the program to not only integrate multiple interacting factors that influence SCC, but also incorporate evidence from program mitigation actions. This paper presents a framework based on Bayesian approach to incorporate multiple lines of evidence while transparently treating associated uncertainty to estimate a more representative SCC occurrence and corresponding SCC failure rate. Knowledge gathered from industry SCC management best practices and SCC susceptibility models are used in conjunction with expert knowledge and ILI findings to develop the proposed framework. The framework consists of two components; first, SCC susceptibility is established to quantify the SCC occurrence rate on a pipeline. Second, field evidence is incorporated into the framework using Bayesian updating to refine the initial estimates of segment specific SCC occurrence and failure rate. The approach provides a significant flexibility to update the proposed model at any maturity level of the program as additional data becomes available.
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