权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

Preliminary Study of Pipeline Fatigue Crack Growth Prediction Utilizing Inline Inspection Data

利用在线检测数据预测管道疲劳裂纹扩展的初步研究

基本信息

批准号：
485866-2015
负责人：
Tian, Zhigang
金额：
$ 1.82万
依托单位：
University of Alberta
依托单位国家：
加拿大
项目类别：
Engage Grants Program
财政年份：
2015
资助国家：
加拿大
起止时间：
2015-01-01 至 2016-12-31
项目状态：
已结题

来源：
https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=585241
关键词：
Preliminary Study Pipeline Fatigue Crack

项目摘要

Pipelines are known as the safest and most economical way to transport large quantities of oil and gas products. Enbridge Pipelines Inc. operates the world's longest crude oil and liquids transportation system. Pipelines are subject to different types of defects, such as fatigue crack, corrosion, etc. If proper remediation actions are not taken, these defects can eventually result in pipeline failures including leaks or ruptures, which lead to very expensive downtime, and leakage and spillage of pipeline contents to the environment. Inline inspections (ILI) are performed periodically using smart pigging tools, to detect defects and evaluate pipeline health conditions. Fatigue cracking refers to crack growth due to fatigue caused by pressure cycling during pipeline operations. Fatigue cracking is a key hazard for liquid pipelines, which has not been well understood. In this project, we plan to perform a preliminary study of pipeline fatigue crack growth prediction utilizing inline inspection data, and develop pipe physical models and integrated fatigue crack growth model considering a single fatigue crack. The proposed tools are expected to achieve improved fatigue crack prediction accuracy, with the presence of large crack sizing error. The proposed pipeline fatigue crack growth prediction methods can contribute to preventing pipeline leaks and ruptures, reducing expensive downtime, and avoiding damage to the environment.

管道被认为是运输大量石油和天然气产品的最安全和最经济的方式。恩布里奇管道公司运营着世界上最长的原油和液体运输系统。管道受到不同类型的缺陷，如疲劳裂纹，腐蚀等，如果不采取适当的补救措施，这些缺陷最终可能导致管道故障，包括泄漏或破裂，昂贵的停机时间以及管道内容物泄漏和溢出到环境中。在线检查（ILI）使用智能清管工具定期执行，以检测缺陷并评估管道健康状况。疲劳裂纹是指管道运行期间压力循环引起的疲劳引起的裂纹生长。疲劳裂纹是液体管道的一个主要危害，但尚未得到很好的理解。在本项目中，我们计划利用管道疲劳裂纹扩展预测进行初步研究在线检测数据，并开发管道物理模型和综合疲劳裂纹扩展模型，一个疲劳裂纹所提出的工具有望实现提高的疲劳裂纹预测精度，存在较大的裂纹尺寸误差。管道疲劳裂纹扩展预测方法有助于防止管道泄漏和破裂，减少昂贵的停机时间，并避免损坏对环境