Visual Analytics for Pipeline Risk Assessment

当输送石油产品的管道发生故障时，可能会造成重大的经济、环境和/或 公共卫生后果。然而，因为收集了大量关于这一关键部件的数据 在基础设施方面，可以使用数据挖掘和分析技术来了解和缓解风险 导致管道故障。我们在这个项目上的行业合作伙伴TransCanada管道(TCPL)管理天然气 北美各地每天输送89亿立方英尺天然气的管道，并编制了 关于这些管道所有方面的详尽数据。作为其持续的系统范围风险的一部分 评估(SWRA)计划，TCPL正在对海量数据的收集和存储进行标准化 他们已经积累了。TCPL目前使用定量风险评估方法来计算系统范围的风险。 该项目将研究数据分析和视觉分析技术，这些技术可以用来补充和 提高根据SWRA方案收集的数据的有效性。

When pipelines transporting petroleum products fail, it can result in a major economic, environmental, and/or public health consequences. However, because a tremendous amount of data is collected on this critical piece of infrastructure, it's possible to use data mining and analysis techniques to understand - and mitigate - the risks leading to pipeline failure. Our industry partner on this project, TransCanada PipeLines (TCPL), manages gas pipelines throughout North America to transport 8.9 billion cubic feet of natural gas every day and compiles exhaustive data regarding all aspects of these pipelines. As part of their ongoing System-Wide Risk Assessment (SWRA) program, TCPL is standardizing data collection and storage for the huge amount of data they have amassed. TCPL currently uses quantitative risk assessment methods to calculate system wide risk. This project will investigate data analytics and visual analytics techniques that can be used to complement and increase the effectiveness of data collected under the SWRA program.