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Dissertation/Thesis Abstract

Analyzing Critical Pipeline Crossings at Highways
by Karki, Iha, M.S., California State University, Long Beach, 2020, 67; 27962861
Abstract (Summary)

The US Congress is interested in determining how the age of pipelines correlates to pipeline failure, because even though government and industry have taken steps to improve pipeline safety in the past, pipeline failures are still a huge current issue. This issue is also a major concern for California Department of Transportation (CALTRANS) and many other entities, since failures of these pipelines (in the form of hazardous liquids and gasoline leakages) around high traffic roads can cause major highways to close. There are various contributing factors in pipeline failures, both external and internal. Although many of these factors of failure are unpredictable, age is a factor that can be tracked. Empirical data shows that the older a pipeline is, the higher the risk of failure. However, not all pipelines that are underground have a record of their age, especially at the crossings with high traffic volume roads.

This research has closely studied 74 pipeline and highway crossings in the County of Los Angeles (LA) and identified the highest risk crossings based on the record of pipelines for which the installation year is known. The installation year obtained from the Pipeline and Hazardous Material Safety Administration (PHMSA) for pipeline accidents was utilized to assign an age to the 74 pipeline crossings using the method of Point Distance Analysis on Geographic Information Systems (GIS) to formulate the Origin-Destination Matrix (O-D Matrix). The O-D Matrix exhibits all 1,036 distances from the 14 pipeline incident locations to the 74 crossings. The analysis displayed evidence that freeways I-10, SR-60 and SR-57 have the highest risk for pipeline failure as they are determined to be the oldest pipelines. Additional analysis was conducted on the 14 accidents using the Nearest Neighbor Analysis on GIS which resulted in a z-score of 2.594442 and a p-value of 0.009474 which showed the data to be dispersed and significant. The analysis methods from this study may lead to establishing policies to monitor the age of pipelines to predict future failures and other related applications.

Indexing (document details)
Advisor: Chandra, Shailesh
Commitee: Asvapathanagul, Pitiporn, Hong, Jin Gi
School: California State University, Long Beach
Department: Civil Engineering & Construction Engineering Management
School Location: United States -- California
Source: MAI 82/4(E), Masters Abstracts International
Subjects: Civil engineering, Transportation, Engineering
Keywords: Age of Pipelines, County of Los Angeles, High Risk Utilities, Highways, Pipeline Failure, Transportation
Publication Number: 27962861
ISBN: 9798684689017
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