Safety and Technical Protection Engineering
Abdolrahim Taheri; Soleimani torfi Soleimani torfi
Abstract
Pipelines are considered the most practical way to transport oil and gas. However, some factors such as corrosion, third party damage, etc. can lead to serious incidents. Appropriate risk assessment can help reduce the risk of pipeline systems. Prioritizing repairs, scheduling physical integrity assessments, ...
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Pipelines are considered the most practical way to transport oil and gas. However, some factors such as corrosion, third party damage, etc. can lead to serious incidents. Appropriate risk assessment can help reduce the risk of pipeline systems. Prioritizing repairs, scheduling physical integrity assessments, and developing emergency plans can’t be done properly without implementing an appropriate Risk Assessment Method. Risk consists of the Probability of Failure (PoF) and Consequence of Failure (CoF) and in many cases is obtained from the failure statistics published by the pipeline operators. In an endeavor to apply more engineering concepts to the highly statistics-dominated concept of risk assessment, the PoF can be calculated using Finite Element and Monte Carlo methods. This paper is specifically concerned with finding the PoF caused by excavations that are done neighboring a buried pipeline. which is a form of failure that is rarely considered, as most of the studies conducted about third party damages are concerned with the direct hit as a failure cause. Hence, a Python script was written that models the excavations using ABAQUS; The soil is modelled using the Mohr-Coulomb plasticity approach, while the pipe is modelled as a shell. The excavation adjacent to the pipe will cause the pipe to deflect due to gravity. The stress caused by this deflection is compared to the yield stress to determine whether or not it will fail. In order to determine the probability of failure (PoF), this iterative process is carried out for excavations of different sizes using a Monte Carlo method. Additionally, a methodology has been implemented to address the issue of computationally expensive models. The method proposed in this paper is compared and weighted against other common methods to determine whether the advantages of FEA-based risk assessment can justify its complexity.
