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Application of Probabilistic Model in SCCDA

Stress Corrosion Cracking (SCC) is a serious threat to our pipeline infrastructure. Past SCC failures have shown that both NN pH SCC and high pH SCC may lead to catastrophic pipeline failure. This is due to the formation of cracks that are difficult to detect. Moreover, SCC is difficult to predict, as multiple mechanisms must interact to lead to the formation of these cracks.

Product Number: 51323-18956-SG
Author: Francois Ayello, Ramgopal Thodla, Guanlan Liu, Narasi Sridhar
Publication Date: 2023
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Stress Corrosion Cracking Direct Assessment (SCCDA) is a valuable tool for gas and liquid pipeline risk management, and it is used across the pipeline industry. To carry out SCCDA pipeline operators usually use AMPP standards SP0204 which follow a four-step approach: (1) pre-assessment step used for data gathering, (2) indirect assessment using the collected data and prioritizing inspection locations, (3) direct examination using a combination of excavations and in-line inspection, and finally (4) a post-assessment that established re-inspection intervals and informs other threat assessments. The publication shows how a SCC probabilistic model will help each step of the SCCDA. The main benefits are (1) improved data gathering activities using data uncertainty to help pipeline operators focus on the most useful data and (2) help calculate the optimal number of digs to help pipeline operators shift focus from one pipeline to the next when the probability of failure drops below an acceptable level. The model used was developed in a PHMSA funded project and the methodology is tested using data provided by 4 pipeline operators in the United States and Canada.
 

Stress Corrosion Cracking Direct Assessment (SCCDA) is a valuable tool for gas and liquid pipeline risk management, and it is used across the pipeline industry. To carry out SCCDA pipeline operators usually use AMPP standards SP0204 which follow a four-step approach: (1) pre-assessment step used for data gathering, (2) indirect assessment using the collected data and prioritizing inspection locations, (3) direct examination using a combination of excavations and in-line inspection, and finally (4) a post-assessment that established re-inspection intervals and informs other threat assessments. The publication shows how a SCC probabilistic model will help each step of the SCCDA. The main benefits are (1) improved data gathering activities using data uncertainty to help pipeline operators focus on the most useful data and (2) help calculate the optimal number of digs to help pipeline operators shift focus from one pipeline to the next when the probability of failure drops below an acceptable level. The model used was developed in a PHMSA funded project and the methodology is tested using data provided by 4 pipeline operators in the United States and Canada.