Development of a Framework for Assessing Cathodic Protection (CP) Effectiveness in Pipelines Based on Artificial Intelligence (AI)

Overview

Fast Facts
Project No.	1023
Contract No.	693JK32350005CAAP
Research Award Recipient	Texas A&M Engineering Experiment Station 400 Harvey Mitchell Parkway South Suite 300 College Station, TX 77845-4375
AOR/TTI	Katherine Roth Nusnin Akter
Researcher Contact Info	Dr. Homero Castaneda, Professor and Director at the National Corrosion and Materials Reliability Laboratory hcastaneda@tamu.edu 979-845-0750 Subcontract Prof. Hui Wang, University of Dayton (UDayton)

Technology and Commercialization
Technology Demonstrated	TBD
Commercialized (in whole/part)	TBD
Commercial Partner	Empty Value
Net Improvement	Empty Value

Financial and Status Data
Project Status	Active
Start Fiscal Year	2023 (09/30/2023)
End Fiscal Year	2026 (09/30/2026)
PHMSA $$ Budgeted	$580,271.00

Main Objective

The main objective is to provide a framework to identify, characterize, and assess CP systems on remote and difficult-to-access buried pipelines.

Public Abstract

This project aims to provide a framework to identify, characterize and assess the cathodic protection (CP) systems on remote and difficult-to-access buried pipelines. The approach integrates comprehensive laboratory characterization, numerical development, and extensive field monitoring data, analysis, and validation. The objective is to establish a robust, reliable, and accurate methodology and tool for evaluating the effectiveness of cathodic protection in mitigating degradation, anomalies, and failures related to coating and corrosion severity on buried pipelines. Additionally, the project seeks to validate corrosion severity levels when the coating is damaged and estimate the operational risks associated with CP performance to support integrity management programs. The overarching goal is to develop a methodology for assessing how the CP conditions influence coating performance and corrosion severity. The framework can be integrated and implemented to deploy a reliable, and accurate tool for early detection of failures caused by coating damage and corrosion severity. The results from this effort could be adapted to current external corrosion direct assessment (ECDA) practices to supplement the indirect survey technologies with an analysis of data based on deterministic, probabilistic, and AI tools underpinned by a strong foundational approach.

Anticipated Results: The result of the project would be a procedure including an integrated methodology to characterize and assess the CP effectiveness. The procedure and/or methodology would help prioritize high-risk (low CP effectiveness due to coating defects and corrosion severity) sites. The methodology could result in a standardized method that initiates the basis for threat location and prevention actions (such as where to implement, repair, monitor or enhance or redesign CP).

Potential Impact on Safety: The outcome of the project will positively impact safety by improving the integrity of the pipeline through the reduction of the number of incidents caused by the time-dependent threat (corrosion) or third-party damage. Developing a methodology to monitor, characterize and assess the CP will lead to minimizing the risk and maximizing the integrity based on optimizing corrosion assessment practices.