Accelerated Corrosion Testing and Risk Assessment for Pipeline Monitoring in Petrochemical Units

ABSTRACT Pipeline corrosion is a major cause of leakage in the oil and gas industry, posing serious safety and environmental risks. This study proposes an accelerated evaluation strategy integrated with predictive modeling to enable rapid and accurate estimation of pipeline corrosion rates. Steel pipelines were subjected to hydrochloric acid (0.1–1.0%) immersion tests at 10–35°C, and data obtained under strong acidic conditions were used to establish correlations applicable to milder environments. Based on these datasets, a multi‐parameter coupled model was developed in MATLAB with pH and temperature as core inputs. Validation against experiments confirmed high reliability, with prediction errors consistently below 10%. The model is linked to the refinery's DCS and HAZOP framework, enabling real‐time monitoring and early warning for a wax oil hydrogenation unit, providing a practical tool for corrosion assessment, risk reduction, and safer pipeline operation.

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Publication Details

Journal
Chemical Engineering & Technology
Published
2026-01-01
DOI
https://doi.org/10.1002/ceat.70156
Primary Topic
Corrosion Behavior and Inhibition
Type
article
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article

Accelerated Corrosion Testing and Risk Assessment for Pipeline Monitoring in Petrochemical Units

Wang Fe, Huazhuo Wang, Jing Bian, Zeyu Zhang et al.
Chemical Engineering & Technology
Corrosion Behavior and Inhibition
article

Accelerated Corrosion Testing and Risk Assessment for Pipeline Monitoring in Petrochemical Units

Wang Fe, Huazhuo Wang, Jing Bian, Zeyu Zhang, Hehua Huang
article en

Abstract

ABSTRACT Pipeline corrosion is a major cause of leakage in the oil and gas industry, posing serious safety and environmental risks. This study proposes an accelerated evaluation strategy integrated with predictive modeling to enable rapid and accurate estimation of pipeline corrosion rates. Steel pipelines were subjected to hydrochloric acid (0.1–1.0%) immersion tests at 10–35°C, and data obtained under strong acidic conditions were used to establish correlations applicable to milder environments. Based on these datasets, a multi‐parameter coupled model was developed in MATLAB with pH and temperature as core inputs. Validation against experiments confirmed high reliability, with prediction errors consistently below 10%. The model is linked to the refinery's DCS and HAZOP framework, enabling real‐time monitoring and early warning for a wax oil hydrogenation unit, providing a practical tool for corrosion assessment, risk reduction, and safer pipeline operation.

Chemical Engineering & TechnologyVol. 49(1)
Shandong Academy of Environmental Science (CN), Shandong Special Equipment Inspection Institute (CN), Beijing University of Chemical Technology (CN)
Industry, innovation and infrastructure
Openalex Percentile: Top 92%
Corrosion Behavior and Inhibition
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