Proactive maintenance strategy for submarine pipelines based on stochastic modelling of deterioration due to corrosion

This study presents a stochastic model for corrosion deterioration in submarine pipelines, a major threat to structural integrity and operational efficiency. Using Bayesian updating, the model dynamically adjusts its parameters with new inspection data, improving predictions of corrosion growth and optimizing maintenance intervals to minimize failures. A numerical example demonstrates the model’s effectiveness in forecasting corrosion progression and enhancing maintenance decisions based on reliability and failure probability using the gamma process.