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Naji, M. |
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Motta, Antonella |
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Aletan, Dirar |
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Mohamed, Tarek |
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Ertürk, Emre |
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Taccardi, Nicola |
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Kononenko, Denys |
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Petrov, R. H. | Madrid |
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Alshaaer, Mazen | Brussels |
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Bih, L. |
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Casati, R. |
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Muller, Hermance |
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Kočí, Jan | Prague |
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Šuljagić, Marija |
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Kalteremidou, Kalliopi-Artemi | Brussels |
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Azam, Siraj |
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Ospanova, Alyiya |
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Blanpain, Bart |
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Ali, M. A. |
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Popa, V. |
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Rančić, M. |
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Ollier, Nadège |
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Azevedo, Nuno Monteiro |
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Landes, Michael |
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Rignanese, Gian-Marco |
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Garaniya, Vikram
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Topics
Publications (13/13 displayed)
- 2024Classification of pitting corrosion damage in process facilities using supervised machine learningcitations
- 2022Experimental analysis of pitting corrosion in offshore structurescitations
- 2020Pitting corrosion modelling of X80 steel utilized in offshore petroleum pipelinescitations
- 2018Condition monitoring of subsea pipelines considering stress observation and structural deteriorationcitations
- 2017Modelling the impacts of fire in a typical FLNG processing facility
- 2017Modelling the impacts of fire in a typical FLNG processing facility
- 2017Accelerated pitting corrosion test of 304 stainless steel using ASTM G48; Experimental investigation and concomitant challengescitations
- 2017Integrated probabilistic modelling of pitting and corrosion fatigue damage of subsea pipelines
- 2017Pitting degradation modelling of ocean steel structures using Bayesian networkcitations
- 2016Dynamic risk-based maintenance for offshore processing facilitycitations
- 2016Reliability assessment of offshore asset under pitting corrosion using Bayesian Network
- 2016Reliability assessment of offshore asset under pitting corrosion using Bayesian Network
- 2015Modelling of pitting corrosion in marine and offshore steel structures - A technical reviewcitations
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article
Pitting corrosion modelling of X80 steel utilized in offshore petroleum pipelines
Abstract
<p>High strength steels such as X80 steels have recently been used more frequently in production of offshore structures. However, they may still be subject to degradation processes such as corrosion considering the conditions in marine environment. Pitting corrosion is a destructive form of corrosion which reduces the material resistance and may result in failure accidents with severe financial, human life and environmental consequences. The process of pitting corrosion is inconsistent and largely stochastic being influenced by a number of parameters with a high level of uncertainty. This makes it very difficult to predict corrosion in terms of its initiation time and spatial behavior. Therefore, it is vital to investigate pitting corrosion phenomena in offshore structures using a probabilistic approach for the assessment of structural reliability and operational safety. In this study, an in-situ experiment has been conducted on X80 steel in an NaCl solution in a laboratory environment to observe the generation and growth of corrosion pits. A probabilistic model based on Hierarchical Bayesian Approach (HBA) is developed for predicting the pitting corrosion growth rate using experimental results. In order to model the process more realistically, the proposed methodology considers the degradation process to be consisting of the time needed for pit initiation and propagation. The results indicate that the proposed methodology is capable of predicting the time required to reach a specific pit size. The methodology developed in this study can be applied to estimate the remaining useful life of subsea structures.</p>