Advances in corrosion growth modeling for oil and gas pipelines: A review

Ma, Haonan; Zhang, Weidong; Wang, Yao; Ai, Yibo; Zheng, Wenyue

doi:10.1016/j.psep.2022.12.054

Cited by 49 publications

(11 citation statements)

References 137 publications

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“…The future consideration of the prognosis of corrosion risk in process safety relates to corrosion modeling. Literature is full of developing corrosion models, especially during the last three years (2021 -2023) [40,[44][45][46][47]. This singularity (explosion of research works and information) occurred owing to the use of Artificial Intelligence (AI) methods [48][49][50][51][52][53].…”

Section: Corrosion Models For the Process Safetymentioning

confidence: 99%

Corrosion Risk for Process Safety in the Chemical Industry

Groysman

2024

Afinidad

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The aim of this work is to analyze how corrosion risk management influences process safety. Both issues occupy an important niche in the chemical industry. Corrosion risk management includes identifying, analyzing, assessing, and managing corrosion hazards. Process safety is a discipline that focuses on preventing fires, explosions, and accidental releases at chemical process facilities. Corrosion can cause all these detrimental events. There is much literature about both topics, corrosion risk, and process safety, separately, but there are nearly no research works concerning intersection and influence. The level of corrosion failure and its consequences, defining corrosion risk, may be different: the leak of crude oil, natural gas, water, liquid and gaseous hazardous chemicals, fire, explosion, damages, deterioration of the environment, injuries, and death of people and animals. Due to the biological and psychological properties of human nature, we are unlikely to exclude human mistakes. We should pay significant attention to education, dissemination of information, knowledge transfer, collaboration, and communication. Correct corrosion risk management gives rise to the improvement of process safety at stages of design, fabrication, implementation, erection, service, and maintenance of equipment and constructions in the chemical industry. For this realization, specific corrosion mitigation strategies and technologies are described. They are successfully implemented in the chemical industry. It shows how corrosion management and process safety management can be better integrated into practice. The future consideration of the prognosis of corrosion risk with process safety is connected with corrosion modeling. Limitations and challenges of such a forecast are discussed too. Special educational and training programs are developed to help engineers, scientists, professionals, students, and managers learn about corrosion science and engineering

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Section: Corrosion Models For the Process Safetymentioning

confidence: 99%

Corrosion Risk for Process Safety in the Chemical Industry

Groysman

2024

Afinidad

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“…4,5 Widespread attention has been focused on preventing metal corrosion and enhancing the corrosion resistance of metals in marine atmospheric and splash zones. 6,7 Corrosion protection methods primarily include the utilization of coatings, cathodic protection (CP), and corrosion inhibitors. 8−11 Coatings are prone to degradation over time, and their performance is often below standard values after a period of use.…”

Section: Introductionmentioning

confidence: 99%

“…These conditions can result in severe corrosion of facilities and equipment. − Corrosion will shorten the service life of the equipment and threaten personal safety, leading to substantial economic losses. Additionally, it causes significant pollution to the environment and disrupts the ecological balance. , Widespread attention has been focused on preventing metal corrosion and enhancing the corrosion resistance of metals in marine atmospheric and splash zones. , …”

Section: Introductionmentioning

confidence: 99%

Review of TiO₂-Based Heterojunction Coatings in Photocathodic Protection

Xu,

Li,

Wen

et al. 2024

ACS Appl. Nano Mater.

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Photocathodic protection coating is an emerging anticorrosion technology that combines the protective characteristics of coating and cathodic protection. TiO 2 is stable and easy to prepare; however, it suffers from a low sunlight utilization rate and low photoelectric conversion efficiency. The construction of TiO 2 -based heterojunction coatings provides an effective solution to these challenges. This work summarizes the synthesis methods of TiO 2based heterojunction coatings, explores the charge-transfer mechanisms associated with various types of heterojunction coatings (e.g., type II heterojunction, p−n junction, Schottky junction, and Z-scheme heterojunction), and reviews the characterization methods used for heterojunction analysis. Finally, the application prospects and future research directions of TiO 2 -based heterojunction coatings are proposed. This study will help researchers understand the fabrication process and application of TiO 2 -based heterojunction coatings in photocathodic protection.

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“…The corrosion growth model can assess accurately the corrosion condition of buried pipelines, providing a scientific basis for pipeline integrity management [ 7 , 8 ]. In the framework of Industry 4.0, multiple systems that involve monitoring operations, managing risks, and maintaining and inspecting oil and gas pipelines are being extensively digitized [ 9 ]. This advancement facilitates rapid expansion and application of data-driven models for predicting corrosion damage in pipelines [ 10 ].…”

Section: Introductionmentioning

confidence: 99%

Data Augmentation of a Corrosion Dataset for Defect Growth Prediction of Pipelines Using Conditional Tabular Generative Adversarial Networks

Ma,

Geng,

Wang

et al. 2024

Materials

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Due to corrosion characteristics, there are data scarcity and uneven distribution in corrosion datasets, and collecting high-quality data is time-consuming and sometimes difficult. Therefore, this work introduces a novel data augmentation strategy using a conditional tabular generative adversarial network (CTGAN) for enhancing corrosion datasets of pipelines. Firstly, the corrosion dataset is subjected to data cleaning and variable correlation analysis. The CTGAN is then used to generate external environmental factors as input variables for corrosion growth prediction, and a hybrid model based on machine learning is employed to generate corrosion depth as an output variable. The fake data are merged with the original data to form the synthetic dataset. Finally, the proposed data augmentation strategy is verified by analyzing the synthetic dataset using different visualization methods and evaluation indicators. The results show that the synthetic and original datasets have similar distributions, and the data augmentation strategy can learn the distribution of real corrosion data and sample fake data that are highly similar to the real data. Predictive models trained on the synthetic dataset perform better than predictive models trained using only the original dataset. In comparative tests, the proposed strategy outperformed other data generation methods.

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Advances in corrosion growth modeling for oil and gas pipelines: A review

Cited by 49 publications

References 137 publications

Corrosion Risk for Process Safety in the Chemical Industry

Corrosion Risk for Process Safety in the Chemical Industry

Review of TiO₂-Based Heterojunction Coatings in Photocathodic Protection

Data Augmentation of a Corrosion Dataset for Defect Growth Prediction of Pipelines Using Conditional Tabular Generative Adversarial Networks

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Advances in corrosion growth modeling for oil and gas pipelines: A review

Cited by 49 publications

References 137 publications

Corrosion Risk for Process Safety in the Chemical Industry

Corrosion Risk for Process Safety in the Chemical Industry

Review of TiO2-Based Heterojunction Coatings in Photocathodic Protection

Data Augmentation of a Corrosion Dataset for Defect Growth Prediction of Pipelines Using Conditional Tabular Generative Adversarial Networks

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Product

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Review of TiO₂-Based Heterojunction Coatings in Photocathodic Protection