Critical review on data-driven approaches for learning from accidents: comparative analysis and future research

Y Niu, Y Fan, X Ju - Safety science, 2024 - Elsevier
Data-driven intelligent technologies are promoting a disruptive digital transformation of
human society. Industrial accident prevention is also amid this change. Although many …

Analysis of machine learning models and data sources to forecast burst pressure of petroleum corroded pipelines: A comprehensive review

AA Soomro, AA Mokhtar, HB Hussin, N Lashari… - Engineering Failure …, 2024 - Elsevier
A comprehensive evaluation of the integrity of oil and gas pipelines subjected to corrosion
defect is required for forecasting health & safety actions. If corrosion is ignored, it may have …

A Bayesian approach to assess under-deposit corrosion in oil and gas pipelines

U Dao, R Yarveisy, S Anwar, F Khan, Y Zhang… - Process Safety and …, 2023 - Elsevier
Under-deposit corrosion (UDC) and microbiologically influenced corrosion under deposits
(UD-MIC) have increasingly been identified as severe forms of localized corrosion …

Maintenance strategy optimization of pipeline system with multi-stage corrosion defects based on heuristically genetic algorithm

M **e, J Zhao, X Pei - Process Safety and Environmental Protection, 2023 - Elsevier
To ensure the high reliability of the pipeline system, it is necessary to take group
maintenance actions. This work proposes an optimal group maintenance approach based …

Long-Term Survival of Toxoplasma gondii Sporulated Oocysts in Seawater

DS Lindsay, JP Dubey - Journal of Parasitology, 2009 - meridian.allenpress.com
Toxoplasma gondii is now recognized as an important pathogen in costal marine mammals.
Oocysts from cat feces are believed to be washed into seawater and serve as a source of …

A unified causation prediction model for aboveground onshore oil and refined product pipeline incidents using artificial neural network

P Kumari, Q Wang, F Khan, JSI Kwon - Chemical Engineering Research …, 2022 - Elsevier
Aboveground onshore oil and refined product pipeline incidents pose significant hazards to
people, property, and environment. Therefore, several data-driven models have been …

A direct transfer entropy-based multiblock Bayesian network for root cause diagnosis of process faults

P Kumari, Q Wang, F Khan… - Industrial & Engineering …, 2022 - ACS Publications
In chemical processes, Bayesian network (BN)-based approaches have been extensively
applied for process fault diagnosis. Generally, BN is learned using score and search …

A novel pipeline age evaluation: considering overall condition index and neural network based on measured data

H Noroznia, M Gandomkar, J Nikoukar… - Machine Learning and …, 2023 - mdpi.com
Today, the chemical corrosion of metals is one of the main problems of large productions,
especially in the oil and gas industries. Due to massive downtime connected to corrosion …

Rapid failure risk analysis of corroded gas pipelines using machine learning

R **ao, T Zayed, M Meguid, L Sushama - Ocean Engineering, 2024 - Elsevier
Pipelines are critical to the urban development of modern cities, closely entwined with both
production and residential activities. This study introduces a rapid and efficient methodology …

[HTML][HTML] Pipeline corrosion prediction and uncertainty analysis with an ensemble Bayesian neural network approach

B Cui, H Wang - Process Safety and Environmental Protection, 2024 - Elsevier
This study developed an ensemble Bayesian Neural Network (BNN) model for pipeline
corrosion prediction incorporating uncertainty analysis. The performance of the proposed …