Probabilistic Assessment of Complex Corrosion in Pipelines Considering River-Bottom Profile Information DOI

Renato Siqueira Motta,

Adriano Dayvson Marques Ferreira,

Silvana Afonso da Silva

и другие.

Опубликована: Янв. 1, 2024

This study addresses pipeline failure, a critical issue primarily attributed to corrosion, with far-reaching consequences in social, economic, and environmental domains. Traditional assessment methods, while simple fast, often yield conservative results. Existing approaches typically overlook inherent uncertainties failure pressure prediction, emphasizing safety factors. research focuses on the probability of complex corrosion profiles characterized by river-bottom (RBPs), aiming bridge gap literature. The employs traditional Monte Carlo (MC) an proposed modified first-order reliability method (FORM) assess intricate defects, utilizing Effective Area within function. To manage computational demands, FORM is favored for its efficiency requiring fewer evaluations. Despite challenges gradient computation using Level-2 methods like Area, novel procedure efficiently accurately determining FP gradients algorithm. Results show that converges 15 iterations all 11 cases, presenting rapid precise alternative Level-1 methods. approach offers valuable contribution computing as demonstrated this comparative purposes.

Язык: Английский

Structural health monitoring of oil and gas pipelines: Developments, applications and future directions DOI
Yihuan Wang,

Shiyi Zhu,

Bohong Wang

и другие.

Ocean Engineering, Год журнала: 2024, Номер 308, С. 118293 - 118293

Опубликована: Июнь 5, 2024

Язык: Английский

Процитировано

13

An interpretable machine learning-based pitting corrosion depth prediction model for steel drinking water pipelines DOI
Taehyeon Kim, Kibum Kim, Jinseok Hyung

и другие.

Process Safety and Environmental Protection, Год журнала: 2024, Номер 190, С. 571 - 585

Опубликована: Авг. 10, 2024

Язык: Английский

Процитировано

4

Machine learning-aided risk-based inspection strategy for hydrogen technologies DOI Creative Commons
Alessandro Campari, Chiara Vianello, Federico Ustolin

и другие.

Process Safety and Environmental Protection, Год журнала: 2024, Номер unknown

Опубликована: Сен. 1, 2024

Язык: Английский

Процитировано

4

An efficient probabilistic framework for estimating the corrosion state of offshore pipelines: A case study DOI
Zhi Li, Yanbo Niu, Xiaoguang Zhou

и другие.

Ocean Engineering, Год журнала: 2025, Номер 319, С. 120265 - 120265

Опубликована: Янв. 6, 2025

Язык: Английский

Процитировано

0

Material selection of titanium alloy pipelines considering multi-criteria in an acidic environment based on analytic hierarchy process DOI

Dezhi Zeng,

Jiancheng Luo, Chunping Yu

и другие.

International Journal of Pressure Vessels and Piping, Год журнала: 2025, Номер unknown, С. 105461 - 105461

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

0

Multiparametric Resilience Assessment of Chemical Process Systems Incorporating Process Dynamics and Independent Protection Layers DOI
Hao Sun, Meng Qi, Ming Yang

и другие.

Process Safety and Environmental Protection, Год журнала: 2025, Номер unknown, С. 107018 - 107018

Опубликована: Март 1, 2025

Язык: Английский

Процитировано

0

Machine learning-based maximum pipeline pitting corrosion depth prediction using hybrid FVIM-BNN-XGB model DOI
Shuo Sun, Zhendong Cui, Dong Zhang

и другие.

Engineering Failure Analysis, Год журнала: 2025, Номер unknown, С. 109603 - 109603

Опубликована: Апрель 1, 2025

Язык: Английский

Процитировано

0

A resilience-driven emergency maintenance operation scheme optimization method based on risk DOI
Yanping Zhang, Baoping Cai, Salim Ahmed

и другие.

Reliability Engineering & System Safety, Год журнала: 2024, Номер 254, С. 110630 - 110630

Опубликована: Ноя. 4, 2024

Язык: Английский

Процитировано

2

Probabilistic assessment of complex corrosion in pipelines considering River-Bottom Profile information DOI
Renato de Siqueira Motta, Adriano Dayvson Marques Ferreira, Silvana M. B. Afonso

и другие.

Engineering Failure Analysis, Год журнала: 2024, Номер 165, С. 108801 - 108801

Опубликована: Авг. 23, 2024

Язык: Английский

Процитировано

1

A Bibliometric Analysis on the Safety of Oil and Gas Pipelines: Research Trends and Perspectives DOI
Lihang Wang, Hao Zhou

Journal of Pipeline Systems Engineering and Practice, Год журнала: 2024, Номер 16(1)

Опубликована: Дек. 5, 2024

Язык: Английский

Процитировано

1