Data modeling techniques for pipeline integrity assessment: A State-of-the-Art Survey

J Ling, K Feng, T Wang, M Liao… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Pipelines are economical and efficient modes of transporting oil and gas. Pipelines will
inevitably confront various risk factors throughout their lifespan, which could lead to defects …

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 …

Leveraging machine learning for pipeline condition assessment

H Lu, ZD Xu, X Zang, D Xi, T Iseley… - Journal of Pipeline …, 2023 - ascelibrary.org
Pipeline condition assessment is a cost-effective method to determine the status of pipeline
structure and predict failure probability. Although 100% inspection may not be feasible for …

Novel method for residual strength prediction of defective pipelines based on HTLBO-DELM model

X Miao, H Zhao - Reliability Engineering & System Safety, 2023 - Elsevier
Residual strength prediction of defective pipelines is critical to pipeline reliability
assessment, which can affect the remaining useful life of pipelines. In this paper, we propose …

A study on burst failure mechanism analysis and quantitative risk assessment of corroded pipelines with random pitting clusters

F Jiang, S Dong, E Zhao - Ocean Engineering, 2023 - Elsevier
Corrosion defect is the primary inducement for pipeline burst failures. Natural-occurred
defects appear in the form of pitting clusters, exhibiting randomness and irregularity in local …

M2BIST-SPNet: RUL prediction for railway signaling electromechanical devices

X Hu, L Tan, T Tang - The Journal of Supercomputing, 2024 - Springer
Railway signaling electromechanical devices (RSEDs) play a pivotal role in the railway
industry. Normal wear and tear of these devices occur during day-and-night operation and …

A novel multi-scale competitive network for fault diagnosis in rotating machinery

Z Huang, X Zhao - Engineering Applications of Artificial Intelligence, 2024 - Elsevier
Bearing fault diagnosis plays a vital role in ensuring the safe and reliable operation of
rotating machinery. The diagnostic process is more difficult when the fault is in its early …

Theory and machine learning modeling for burst pressure estimation of pipeline with multipoint corrosion

H Lu, H Peng, ZD Xu, G Qin, M Azimi… - Journal of Pipeline …, 2023 - ascelibrary.org
Burst pressure is an essential parameter to measure the residual bearing capacity of
pipelines with corrosion defects. Accurate prediction of burst pressure is beneficial to …

Environmental commitments and Innovation in China's corporate landscape: An analysis of ESG governance strategies

LK David, J Wang, V Angel, M Luo - Journal of Environmental Management, 2024 - Elsevier
This study delves into the nexus between corporate ESG commitments—with a spotlight on
environmental considerations—and innovation trends in China's corporate sector …

A novel neural network-based framework to estimate oil and gas pipelines life with missing input parameters

NB Shaik, K Jongkittinarukorn, W Benjapolakul… - Scientific Reports, 2024 - nature.com
Dry gas pipelines can encounter various operational, technical, and environmental issues,
such as corrosion, leaks, spills, restrictions, and cyber threats. To address these difficulties …