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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Detection of faults in subsea pipelines by flow monitoring with regression supervised machine learning
Daniel Eastvedt, G.F. Naterer, Xili Duan
Process Safety and Environmental Protection (2022) Vol. 161, pp. 409-420
Closed Access | Times Cited: 42

Showing 1-25 of 42 citing articles:

Predictive deep learning for pitting corrosion modeling in buried transmission pipelines
Behnam Akhlaghi, Hassan Mesghali, Majid Ehteshami, et al.
Process Safety and Environmental Protection (2023) Vol. 174, pp. 320-327
Open Access | Times Cited: 40
Review of interpretable machine learning for process industries
A. Carter, Syed Imtiaz, G.F. Naterer
Process Safety and Environmental Protection (2022) Vol. 170, pp. 647-659
Closed Access | Times Cited: 48
Prediction of oil and gas pipeline failures through machine learning approaches: A systematic review
Abdulnaser M. Al-Sabaeei, Hitham Alhussian, Said Jadid Abdulkadir, et al.
Energy Reports (2023) Vol. 10, pp. 1313-1338
Open Access | Times Cited: 31
Performance analysis of various machine learning algorithms for CO2 leak prediction and characterization in geo-sequestration injection wells
Saeed Harati, Sina Rezaei Gomari, Mohammad Azizur Rahman, et al.
Process Safety and Environmental Protection (2024) Vol. 183, pp. 99-110
Open Access | Times Cited: 12
Deeppipe: Theory-guided neural network method for predicting burst pressure of corroded pipelines
Yunlu Ma, Jianqin Zheng, Yongtu Liang, et al.
Process Safety and Environmental Protection (2022) Vol. 162, pp. 595-609
Closed Access | Times Cited: 32
Solid oxide fuel cells for shipping: A machine learning model for early detection of hazardous system deviations
Tomaso Vairo, Davide Cademartori, Davide Clematis, et al.
Process Safety and Environmental Protection (2023) Vol. 172, pp. 184-194
Open Access | Times Cited: 20
Critical review on data-driven approaches for learning from accidents: Comparative analysis and future research
Yi Niu, Yunxiao Fan, Xing Ju
Safety Science (2023) Vol. 171, pp. 106381-106381
Closed Access | Times Cited: 18
A stochastic model for RUL prediction of subsea pipeline subject to corrosion-fatigue degradation
Ziyue Han, Xinhong Li, Guoming Chen
Process Safety and Environmental Protection (2023) Vol. 178, pp. 739-747
Closed Access | Times Cited: 16
Enhancing pipeline integrity: a comprehensive review of deep learning-enabled finite element analysis for stress corrosion cracking prediction
Umair Sarwar, Ainul Akmar Mokhtar, Masdi Muhammad, et al.
Engineering Applications of Computational Fluid Mechanics (2024) Vol. 18, Iss. 1
Open Access | Times Cited: 6
A data-driven methodology for predicting residual strength of subsea pipeline with double corrosion defects
Xinhong Li, Ruichao Jia, Renren Zhang
Ocean Engineering (2023) Vol. 279, pp. 114530-114530
Closed Access | Times Cited: 15
Data-driven predictive prognostic model for power batteries based on machine learning
Jinxi Dong, Zhaosheng Yu, Xikui Zhang, et al.
Process Safety and Environmental Protection (2023) Vol. 172, pp. 894-907
Closed Access | Times Cited: 13
Prediction of Water Leakage in Pipeline Networks Using Graph Convolutional Network Method
Ersin Şahin, Hüseyin Yüce
Applied Sciences (2023) Vol. 13, Iss. 13, pp. 7427-7427
Open Access | Times Cited: 13
Research on remaining bearing capacity evaluation method for corroded pipelines with complex shaped defects
LI Song-ling, Zhiwei Zhang, Hongliang Qian, et al.
Ocean Engineering (2024) Vol. 296, pp. 116805-116805
Closed Access | Times Cited: 4
Analysis of connection fault and service maintenance strategy for subsea horizontal clamp connector
Weifeng Liu, Feihong Yun, Ming Ju, et al.
Ocean Engineering (2024) Vol. 307, pp. 118257-118257
Closed Access | Times Cited: 4
Application of machine learning to leakage detection of fluid pipelines in recent years: A review and prospect
Jianwu Chen, Xiao Wu, Zhibo Jiang, et al.
Measurement (2025), pp. 116857-116857
Closed Access
Innovative prognostic methodology for pipe defect detection leveraging acoustic emissions analysis and computational modeling integration
Ahmad Braydi, Pascal Fossat, Mohsen Ardabilian, et al.
Applied Ocean Research (2025), pp. 104521-104521
Open Access
Digital twin for leak detection and fault diagnostics in gas pipelines: A systematic review, model development, and case study
Wahib A. Al‐Ammari, Ahmad K. Sleiti, Mohammad Azizur Rahman, et al.
Alexandria Engineering Journal (2025) Vol. 123, pp. 91-111
Closed Access
Maintenance strategy optimization of pipeline system with multi-stage corrosion defects based on heuristically genetic algorithm
Mingjiang Xie, Jianli Zhao, Xianjun Pei
Process Safety and Environmental Protection (2022) Vol. 170, pp. 553-572
Closed Access | Times Cited: 20
Pipeline damage identification in nuclear industry using a particle swarm optimization-enhanced machine learning approach
Qi Jiang, Wenzhong Qu, Xiao Li
Engineering Applications of Artificial Intelligence (2024) Vol. 133, pp. 108467-108467
Closed Access | Times Cited: 4
Real-time monitoring of CO2 transport pipelines using deep learning
Juhyun Kim, Hyunjee Yoon, Saebom Hwang, et al.
Process Safety and Environmental Protection (2023) Vol. 181, pp. 480-492
Open Access | Times Cited: 7
Enhancing Safety in Geological Carbon Sequestration: Supervised Machine Learning for Early Detection and Mitigation of CO2 Leakage in Injection Wells
Saeed Harati, Sina Rezaei Gomari, Mohammad Azizur Rahman, et al.
All Days (2024)
Closed Access | Times Cited: 2
Data augmentation using SMOTE technique: Application for prediction of burst pressure of hydrocarbons pipeline using supervised machine learning models
Afzal Ahmed Soomro, Ainul Akmar Mokhtar, Masdi Muhammad, et al.
Results in Engineering (2024), pp. 103233-103233
Open Access | Times Cited: 2
Multivariate state estimation-based condition monitoring of slurry circulating pumps for wet flue gas desulfurization of power plants
Dawei Duan, Shangbo Han, Zhongcheng Wang, et al.
Engineering Failure Analysis (2024) Vol. 159, pp. 108099-108099
Closed Access | Times Cited: 1
Enhanced Gas Pipeline Multiple Leak Detection Using Artificial Neural Networks in Complex Multiphase Flow Conditions
Wahib A. Al‐Ammari, Ahmad K. Sleiti
(2024)
Open Access | Times Cited: 1
A study of neural network-based evaluation methods for pipelines with multiple corrosive regions
Zhiwei Zhang, LI Song-ling, Huajie Wang, et al.
Reliability Engineering & System Safety (2024), pp. 110507-110507
Closed Access | Times Cited: 1
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