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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:

A comprehensive review of digital twin — part 1: modeling and twinning enabling technologies
Adam Thelen, Xiaoge Zhang, Olga Fink, et al.
Structural and Multidisciplinary Optimization (2022) Vol. 65, Iss. 12
Open Access | Times Cited: 182

Showing 1-25 of 182 citing articles:

A comprehensive review of digital twin—part 2: roles of uncertainty quantification and optimization, a battery digital twin, and perspectives
Adam Thelen, Xiaoge Zhang, Olga Fink, et al.
Structural and Multidisciplinary Optimization (2022) Vol. 66, Iss. 1
Closed Access | Times Cited: 76
Uncertainty quantification in machine learning for engineering design and health prognostics: A tutorial
Venkat Pavan Nemani, Luca Biggio, Xun Huan, et al.
Mechanical Systems and Signal Processing (2023) Vol. 205, pp. 110796-110796
Open Access | Times Cited: 75
Digital twin of electric vehicle battery systems: Comprehensive review of the use cases, requirements, and platforms
Farshid Naseri, Santiago Gil, C. Barbu, et al.
Renewable and Sustainable Energy Reviews (2023) Vol. 179, pp. 113280-113280
Open Access | Times Cited: 71
Digital Twins in the Construction Industry: A Comprehensive Review of Current Implementations, Enabling Technologies, and Future Directions
Hossein Omrany, Karam M. Al-Obaidi, A. Sakeer Husain, et al.
Sustainability (2023) Vol. 15, Iss. 14, pp. 10908-10908
Open Access | Times Cited: 61
A digital twin framework for civil engineering structures
Matteo Torzoni, Marco Tezzele, Stefano Mariani, et al.
Computer Methods in Applied Mechanics and Engineering (2023) Vol. 418, pp. 116584-116584
Open Access | Times Cited: 49
Preserving our heritage: A photogrammetry-based digital twin framework for monitoring deteriorations of historic structures
Xiangxiong Kong, Ronny Garrett Hucks
Automation in Construction (2023) Vol. 152, pp. 104928-104928
Open Access | Times Cited: 46
Exploring the Intersection of Metaverse, Digital Twins, and Artificial Intelligence in Training and Maintenance
Monica Bordegoni, Francesco Ferrise
Journal of Computing and Information Science in Engineering (2023) Vol. 23, Iss. 6
Closed Access | Times Cited: 40
A Systematic Literature Review of Digital Twin Research for Healthcare Systems: Research Trends, Gaps, and Realization Challenges
Md Doulotuzzaman Xames, Taylan G. Topcu
IEEE Access (2024) Vol. 12, pp. 4099-4126
Open Access | Times Cited: 26
Digital twins in safety analysis, risk assessment and emergency management
Enrico Zio, Leonardo Miqueles
Reliability Engineering & System Safety (2024) Vol. 246, pp. 110040-110040
Open Access | Times Cited: 24
Digital twins-boosted intelligent maintenance of ageing bridge hangers exposed to coupled corrosion–fatigue deterioration
Junlin Heng, You Dong, Li Lai, et al.
Automation in Construction (2024) Vol. 167, pp. 105697-105697
Closed Access | Times Cited: 14
An optimization-centric review on integrating artificial intelligence and digital twin technologies in manufacturing
Vispi Karkaria, Ying-Kuan Tsai, Yi-Ping Chen, et al.
Engineering Optimization (2025), pp. 1-47
Open Access | Times Cited: 1
Physics-informed machine learning in prognostics and health management: State of the art and challenges
Weikun Deng, Khanh T.P. Nguyen, Kamal Medjaher, et al.
Applied Mathematical Modelling (2023) Vol. 124, pp. 325-352
Open Access | Times Cited: 35
Hydrogenerator early fault detection: Sparse Dictionary Learning jointly with the Variational Autoencoder
Ryad Zemouri, Rony Ibrahim, Antoine Tahan
Engineering Applications of Artificial Intelligence (2023) Vol. 120, pp. 105859-105859
Closed Access | Times Cited: 22
A Physics-Constrained Bayesian neural network for battery remaining useful life prediction
David Najera-Flores, Zhen Hu, Mayank Chadha, et al.
Applied Mathematical Modelling (2023) Vol. 122, pp. 42-59
Open Access | Times Cited: 22
Digital twins for aircraft maintenance and operation: A systematic literature review and an IoT-enabled modular architecture
Giovanni Marco Bisanti, Luca Mainetti, Teodoro Montanaro, et al.
Internet of Things (2023) Vol. 24, pp. 100991-100991
Open Access | Times Cited: 22
Toward intelligent food drying: Integrating artificial intelligence into drying systems
Seyed-Hassan Miraei Ashtiani, Alex Martynenko
Drying Technology (2024) Vol. 42, Iss. 8, pp. 1240-1269
Closed Access | Times Cited: 12
Prognostics and health management for predictive maintenance: A review
Chao Huang, Siqi Bu, Hiu Hung Lee, et al.
Journal of Manufacturing Systems (2024) Vol. 75, pp. 78-101
Closed Access | Times Cited: 12
Probabilistic machine learning for battery health diagnostics and prognostics—review and perspectives
Adam Thelen, Xun Huan, Noah H. Paulson, et al.
npj Materials Sustainability (2024) Vol. 2, Iss. 1
Open Access | Times Cited: 11
Research on multi-digital twin and its application in wind power forecasting
Shuwei Liu, Jianyan Tian, Zhengxiong Ji, et al.
Energy (2024) Vol. 292, pp. 130269-130269
Closed Access | Times Cited: 10
A digital twin to overcome long-time challenges in photovoltaics
Larry Lüer, Ian Marius Peters, Ana‐Sunčana Smith, et al.
Joule (2024)
Open Access | Times Cited: 9
A review on computer model calibration
Chih‐Li Sung, Rui Tuo
Wiley Interdisciplinary Reviews Computational Statistics (2024) Vol. 16, Iss. 1
Closed Access | Times Cited: 9
Making knowledge graphs work for smart manufacturing: Research topics, applications and prospects
Y Wan, Ying Liu, Zhenyuan Chen, et al.
Journal of Manufacturing Systems (2024) Vol. 76, pp. 103-132
Open Access | Times Cited: 8
Application of physics-informed machine learning for excavator working resistance modeling
Shijiang Li, Shaojie Wang, Chen Xiu, et al.
Mechanical Systems and Signal Processing (2024) Vol. 209, pp. 111117-111117
Closed Access | Times Cited: 7
Advancing Electric Vehicle Battery Analysis With Digital Twins in Intelligent Transportation Systems
Irum Saba, M. Habib Ullah, Muhammad Tariq
IEEE Transactions on Intelligent Transportation Systems (2024) Vol. 25, Iss. 9, pp. 12141-12150
Closed Access | Times Cited: 7
A structure-preserving machine learning framework for accurate prediction of structural dynamics for systems with isolated nonlinearities
David Najera-Flores, D. Dane Quinn, Anthony Garland, et al.
Mechanical Systems and Signal Processing (2024) Vol. 213, pp. 111340-111340
Open Access | Times Cited: 7
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