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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:

Digital twinning of self-sensing structures using the statistical finite element method
Eky Febrianto, Liam Butler, Mark Girolami, et al.
Data-Centric Engineering (2022) Vol. 3
Open Access | Times Cited: 36

Showing 1-25 of 36 citing articles:

Bridge management through digital twin-based anomaly detection systems: A systematic review
Alejandro Jiménez Ríos, Vagelis Plevris, María Nogal
Frontiers in Built Environment (2023) Vol. 9
Open Access | Times Cited: 40
A review on the applications of artificial neural network techniques for accelerating finite element analysis in the civil engineering domain
Sanduni Jayasinghe, Mojtaba Mahmoodian, Azadeh Alavi, et al.
Computers & Structures (2025) Vol. 310, pp. 107698-107698
Open Access | Times Cited: 1
Prescriptive maintenance of prestressed concrete bridges considering digital twin and key performance indicator
Chi-Ho Jeon, Chang-Su Shim, Yanghee Lee, et al.
Engineering Structures (2023) Vol. 302, pp. 117383-117383
Closed Access | Times Cited: 22
Revamping structural health monitoring of advanced rail transit systems: A paradigmatic shift from digital shadows to digital twins
Mujib Olamide Adeagbo, Sumei Wang, Yi‐Qing Ni
Advanced Engineering Informatics (2024) Vol. 61, pp. 102450-102450
Open Access | Times Cited: 12
Recent progress and future outlook of digital twins in structural health monitoring of civil infrastructure
M. Sakr, Ayan Sadhu
Smart Materials and Structures (2024) Vol. 33, Iss. 3, pp. 033001-033001
Open Access | Times Cited: 10
Towards AI-assisted digital twins for smart railways: preliminary guideline and reference architecture
Lorenzo De Donato, Ruth Dirnfeld, Alessandra Somma, et al.
Journal of Reliable Intelligent Environments (2023) Vol. 9, Iss. 3, pp. 303-317
Open Access | Times Cited: 17
Instance segmentation of reinforced concrete bridge point clouds with transformers trained exclusively on synthetic data
Asad Ur Rahman, Vedhus Hoskere
Automation in Construction (2025) Vol. 173, pp. 106067-106067
Closed Access
Probabilistic learning from real-world observations of systems with unknown inputs for model-form UQ and digital twinning
Jenmy Zimi Zhang, Akmal Bakar, Adrian Humphry, et al.
Computer Methods in Applied Mechanics and Engineering (2025), pp. 117863-117863
Closed Access
Bridge Health Monitoring: A Review of Utilizing the Internet of Things, Digital Twin, and Advanced Technologies
Hamed Hasani, Francesco Freddi
Springer tracts in civil engineering (2025), pp. 423-447
Closed Access
Fully probabilistic deep models for forward and inverse problems in parametric PDEs
Arnaud Vadeboncoeur, Ömer Deniz Akyıldız, Ieva Kazlauskaite, et al.
Journal of Computational Physics (2023) Vol. 491, pp. 112369-112369
Open Access | Times Cited: 12
Integrating AI and DTs: challenges and opportunities in railway maintenance application and beyond
Ruth Dirnfeld, Lorenzo De Donato, Alessandra Somma, et al.
SIMULATION (2024) Vol. 100, Iss. 9, pp. 903-917
Closed Access | Times Cited: 4
Recent advances in structural health diagnosis: a machine learning perspective
Yuequan Bao, Huabin Sun, Yang Xu, et al.
Advances in Bridge Engineering (2025) Vol. 6, Iss. 1
Open Access
Digital Twin for Railway: A Comprehensive Survey
Sara Ghaboura, Rahatara Ferdousi, Fedwa Laamarti, et al.
IEEE Access (2023) Vol. 11, pp. 120237-120257
Open Access | Times Cited: 11
Revolutionizing Structural Health Monitoring and Preserving Cultural Heritage via Digital Twins
Danilo Maurmo, Tommaso Ruga, Ester Zumpano, et al.
(2024), pp. 92-97
Closed Access | Times Cited: 3
Inferring displacement fields from sparse measurements using the statistical finite element method
Vahab B. Narouie, Henning Wessels, Ulrich Römer
Mechanical Systems and Signal Processing (2023) Vol. 200, pp. 110574-110574
Open Access | Times Cited: 7
Research progress and prospect of digital twin in bridge engineering
Yuanliang Yang, Yichen Zhu, C.S. Cai
Advances in Structural Engineering (2023) Vol. 27, Iss. 2, pp. 333-352
Closed Access | Times Cited: 7
Approach Towards the Development of Digital Twin for Structural Health Monitoring of Civil Infrastructure: A Comprehensive Review
Zhiyan Sun, Sanduni Jayasinghe, Amir Sidiq, et al.
Sensors (2024) Vol. 25, Iss. 1, pp. 59-59
Open Access | Times Cited: 2
The Potential for Digital Twin Applications in Railway Infrastructure Management
Gerhardus Christiaan Doubell, Karel Kruger, Anton Basson, et al.
Lecture notes in mechanical engineering (2022), pp. 241-249
Closed Access | Times Cited: 11
Bayesian model calibration and damage detection for a digital twin of a bridge demonstrator
Thomas Titscher, Thomas van Dijk, Daniel Kadoke, et al.
Engineering Reports (2023) Vol. 5, Iss. 11
Open Access | Times Cited: 6
A brief note on building augmented reality models for scientific visualization
Mrudang Mathur, Josef M. Brozovich, Manuel K. Rausch
Finite Elements in Analysis and Design (2022) Vol. 213, pp. 103851-103851
Open Access | Times Cited: 10
Stochastic PDE representation of random fields for large-scale Gaussian process regression and statistical finite element analysis
Kim Jie Koh, Fehmi Cirak
Computer Methods in Applied Mechanics and Engineering (2023) Vol. 417, pp. 116358-116358
Open Access | Times Cited: 5
Digital Twins for Condition Assessment of Railway Infrastructures
Marcos Massao Futai, L. B. Machado, Ruan Richelly Santos, et al.
(2024), pp. 157-176
Closed Access | Times Cited: 1
Mitigating Measurement Inaccuracies in Digital Twins of Construction Machinery through Multi-Objective Optimization
Misganaw Abebe, Yonggeun Cho, Seung Chul Han, et al.
Sensors (2024) Vol. 24, Iss. 11, pp. 3347-3347
Open Access | Times Cited: 1
Assisting Load Rating Testing of Precast Reinforced Concrete Bridge Slab through Digital Twins and Field Monitoring Data
Li Ai, K C Laxman, Elhussien Elbatanouny, et al.
Journal of Testing and Evaluation (2024) Vol. 52, Iss. 4, pp. 1926-1938
Closed Access | Times Cited: 1
Advancements and applications of digital twin in the railway industry: a literature review
Dinesh Kushwaha, Ankit Kumar, S. P. Harsha
International Journal of Rail Transportation (2024), pp. 1-26
Closed Access | Times Cited: 1
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