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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:

Data-Enabled Physics-Informed Machine Learning for Reduced-Order Modeling Digital Twin: Application to Nuclear Reactor Physics
Helin Gong, Sibo Cheng, Zhang Chen, et al.
Nuclear Science and Engineering (2022) Vol. 196, Iss. 6, pp. 668-693
Open Access | Times Cited: 82

Showing 1-25 of 82 citing articles:

Machine Learning With Data Assimilation and Uncertainty Quantification for Dynamical Systems: A Review
Sibo Cheng, César Quilodrán-Casas, Said Ouala, et al.
IEEE/CAA Journal of Automatica Sinica (2023) Vol. 10, Iss. 6, pp. 1361-1387
Open Access | Times Cited: 120
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
Data-driven surrogate model with latent data assimilation: Application to wildfire forecasting
Sibo Cheng, I. Colin Prentice, Yuhan Huang, et al.
Journal of Computational Physics (2022) Vol. 464, pp. 111302-111302
Open Access | Times Cited: 71
A review of the application of artificial intelligence to nuclear reactors: Where we are and what's next
Qingyu Huang, Shinian Peng, Jian Deng, et al.
Heliyon (2023) Vol. 9, Iss. 3, pp. e13883-e13883
Open Access | Times Cited: 41
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
Methods for enabling real-time analysis in digital twins: A literature review
Mohammad Sadegh Es-haghi, Cosmin Anitescu, Timon Rabczuk
Computers & Structures (2024) Vol. 297, pp. 107342-107342
Open Access | Times Cited: 19
Predicting Neutron Flux Density Distribution in HTR-10 using U-Net Based on DEM-MC coupled Simulations
Qianye Yang, Nan Gui, Xingtuan Yang, et al.
Nuclear Engineering and Technology (2025), pp. 103425-103425
Open Access | Times Cited: 1
Generalised Latent Assimilation in Heterogeneous Reduced Spaces with Machine Learning Surrogate Models
Sibo Cheng, Jianhua Chen, Charitos Anastasiou, et al.
Journal of Scientific Computing (2022) Vol. 94, Iss. 1
Open Access | Times Cited: 58
Online autonomous calibration of digital twins using machine learning with application to nuclear power plants
Houde Song, Meiqi Song, Xiaojing Liu
Applied Energy (2022) Vol. 326, pp. 119995-119995
Closed Access | Times Cited: 51
An efficient digital twin based on machine learning SVD autoencoder and generalised latent assimilation for nuclear reactor physics
Helin Gong, Sibo Cheng, Zhang Chen, et al.
Annals of Nuclear Energy (2022) Vol. 179, pp. 109431-109431
Open Access | Times Cited: 47
Parameter Flexible Wildfire Prediction Using Machine Learning Techniques: Forward and Inverse Modelling
Sibo Cheng, Yufang Jin, Sandy P. Harrison, et al.
Remote Sensing (2022) Vol. 14, Iss. 13, pp. 3228-3228
Open Access | Times Cited: 44
Reduced-order digital twin and latent data assimilation for global wildfire prediction
Caili Zhong, Sibo Cheng, Matthew Kasoar, et al.
Natural hazards and earth system sciences (2023) Vol. 23, Iss. 5, pp. 1755-1768
Open Access | Times Cited: 27
Comparative study of data-driven and model-driven approaches in prediction of nuclear power plants operating parameters
Houde Song, Xiaojing Liu, Meiqi Song
Applied Energy (2023) Vol. 341, pp. 121077-121077
Closed Access | Times Cited: 24
Digital twins for the designs of systems: a perspective
Anton van Beek, Vispi Karkaria, Wei Chen
Structural and Multidisciplinary Optimization (2023) Vol. 66, Iss. 3
Closed Access | Times Cited: 19
Current status of digital twin architecture and application in nuclear energy field
Hu Mengyan, Xueyan Zhang, Peng Cuiting, et al.
Annals of Nuclear Energy (2024) Vol. 202, pp. 110491-110491
Closed Access | Times Cited: 6
Advanced manufacturing and digital twin technology for nuclear energy*
Kunal Mondal, Oscar Martínez, Prashant Jain
Frontiers in Energy Research (2024) Vol. 12
Open Access | Times Cited: 5
The time for revolutionizing small modular reactors: Cost reduction strategies from innovations in operation and maintenance
Ik Jae Jin, In Cheol Bang
Progress in Nuclear Energy (2024) Vol. 174, pp. 105288-105288
Closed Access | Times Cited: 5
Multi-domain encoder–decoder neural networks for latent data assimilation in dynamical systems
Sibo Cheng, Yilin Zhuang, Lyes Kahouadji, et al.
Computer Methods in Applied Mechanics and Engineering (2024) Vol. 430, pp. 117201-117201
Open Access | Times Cited: 5
A review on full-, zero-, and partial-knowledge based predictive models for industrial applications
Stefano Zampini, Guido Parodi, Luca Oneto, et al.
Information Fusion (2025), pp. 102996-102996
Open Access
A study on the development of digital model of digital twin in nuclear power plant based on a hybrid physics and data-driven approach
Fukun Chen, Qingyu Huang, Meiqi Song, et al.
Applied Thermal Engineering (2025), pp. 126289-126289
Closed Access
Parameter identification and state estimation for nuclear reactor operation digital twin
Helin Gong, Tao Zhu, Zhang Chen, et al.
Annals of Nuclear Energy (2022) Vol. 180, pp. 109497-109497
Closed Access | Times Cited: 24
An open time-series simulated dataset covering various accidents for nuclear power plants
Ben Qi, Xingyu Xiao, Jingang Liang, et al.
Scientific Data (2022) Vol. 9, Iss. 1
Open Access | Times Cited: 24
Efficient deep data assimilation with sparse observations and time-varying sensors
Sibo Cheng, Che Liu, Yike Guo, et al.
Journal of Computational Physics (2023) Vol. 496, pp. 112581-112581
Open Access | Times Cited: 15
An online learning method for constructing self-update digital twin model of power transformer temperature prediction
Tao Wu, Fan Yang, Umer Farooq, et al.
Applied Thermal Engineering (2023) Vol. 237, pp. 121728-121728
Closed Access | Times Cited: 13
Data-driven model order reduction for sensor positioning and indirect reconstruction with noisy data: Application to a Circulating Fuel Reactor
Antonio Cammi, Stefano Riva, Carolina Introini, et al.
Nuclear Engineering and Design (2024) Vol. 421, pp. 113105-113105
Open Access | Times Cited: 4
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