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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:

Three-dimensional deep learning-based reduced order model for unsteady flow dynamics with variable Reynolds number
Rachit Gupta, Rajeev K. Jaiman
Physics of Fluids (2022) Vol. 34, Iss. 3
Open Access | Times Cited: 45

Showing 1-25 of 45 citing articles:

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
Advancing fluid dynamics simulations: A comprehensive approach to optimizing physics-informed neural networks
Wen Zhou, Shuichiro Miwa, Koji Okamoto
Physics of Fluids (2024) Vol. 36, Iss. 1
Open Access | Times Cited: 13
A finite element-inspired hypergraph neural network: Application to fluid dynamics simulations
Rui Gao, Indu Kant Deo, Rajeev K. Jaiman
Journal of Computational Physics (2024) Vol. 504, pp. 112866-112866
Open Access | Times Cited: 9
Data-driven optimization of turbulent kinetic energy and tumble-y in combustion engines: A comparative study of machine learning models
Amirali Shateri, Zhiyin Yang, Yun Liu, et al.
Fuel (2025) Vol. 389, pp. 134590-134590
Open Access | Times Cited: 1
Deep learning-based reduced-order modeling for parameterized convection-dominated partial differential equations
Yu-shan Meng, Yuanhong Chen, Zhen Gao, et al.
Physics of Fluids (2025) Vol. 37, Iss. 2
Closed Access | Times Cited: 1
FastSVD-ML–ROM: A reduced-order modeling framework based on machine learning for real-time applications
G. I. Drakoulas, Theodore V. Gortsas, George C. Bourantas, et al.
Computer Methods in Applied Mechanics and Engineering (2023) Vol. 414, pp. 116155-116155
Open Access | Times Cited: 19
Predicting waves in fluids with deep neural network
Indu Kant Deo, Rajeev K. Jaiman
Physics of Fluids (2022) Vol. 34, Iss. 6
Open Access | Times Cited: 26
Deep neural network for learning wave scattering and interference of underwater acoustics
Wrik Mallik, Rajeev K. Jaiman, Jasmin Jelovica
Physics of Fluids (2024) Vol. 36, Iss. 1
Open Access | Times Cited: 5
A high-speed numerical simulation method for diverse boundary conditions for real time applications unleashing MeshGraphNet
Avishek Mukherjee, Surjya K. Pal, Debashish Chakravarty
Engineering Analysis with Boundary Elements (2025) Vol. 175, pp. 106204-106204
Closed Access
Predicting fluid–structure interaction with graph neural networks
Rui Gao, Rajeev K. Jaiman
Physics of Fluids (2024) Vol. 36, Iss. 1
Open Access | Times Cited: 4
Enhancing Computational Efficiency of Numerical Simulation for Subsurface Fluid-Induced Deformation Using Deep Learning Reduced Order Models
Elsa Ballini, A. Cominelli, L. Dovera, et al.
SPE Reservoir Simulation Conference (2025)
Closed Access
Spatio-temporal transfer learning for multiphase flow prediction in the fluidized bed reactor
Xinyu Xie, Yichen Hao, Pu Zhao, et al.
Applied Thermal Engineering (2025), pp. 126247-126247
Closed Access
Synergizing machine learning with fluid–structure interaction research: An overview of trends and challenges
Muk Chen Ong, Guang Yin
(2025) Vol. 1, Iss. 1, pp. 9470002-9470002
Closed Access
DeepTRNet: Time-resolved reconstruction of flow around a circular cylinder via spatiotemporal deep neural networks
Shujin Laima, Xuxi Zhou, Xiaowei Jin, et al.
Physics of Fluids (2022) Vol. 35, Iss. 1
Closed Access | Times Cited: 16
An attention-mechanism incorporated deep recurrent optical flow network for particle image velocimetry
Yuxuan Han, Qian Wang
Physics of Fluids (2023) Vol. 35, Iss. 7
Closed Access | Times Cited: 10
Combined space–time reduced-order model with three-dimensional deep convolution for extrapolating fluid dynamics
Indu Kant Deo, Rui Gao, Rajeev K. Jaiman
Physics of Fluids (2023) Vol. 35, Iss. 4
Closed Access | Times Cited: 9
Comparison of reduced order models based on dynamic mode decomposition and deep learning for predicting chaotic flow in a random arrangement of cylinders
Neil Ashwin Raj, Danesh K. Tafti, Nikhil Muralidhar
Physics of Fluids (2023) Vol. 35, Iss. 7
Closed Access | Times Cited: 9
A novel attention enhanced deep neural network for hypersonic spatiotemporal turbulence prediction
J. Du, Xin Li, Siwei Dong, et al.
Physics of Fluids (2024) Vol. 36, Iss. 5
Open Access | Times Cited: 3
Fast prediction of compressor flow field in nuclear power system based on proper orthogonal decomposition and deep learning
Jun Yang, Yanping Huang, Dianle Wang, et al.
Frontiers in Energy Research (2023) Vol. 11
Open Access | Times Cited: 7
Heat Flux Prediction of Radiation Balance Wall by Deep Convolutional Neural Networks
Gang Dai, Wenwen Zhao, Shaobo Yao, et al.
Journal of Thermophysics and Heat Transfer (2024) Vol. 38, Iss. 4, pp. 538-548
Closed Access | Times Cited: 2
Learning Paradigms and Modelling Methodologies for Digital Twins in Process Industry
Michael Mayr, Georgios C. Chasparis, Josef Küng
Lecture notes in computer science (2024), pp. 34-47
Closed Access | Times Cited: 2
Deep learning-based reduced order model for three-dimensional unsteady flow using mesh transformation and stitching
Xin Li, Zhiwen Deng, Rui Feng, et al.
Computers & Fluids (2024), pp. 106441-106441
Closed Access | Times Cited: 2
Deep-Learning Strategy Based on Convolutional Neural Network for Wall Heat Flux Prediction
Gang Dai, Wenwen Zhao, Shaobo Yao, et al.
AIAA Journal (2023) Vol. 61, Iss. 11, pp. 4772-4782
Closed Access | Times Cited: 6
Discovering optimal flapping wing kinematics using active deep learning
Baptiste Corban, Michaël Bauerheim, Thierry Jardin
Journal of Fluid Mechanics (2023) Vol. 974
Closed Access | Times Cited: 5
A generalized framework for unsupervised learning and data recovery in computational fluid dynamics using discretized loss functions
Deepinder Jot Singh Aulakh, Steven Beale, Jon G. Pharoah
Physics of Fluids (2022) Vol. 34, Iss. 7
Closed Access | Times Cited: 8
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