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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:

Fast aerodynamics prediction of laminar airfoils based on deep attention network
Kuijun Zuo, Zhengyin Ye, Weiwei Zhang, et al.
Physics of Fluids (2023) Vol. 35, Iss. 3
Closed Access | Times Cited: 51

Showing 1-25 of 51 citing articles:

A novel method for predicting fluid–structure interaction with large deformation based on masked deep neural network
Yangwei Liu, Shihang Zhao, Feitong Wang, et al.
Physics of Fluids (2024) Vol. 36, Iss. 2
Closed Access | Times Cited: 15
Flow3DNet: A deep learning framework for efficient simulation of three-dimensional wing flow fields
Kuijun Zuo, Zhengyin Ye, Xianxu Yuan, et al.
Aerospace Science and Technology (2025), pp. 109991-109991
Closed Access | Times Cited: 1
Long-term predictions of turbulence by implicit U-Net enhanced Fourier neural operator
Zhijie Li, Wenhui Peng, Zelong Yuan, et al.
Physics of Fluids (2023) Vol. 35, Iss. 7
Open Access | Times Cited: 28
Fast flow field prediction of three-dimensional hypersonic vehicles using an improved Gaussian process regression algorithm
Yuxin Yang, Youtao Xue, Wenwen Zhao, et al.
Physics of Fluids (2024) Vol. 36, Iss. 1
Open Access | Times Cited: 11
Self-supervised learning based on Transformer for flow reconstruction and prediction
Bonan Xu, Yuanye Zhou, Xin Bian
Physics of Fluids (2024) Vol. 36, Iss. 2
Open Access | Times Cited: 9
Aerodynamic shape optimization based on proper orthogonal decomposition reparameterization under small training sets
Yuxin Yang, Youtao Xue, Wenwen Zhao, et al.
Aerospace Science and Technology (2024) Vol. 147, pp. 109072-109072
Closed Access | Times Cited: 9
Prediction of transonic flow over supercritical airfoils using geometric-encoding and deep-learning strategies
Zhiwen Deng, Jing Wang, Hongsheng Liu, et al.
Physics of Fluids (2023) Vol. 35, Iss. 7
Open Access | Times Cited: 18
Estimation of cavitation velocity fields based on limited pressure data through improved U-shaped neural network
Yuhang Xu, Yangyang Sha, Cong Wang, et al.
Physics of Fluids (2023) Vol. 35, Iss. 8
Closed Access | Times Cited: 18
Fast and high-precision compressible flowfield inference method of transonic airfoils based on attention UNet
Z. Zhu, Guoqing Zhao, Qijun Zhao
Physics of Fluids (2024) Vol. 36, Iss. 3
Closed Access | Times Cited: 6
A complete state-space solution model for inviscid flow around airfoils based on physics-informed neural networks
Wenbo Cao, Jiahao Song, Weiwei Zhang
Journal of Computational Physics (2024) Vol. 516, pp. 113285-113285
Open Access | Times Cited: 6
Enhancing the accuracy of physics-informed neural networks for indoor airflow simulation with experimental data and Reynolds-averaged Navier–Stokes turbulence model
Chi Zhang, Chih‐Yung Wen, Jia Yuan, et al.
Physics of Fluids (2024) Vol. 36, Iss. 6
Closed Access | Times Cited: 5
Advances in the modeling of multiphase flows and their application in nuclear engineering—A review
Mengqi Wu, Jinsong Zhang, Nan Gui, et al.
Experimental and Computational Multiphase Flow (2024) Vol. 6, Iss. 4, pp. 287-352
Closed Access | Times Cited: 5
Blast loading prediction in a typical urban environment based on Bayesian deep learning
Weiwen Peng, Meilin Pan, Chunjiang Leng, et al.
Engineering Applications of Computational Fluid Mechanics (2025) Vol. 19, Iss. 1
Open Access
Deep Learning Method for Airfoil Flow Field Simulation Based on Unet++
Xie Rui-ling, Jie Xu, Jianping Chen, et al.
International Journal for Numerical Methods in Fluids (2025)
Closed Access
Unsteady aerodynamic modeling and analysis of aircraft model in multi-DOF coupling maneuvers at high angles of attack with attention mechanism
Wenzhao Dong, Xiaoguang Wang, Dong Han, et al.
Chinese Journal of Aeronautics (2025), pp. 103444-103444
Open Access
An Intelligent Prediction Method for Supersonic Flow Field in Scramjet Isolator Enhanced by Feature Details
Ye Tian, Yitong Zhao, Xue Deng, et al.
Aerospace Science and Technology (2025), pp. 110116-110116
Closed Access
UTransNet: An efficient hybrid architecture of convolutional neural networks and transformer for the approximation of non-uniform steady laminar flow
W. P. Wang, Tianle Yin, Jing Pang
Physics of Fluids (2025) Vol. 37, Iss. 3
Closed Access
Enhancing airfoil design optimization surrogate models using multi-task learning: Separating airfoil surface and fluid domain predictions
Xin Hu, Bo An, Yuelin Guan, et al.
Physics of Fluids (2025) Vol. 37, Iss. 3
Closed Access
Shock wave prediction in transonic flow fields using domain-informed probabilistic deep learning
Bilal Mufti, Anindya Bhaduri, Sayan Ghosh, et al.
Physics of Fluids (2024) Vol. 36, Iss. 1
Closed Access | Times Cited: 4
A Combined Modeling Method for Complex Multi-Fidelity Data Fusion
Lei Tang, Feng Liu, Anping Wu, et al.
Machine Learning Science and Technology (2024) Vol. 5, Iss. 3, pp. 035071-035071
Open Access | Times Cited: 4
Fast flow prediction of airfoil dynamic stall based on Fourier neural operator
Deying Meng, Yiding Zhu, Jianchun Wang, et al.
Physics of Fluids (2023) Vol. 35, Iss. 11
Closed Access | Times Cited: 11
A Review of Intelligent Airfoil Aerodynamic Optimization Methods Based on Data-Driven Advanced Models
Liyue Wang, Haochen Zhang, Cong Wang, et al.
Mathematics (2024) Vol. 12, Iss. 10, pp. 1417-1417
Open Access | Times Cited: 3
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
A generalized framework for integrating machine learning into computational fluid dynamics
Xuxiang Sun, Wenbo Cao, Xianglin Shan, et al.
Journal of Computational Science (2024) Vol. 82, pp. 102404-102404
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
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