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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:

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: 16

Showing 16 citing articles:

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
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
Deep learning for airfoil aerodynamic-electromagnetic coupling optimization with random forest
Shi-Yi Jin, Shu-sheng Chen, C. C. Feng, et al.
Physics of Fluids (2024) Vol. 36, Iss. 1
Closed Access | Times Cited: 8
A boundary-assimilation Fourier neural operator for predicting initial fields of flow around structures
Yulin Xie, Bin Deng, Changbo Jiang, et al.
Physics of Fluids (2025) Vol. 37, Iss. 2
Closed Access
Wake field prediction and optimization of submarine with fillet based on data-driven deep learning model
K. H. Liu, Xinjing Wang, Jinglu Li, et al.
Physics of Fluids (2025) Vol. 37, Iss. 3
Closed Access
Nonlinear reduced-order modeling of compressible flow fields using deep learning and manifold learning
Bilal Mufti, Christian Perron, Dimitri N. Mavris
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 comprehensive deep learning geometric shape optimization framework with field prediction surrogate and reinforcement learning
Hao Ma, Jianing Liu, Mai Ye, et al.
Physics of Fluids (2024) Vol. 36, Iss. 4
Closed Access | Times Cited: 4
A residual graph convolutional network for setting initial flow field in computational fluid dynamics simulations
Xiaoyuan Zhang, Guopeng Sun, Peng Zhang, et al.
Physics of Fluids (2024) Vol. 36, Iss. 3
Open Access | Times Cited: 3
Learning dense gas-solids flows with physics-encoded neural network model
Xiaolin Guo, Chenshu Hu, Yuyang Dai, et al.
Chemical Engineering Journal (2024) Vol. 485, pp. 150072-150072
Closed Access | Times Cited: 2
A variable fidelity approach for predicting aerodynamic wall quantities of hypersonic vehicles using the ConvNeXt Encoder-Decoder framework
Yuxin Yang, Shaobo Yao, Youtao Xue, et al.
Aerospace Science and Technology (2024), pp. 109605-109605
Closed Access | Times Cited: 2
Koopman neural operator approach to fast flow prediction of airfoil transonic buffet
Deying Meng, Yiding Zhu, Jianchun Wang, et al.
Physics of Fluids (2024) Vol. 36, Iss. 7
Closed Access | Times Cited: 1
Uncertainty involved drag divergence characteristic predicting method based on VAE
Wei Liu, Hairun Xie, Jing Wang, et al.
Journal of Membrane Computing (2024) Vol. 6, Iss. 2, pp. 53-66
Closed Access
LKFlowNet: A deep neural network based on large kernel convolution for fast and accurate nonlinear fluid-changing prediction
Yan Liu, Qingyang Zhang, Xinhai Chen, et al.
Physics of Fluids (2024) Vol. 36, Iss. 9
Closed Access
CycleMLP++: An efficient and flexible modeling framework for subsonic airfoils
Kuijun Zuo, Zhengyin Ye, Linyang Zhu, et al.
Expert Systems with Applications (2024), pp. 125455-125455
Closed Access
Position query-guided cross-modal flow field prediction model of a transonic compressor cascade
Liyue Wang, Haochen Zhang, Xinyue Lan, et al.
Physics of Fluids (2024) Vol. 36, Iss. 10
Closed Access
Advancing buffet onset prediction: a deep learning approach with enhanced interpretability for aerodynamic engineering
Jing Wang, Liu We, Hairun Xie, et al.
Complex & Intelligent Systems (2024) Vol. 11, Iss. 1
Open Access
Toward aerodynamic surrogate modeling based on β-variational autoencoders
Víctor Francés-Belda, Alberto Solera-Rico, Javier Nieto-Centenero, et al.
Physics of Fluids (2024) Vol. 36, Iss. 11
Closed Access
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