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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:

Towards high-accuracy deep learning inference of compressible flows over aerofoils
Li-Wei Chen, Nils Thuerey
Computers & Fluids (2022) Vol. 250, pp. 105707-105707
Closed Access | Times Cited: 33

Showing 1-25 of 33 citing articles:

Deep learning in computational mechanics: a review
Leon Herrmann, Stefan Kollmannsberger
Computational Mechanics (2024) Vol. 74, Iss. 2, pp. 281-331
Open Access | Times Cited: 26
Current and emerging deep-learning methods for the simulation of fluid dynamics
Mario Lino, Stathi Fotiadis, Anil A. Bharath, et al.
Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences (2023) Vol. 479, Iss. 2275
Open Access | Times Cited: 22
Predicting unsteady incompressible fluid dynamics with finite volume informed neural network
Tianyu Li, Shufan Zou, Xinghua Chang, et al.
Physics of Fluids (2024) Vol. 36, Iss. 4
Open Access | Times Cited: 11
Fast simulation of airfoil flow field via deep neural network
Kuijun Zuo, Zhengyin Ye, Shuhui Bu, et al.
Aerospace Science and Technology (2024) Vol. 150, pp. 109207-109207
Open 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: 16
A deep neural network reduced order model for unsteady aerodynamics of pitching airfoils
Giacomo Baldan, Alberto Guardone
Aerospace Science and Technology (2024) Vol. 152, pp. 109345-109345
Open Access | Times Cited: 5
Spatiotemporal super-resolution forecasting of high-speed turbulent flows
Filippos Sofos, Dimitris Drikakis, Ioannis W. Kokkinakis, et al.
Physics of Fluids (2025) Vol. 37, Iss. 1
Closed Access
Physics-informed graph neural network based on the finite volume method for steady incompressible laminar convective heat transfer
Haiming Zhang, Xin‐Lin Xia, Ze Wu, et al.
Physics of Fluids (2025) Vol. 37, Iss. 1
Closed Access
A convolutional neural network-based model for reconstructing free surface flow fields
Jiahui Wang, Hong Xiao
Physics of Fluids (2025) Vol. 37, Iss. 1
Closed Access
Deep learning modeling of manufacturing and build variations on multistage axial compressors aerodynamics
Giuseppe Bruni, Sepehr Maleki, Senthil Krishnababu
Data-Centric Engineering (2025) Vol. 6
Open Access
Multi-Level Adaptive Sampling Algorithms for Machine Learning of Steady Fluid Flows With Geometry Resolving Recursive Refinement
Eric M. Wolf, Kazuko Fuchi, Christopher R. Schrock
AIAA SCITECH 2022 Forum (2025)
Closed Access
Neural operator-based super-fidelity: A warm-start approach for accelerating steady-state simulations
Xu‐Hui Zhou, Jiequn Han, Muhammad I. Zafar, et al.
Journal of Computational Physics (2025), pp. 113871-113871
Closed Access
Kolmogorov–Arnold PointNet: Deep learning for prediction of fluid fields on irregular geometries
Ali Kashefi
Computer Methods in Applied Mechanics and Engineering (2025) Vol. 439, pp. 117888-117888
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
Aerodynamic shape optimization of gas turbines: a deep learning surrogate model approach
Vahid Esfahanian, Mohammad J. Izadi, Hosein Bashi, et al.
Structural and Multidisciplinary Optimization (2023) Vol. 67, Iss. 1
Closed Access | Times Cited: 12
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
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
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
Towards spatio-temporal prediction of cavitating fluid flow with graph neural networks
Rui Gao, Shayan Heydari, Rajeev K. Jaiman
International Journal of Multiphase Flow (2024) Vol. 177, pp. 104858-104858
Open Access | Times Cited: 3
A novel Bayesian deep learning method for fast wake field prediction of the DARPA SUBOFF
Xinyu Xie, Pu Zhao, C.B. Bian, et al.
Applied Ocean Research (2024) Vol. 150, pp. 104074-104074
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
On neural networks for generating better local optima in topology optimization
Leon Herrmann, Ole Sigmund, V. Li, et al.
Structural and Multidisciplinary Optimization (2024) Vol. 67, Iss. 11
Open Access | Times Cited: 2
MPMNet: A Data-Driven MPM Framework for Dynamic Fluid-Solid Interaction
Jin Li, Yang Gao, Ju Dai, et al.
IEEE Transactions on Visualization and Computer Graphics (2023) Vol. 30, Iss. 8, pp. 4694-4708
Open Access | Times Cited: 5
Knowledge-embedded meta-learning model for lift coefficient prediction of airfoils
Hairun Xie, Jing Wang, Miao Zhang
Expert Systems with Applications (2023) Vol. 233, pp. 121002-121002
Open Access | Times Cited: 5
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