Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

Turbulence control in plane Couette flow using low-dimensional neural ODE-based models and deep reinforcement learning
Alec J. Linot, Kevin Zeng, Michael D. Graham
International Journal of Heat and Fluid Flow (2023) Vol. 101, pp. 109139-109139
Open Access | Times Cited: 18

Showing 18 citing articles:

Perspectives on predicting and controlling turbulent flows through deep learning
Ricardo Vinuesa
Physics of Fluids (2024) Vol. 36, Iss. 3
Open Access | Times Cited: 13
Review of Challenges and Opportunities in Turbulence Modeling: A Comparative Analysis of Data-Driven Machine Learning Approaches
Yi Zhang, Dapeng Zhang, Haoyu Jiang
Journal of Marine Science and Engineering (2023) Vol. 11, Iss. 7, pp. 1440-1440
Open Access | Times Cited: 17
Dynamics of a data-driven low-dimensional model of turbulent minimal Couette flow
Alec J. Linot, Michael D. Graham
Journal of Fluid Mechanics (2023) Vol. 973
Open Access | Times Cited: 15
Data-driven state-space and Koopman operator models of coherent state dynamics on invariant manifolds
C. Ricardo Constante-Amores, Michael D. Graham
Journal of Fluid Mechanics (2024) Vol. 984
Open Access | Times Cited: 5
Data-driven transient lift attenuation for extreme vortex gust–airfoil interactions
Kai Fukami, Hiroya Nakao, Kunihiko Taira
Journal of Fluid Mechanics (2024) Vol. 992
Closed Access | Times Cited: 5
Reinforcement Learning With Symmetry Reduction for Rotating Cylinder Wakes: Finding Unstable Low-Drag Fixed Points
Hiroshi Omichi, Alec J. Linot, Koji Fukagata, et al.
AIAA SCITECH 2022 Forum (2025)
Closed Access
Policy-based optimization for drag reduction via spanwise wall oscillations
Lou Guérin, Laurent Cordier, Cédric Flageul, et al.
Neural Computing and Applications (2025)
Closed Access
Elastoinertial turbulence: data-driven reduced-order model based on manifold dynamics
Manish Kumar, C. Ricardo Constante-Amores, Michael D. Graham
Journal of Fluid Mechanics (2025) Vol. 1007
Open Access
Reducing flow fluctuation using deep reinforcement learning with a CNN-based flow feature model
Shuran Ye, Zhen Zhang, Yiwei Wang, et al.
Ocean Engineering (2024) Vol. 306, pp. 118089-118089
Open Access | Times Cited: 3
Model-based deep reinforcement learning for active control of flow around a circular cylinder using action-informed episode-based neural ordinary differential equations
Yiqian Mao, Shan Zhong, Hujun Yin
Physics of Fluids (2024) Vol. 36, Iss. 8
Closed Access | Times Cited: 2
Control policy transfer of deep reinforcement learning based intelligent forced heat convection control
Yi-Zhe Wang, Jiang-Zhou Peng, Nadine Aubry, et al.
International Journal of Thermal Sciences (2023) Vol. 195, pp. 108618-108618
Open Access | Times Cited: 5
Gym-preCICE: Reinforcement learning environments for active flow control
Mosayeb Shams, Ahmed H. Elsheikh
SoftwareX (2023) Vol. 23, pp. 101446-101446
Open Access | Times Cited: 4
Nonlinear dimensionality reduction then and now: AIMs for dissipative PDEs in the ML era
Eleni D. Koronaki, Nikos Evangelou, Cristina P. Martin-Linares, et al.
Journal of Computational Physics (2024) Vol. 506, pp. 112910-112910
Open Access | Times Cited: 1
Deep Reinforcement Learning-Augmented Spalart–Allmaras Turbulence Model: Application to a Turbulent Round Jet Flow
L. Fuchs, Jakob G. R. von Saldern, Thomas Ludwig Kaiser, et al.
Fluids (2024) Vol. 9, Iss. 4, pp. 88-88
Open Access | Times Cited: 1
Optimization of fluid control laws through deep reinforcement learning using dynamic mode decomposition as the environment
Takumi Sakamoto, Kie Okabayashi
AIP Advances (2024) Vol. 14, Iss. 11
Open Access | Times Cited: 1
On the laminar solutions and stability of accelerating and decelerating channel flows
Alec J. Linot, Peter J. Schmid, Kunihiko Taira
Journal of Fluid Mechanics (2024) Vol. 999
Open Access
Machine-learned closure of URANS for stably stratified turbulence: connecting physical timescales & data hyperparameters of deep time-series models
Murali Gopalakrishnan Meena, Demetri Liousas, Andrew D. Simin, et al.
Machine Learning Science and Technology (2024) Vol. 5, Iss. 4, pp. 045063-045063
Open Access
Nonlinear Dimensionality Reduction then and Now: Aims for Dissipative Pdes in the Ml Era
Eleni D. Koronaki, Nikos Evangelou, Cristina P. Martin-Linares, et al.
(2023)
Open Access
Page 1

Scroll to top