Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction | Paper Citation Record

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This paper cites and Brunton, S.

Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction and Brunton, S

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Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction The autonomous cycle of near-wall turbulence , journal =

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Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction , title =

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This paper cites Coherent structures in wall-bounded turbulence , journal =.

Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction Coherent structures in wall-bounded turbulence , journal =

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Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction and Moin, P

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This paper cites and Rabault, J.

Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction and Rabault, J

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Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction and Liu, Z

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This paper cites and Rabault, J.

Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction and Rabault, J

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This paper cites Flow control of three-dimensional cylinders transitioning to turbulence via multi-agent reinforcement learning , journal =.

Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction Flow control of three-dimensional cylinders transitioning to turbulence via multi-agent reinforcement learning , journal =

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This paper cites and Hoyas, S.

Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction and Hoyas, S

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This paper cites and Hoyas, S.

Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction and Hoyas, S

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This paper cites and Hoyas, S.

Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction and Hoyas, S

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This paper cites and Cremades, A.

Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction and Cremades, A

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This paper cites arXiv preprint arXiv:2601.05525 , year=.

Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction arXiv preprint arXiv:2601.05525 , year=

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This paper cites and Rabault, J.

Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction and Rabault, J

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Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction and Vinuesa, R

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This paper cites and Rabault, J.

Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction and Rabault, J

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Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction and Matteucci, L

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This paper cites An Explainable Deep Learning for Data-Driven Turbulence Model Feature Discovery , year=.

Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction An Explainable Deep Learning for Data-Driven Turbulence Model Feature Discovery , year=

Reference 21

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Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction and Benedikt, N

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This paper cites Explainable deep learning reveals the physical mechanisms behind the turbulent kinetic energy equation , journal =.

Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction Explainable deep learning reveals the physical mechanisms behind the turbulent kinetic energy equation , journal =

Reference 23

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Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction The minimal flow unit in near-wall turbulence , journal =

Reference 24

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Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction and Cremades, A

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Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction and Fukagata, K

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Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction Unresolved cited work

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Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction and van Hoof, H

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Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction and Hill, A

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Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction and Janizek, J

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Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction , title =

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Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction and Wine, David and Holloway, Brian and Chung, Daniel and Smits, Alexander J

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Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction Causal features in turbulent channel flow , journal =

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Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction Methods for interpreting and understanding deep neural networks , journal =

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Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction Multiscale analysis of the topological invariants in the logarithmic region of turbulent channels at a friction

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Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction and Noack, Bernd R

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Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction Artificial neural networks trained through deep reinforcement learning discover control strategies for active flow control , journal =

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Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction Unresolved cited work

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Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction and Monkewitz, Peter A

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Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction and Namkoong, Hongseok and Farhadi, Ali and Carmon, Yair and Kornblith, Simon and Schmidt, Ludwig , title =

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This paper cites URLhttps://www.nature.com/articles/ s43588-022-00264-7.

Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction URLhttps://www.nature.com/articles/ s43588-022-00264-7

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Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction On a self-sustaining process in shear flows

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Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction Jim é nez and A

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This paper cites Coherent structures in wall-bounded turbulence , volume=.

Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction Coherent structures in wall-bounded turbulence , volume=

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Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction McKeon, Peter A

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Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction Critical assessment of turbulent drag reduction through spanwise wall oscillations

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Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction Drag reduction in turbulent boundary layers by in-plane wall motion

Reference 54

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Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction Turbulent drag reduction by streamwise traveling waves of wall-normal forcing

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Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction Reynolds -number dependence of turbulent skin-friction drag reduction induced by spanwise forcing

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Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction Su á rez, F

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This paper cites Effective control of two-dimensional Rayleigh–Bénard convection: Invariant multi-agent reinforcement learning is all you need.Physics of Fluids, 35(6):065146, June 2023.

Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction Effective control of two-dimensional Rayleigh–Bénard convection: Invariant multi-agent reinforcement learning is all you need.Physics of Fluids, 35(6):065146, June 2023

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This paper cites doi: 10.1038/s41467-025-56408-6.

Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction doi: 10.1038/s41467-025-56408-6

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correction dated 2025-04-24. Source: crossref record 10.1038/s41467-025-57534-x->10.1038/s41467-025-56408-6:correction, observed 2026-07-11T02:59:09.107198+00:00. This notice travels one citation hop only.

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This paper cites Navigation in a simplified urban flow through deep rein- forcement learning.Journal of Computational Physics, 538:114194, October 2025.

Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction Navigation in a simplified urban flow through deep rein- forcement learning.Journal of Computational Physics, 538:114194, October 2025

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This paper cites Tonti, J.

Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction Tonti, J

Reference 61

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This paper cites Deep reinforcement learning for turbulent drag reduction in channel flows.The European Physical Journal E, 46(4):27, April 2023.

Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction Deep reinforcement learning for turbulent drag reduction in channel flows.The European Physical Journal E, 46(4):27, April 2023

Reference 62

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correction dated 2023-06-29. Source: crossref record 10.1140/epje/s10189-023-00304-8->10.1140/epje/s10189-023-00285-8:correction, observed 2026-07-11T03:01:38.904603+00:00. This notice travels one citation hop only.

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This paper cites Reinforcement learning of control strategies for reducing skin friction drag in a fully developed turbulent channel flow.Journal of Fluid Mechanics, 960:A30, April 2023.

Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction Reinforcement learning of control strategies for reducing skin friction drag in a fully developed turbulent channel flow.Journal of Fluid Mechanics, 960:A30, April 2023

Reference 63

Resolution: verified exact; doi, observed 2026-06-28T18:02:26.419421Z

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Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction Unresolved cited work

Reference 64

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This paper cites Cremades, S.

Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction Cremades, S

Reference 65

Resolution: verified exact; doi, observed 2026-06-28T18:02:26.446724Z

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This paper cites Cremades, S.

Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction Cremades, S

Reference 66

Resolution: verified exact; doi, observed 2026-06-28T18:02:26.427651Z

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Observation 1103688e-dc86-4c05-8210-e423da94e63e · outbound

This paper cites Cremades, S.

Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction Cremades, S

Reference 67

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Observation e398faab-2c6e-4743-9d50-5d6cea041bde · outbound

This paper cites Multiscale analysis of the topological invariants in the logarithmic region of turbulent channels at a friction Reynolds number of 932.

Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction Multiscale analysis of the topological invariants in the logarithmic region of turbulent channels at a friction Reynolds number of 932

Reference 68

Resolution: verified exact; arxiv_id, observed 2026-06-28T18:02:26.441762Z

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Observation 4693fb14-417f-4587-9994-bdff53d812ab · outbound

This paper cites Causal features in turbulent channel flow.

Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction Causal features in turbulent channel flow

Reference 69

Resolution: verified exact; doi, observed 2026-06-28T18:02:26.408416Z

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Observation 9104821d-5a7d-4d34-bb85-18e605858669 · outbound

This paper cites Hoyas, N.

Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction Hoyas, N

Reference 70

Resolution: verified exact; doi, observed 2026-06-28T18:02:26.438425Z

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Observation b4677d1e-4e5d-4542-bca7-31464970274e · outbound

This paper cites Improving turbulence control through explainable deep learning.

Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction Improving turbulence control through explainable deep learning

Reference 71

Resolution: verified exact; local_arxiv, observed 2026-06-28T18:02:26.898099Z

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Observation b96dde00-df6c-4291-ac0f-cc26558a9eb3 · outbound

This paper cites Kametani and K.

Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction Kametani and K

Reference 72

Resolution: verified exact; doi, observed 2026-06-28T18:02:26.436688Z

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Observation c73db40d-4b2b-4f45-9fef-c5fa9ac2c5f1 · outbound

This paper cites Fu, David Wine, Brian Holloway, Daniel Chung, and Alexander J.

Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction Fu, David Wine, Brian Holloway, Daniel Chung, and Alexander J

Reference 73

Resolution: verified exact; doi, observed 2026-06-28T18:02:26.412079Z

Source-reported events for the cited work

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Observation 72dd5760-ee86-40a8-8bd3-81acff4ad3df · outbound

This paper cites Jim é nez and P.

Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction Jim é nez and P

Reference 74

Resolution: verified exact; doi, observed 2026-06-28T18:02:26.421093Z

Source-reported events for the cited work

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Observation 9d02bb27-559f-424b-bef5-07993bc946bb · outbound

This paper cites J., Vasil, G.

Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction J., Vasil, G

Reference 75

Resolution: verified exact; doi, observed 2026-06-28T18:02:26.443560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation b4c345e0-e851-475d-96e3-f521ea1d2a22 · outbound

This paper cites an unresolved cited work.

Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction Unresolved cited work

Reference 76

Resolution: unresolved; no resolver link, observed 2026-06-28T17:59:27.746095Z

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Observation 8fe7cc43-63cd-4c0e-af53-0c168b78982c · outbound

This paper cites Fujimoto, H.

Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction Fujimoto, H

Reference 77

Resolution: unresolved; no resolver link, observed 2026-06-28T17:59:27.746095Z

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Observation 83968b1f-70eb-4eb0-bf83-d8d82c1d4d2d · outbound

This paper cites Raffin, A.

Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction Raffin, A

Reference 78

Resolution: unresolved; no resolver link, observed 2026-06-28T17:59:27.746095Z

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This paper cites Numerical simulation of turbulent duct flows with constant power input.

Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction Numerical simulation of turbulent duct flows with constant power input

Reference 79

Resolution: verified exact; doi, observed 2026-06-28T18:02:26.419092Z

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Observation e97d81c4-ce22-4a4c-a0d8-1c00a7513956 · outbound

This paper cites Morcos, Hongseok Namkoong, Ali Farhadi, Yair Carmon, Simon Kornblith, and Ludwig Schmidt.

Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction Morcos, Hongseok Namkoong, Ali Farhadi, Yair Carmon, Simon Kornblith, and Ludwig Schmidt

Reference 80

Resolution: unresolved; no resolver link, observed 2026-06-28T17:59:27.746095Z

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