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Artificial neural networks trained through deep reinforcement learning discover control strategies for active flow control

Journal of fluid mechanics, 2019-04, Vol.865, p.281-302

2019

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Direct shape optimization through deep reinforcement learning

Journal of computational physics, 2021-03, Vol.428, p.110080, Article 110080

2021

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Performing particle image velocimetry using artificial neural networks: a proof-of-concept

Measurement science & technology, 2017-11, Vol.28 (12), p.125301

2017

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Deep reinforcement learning for turbulent drag reduction in channel flows

The European physical journal. E, Soft matter and biological physics, 2023-04, Vol.46 (4), p.27-27, Article 27

2023

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Deep reinforcement learning in fluid mechanics: A promising method for both active flow control and shape optimization

Journal of hydrodynamics. Series B, 2020-04, Vol.32 (2), p.234-246

2020

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Flow Control in Wings and Discovery of Novel Approaches via Deep Reinforcement Learning

Fluids (Basel), 2022-02, Vol.7 (2), p.62

2022

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Exploiting locality and translational invariance to design effective deep reinforcement learning control of the 1-dimensional unstable falling liquid film

AIP advances, 2019-12, Vol.9 (12), p.125014-125014-13

2019

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Measurements of wave damping by a grease ice slick in Svalbard using off-the-shelf sensors and open-source electronics

Journal of glaciology, 2017-04, Vol.63 (238), p.372-381

2017

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Correction to: Deep reinforcement learning for turbulent drag reduction in channel flows

The European physical journal. E, Soft matter and biological physics, 2023, Vol.46 (6), p.51-51, Article 51

2023

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A two layer model for wave dissipation in sea ice

Applied ocean research, 2019-07, Vol.88, p.111-118

2019

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Estimating the elastic modulus of landfast ice from wave observations

Journal of glaciology, 2023-09, p.1-11

2023

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Observations of wave dispersion and attenuation in landfast ice

Journal of geophysical research. Oceans, 2016-03, Vol.121 (3), p.1984-1997

2016

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A study using PIV of the intake flow in a diesel engine cylinder

The International journal of heat and fluid flow, 2016-12, Vol.62, p.56-67

2016

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The attenuation of monochromatic surface waves due to the presence of an inextensible cover

Wave motion, 2017-01, Vol.68, p.88-96

2017

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Bringing optical fluid motion analysis to the field: a methodology using an open source ROV as a camera system and rising bubbles as tracers

Measurement science & technology, 2021-09, Vol.32 (9), p.95302

2021

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Wave dispersion and dissipation in landfast ice: comparison of observations against models

The cryosphere, 2021-12, Vol.15 (12), p.5557-5575

2021

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Experimental evidence for a universal threshold characterizing wave-induced sea ice break-up

The cryosphere, 2020-11, Vol.14 (11), p.4265-4278

2020

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A comparison of an operational wave–ice model product and drifting wave buoy observation in the central Arctic Ocean: investigating the effect of sea-ice forcing in thin ice cover

Polar research, 2023-08, Vol.42, p.1-13

2023

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Deep Reinforcement Learning for Flow Control Exploits Different Physics for Increasing Reynolds Number Regimes

Actuators, 2022-12, Vol.11 (12), p.359

2022

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Wave measurements from ship mounted sensors in the Arctic marginal ice zone

Cold regions science and technology, 2021-02, Vol.182, p.103207, Article 103207

2021

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Laboratory Investigations of the Bending Rheology of Floating Saline Ice and Physical Mechanisms of Wave Damping in the HSVA Hamburg Ship Model Basin Ice Tank

Water (Basel), 2021-04, Vol.13 (8), p.1080

2021

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OpenMetBuoy-v2021: An Easy-to-Build, Affordable, Customizable, Open-Source Instrument for Oceanographic Measurements of Drift and Waves in Sea Ice and the Open Ocean

Geosciences (Basel), 2022-01, Vol.12 (3), p.110

2022

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Grid Turbulence Measurements with an Acoustic Doppler Current Profiler

Fluids (Basel), 2024-03, Vol.9 (3), p.60

2024

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A dataset of direct observations of sea ice drift and waves in ice

Scientific data, 2023-05, Vol.10 (1), p.251-251, Article 251

2023

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A review on deep reinforcement learning for fluid mechanics

Computers & fluids, 2021-07, Vol.225, p.104973, Article 104973

2021

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Artificial neural networks trained through deep reinforcement learning discover control strategies for active flow control

Direct shape optimization through deep reinforcement learning

Performing particle image velocimetry using artificial neural networks: a proof-of-concept

Deep reinforcement learning for turbulent drag reduction in channel flows

Deep reinforcement learning in fluid mechanics: A promising method for both active flow control and shape optimization

Flow Control in Wings and Discovery of Novel Approaches via Deep Reinforcement Learning

Exploiting locality and translational invariance to design effective deep reinforcement learning control of the 1-dimensional unstable falling liquid film

Measurements of wave damping by a grease ice slick in Svalbard using off-the-shelf sensors and open-source electronics

Correction to: Deep reinforcement learning for turbulent drag reduction in channel flows

A two layer model for wave dissipation in sea ice

Estimating the elastic modulus of landfast ice from wave observations

Observations of wave dispersion and attenuation in landfast ice

A study using PIV of the intake flow in a diesel engine cylinder

The attenuation of monochromatic surface waves due to the presence of an inextensible cover

Bringing optical fluid motion analysis to the field: a methodology using an open source ROV as a camera system and rising bubbles as tracers

Wave dispersion and dissipation in landfast ice: comparison of observations against models

Experimental evidence for a universal threshold characterizing wave-induced sea ice break-up

A comparison of an operational wave–ice model product and drifting wave buoy observation in the central Arctic Ocean: investigating the effect of sea-ice forcing in thin ice cover

Deep Reinforcement Learning for Flow Control Exploits Different Physics for Increasing Reynolds Number Regimes

Wave measurements from ship mounted sensors in the Arctic marginal ice zone

Laboratory Investigations of the Bending Rheology of Floating Saline Ice and Physical Mechanisms of Wave Damping in the HSVA Hamburg Ship Model Basin Ice Tank

OpenMetBuoy-v2021: An Easy-to-Build, Affordable, Customizable, Open-Source Instrument for Oceanographic Measurements of Drift and Waves in Sea Ice and the Open Ocean

Grid Turbulence Measurements with an Acoustic Doppler Current Profiler

A dataset of direct observations of sea ice drift and waves in ice

A review on deep reinforcement learning for fluid mechanics

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