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Synchronization to Big Data: Nudging the Navier-Stokes Equations for Data Assimilation of Turbulent Flows

Physical review. X, 2020-02, Vol.10 (1), p.011023, Article 011023

2020

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Synchronizing subgrid scale models of turbulence to data

Physics of fluids (1994), 2020-12, Vol.32 (12)

2020

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Reconstructing turbulent velocity and pressure fields from under-resolved noisy particle tracks using physics-informed neural networks

Experiments in fluids, 2023-05, Vol.64 (5), Article 95

2023

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Two-point stress–strain-rate correlation structure and non-local eddy viscosity in turbulent flows

Journal of fluid mechanics, 2021-03, Vol.914, Article A6

2021

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Reconstructing Rayleigh–Bénard flows out of temperature-only measurements using Physics-Informed Neural Networks

The European physical journal. E, Soft matter and biological physics, 2023-03, Vol.46 (3), p.16-16, Article 16

2023

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Assimilation of statistical data into turbulent flows using physics-informed neural networks

The European physical journal. E, Soft matter and biological physics, 2023-03, Vol.46 (3), p.13-13, Article 13

2023

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On the inverse energy transfer in rotating turbulence

The European physical journal. E, Soft matter and biological physics, 2018, Vol.41 (11), p.131-131, Article 131

2018

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Neural operator prediction of linear instability waves in high-speed boundary layers

Journal of computational physics, 2023-02, Vol.474, p.111793, Article 111793

2023

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Physics-Informed Neural Network for Ultrasound Nondestructive Quantification of Surface Breaking Cracks

Journal of nondestructive evaluation, 2020, Vol.39 (3), Article 61

2020

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Inferring flow parameters and turbulent configuration with physics-informed data assimilation and spectral nudging

Physical review fluids, 2018-10, Vol.3 (10), Article 104604

2018

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Quantifying resonant and near-resonant interactions in rotating turbulence

Journal of fluid mechanics, 2016-12, Vol.809, p.821-842

2016

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Instability-wave prediction in hypersonic boundary layers with physics-informed neural operators

Journal of computational science, 2023-11, Vol.73, p.102120, Article 102120

2023

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Quantitative estimation of effective viscosity in quantum turbulence

Physical review. A, 2019-04, Vol.99 (4), Article 043605

2019

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Active grid turbulence anomalies through the lens of physics informed neural networks

Results in engineering, 2024-12, Vol.24, p.103265, Article 103265

2024

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Optimal Control of Point-to-Point Navigation in Turbulent Time Dependent Flows Using Reinforcement Learning

AIxIA 2020 - Advances in Artificial Intelligence, 2021, Vol.12414, p.223-234

2021

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Reconstructing Rayleigh–Bénard flows out of temperature-only measurements using nudging

Physics of fluids (1994), 2022-01, Vol.34 (1)

2022

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Dual cascade and dissipation mechanisms in helical quantum turbulence

Physical review. A, 2017-05, Vol.95 (5), Article 053636

2017

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Neural operator prediction of linear instability waves in high-speed boundary layers

Journal of computational physics, 2022-11, Vol.474

2022

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Dynamics of partially thermalized solutions of the Burgers equation

Physical review fluids, 2018-01, Vol.3 (1), Article 014603

2018

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Finite-temperature effects in helical quantum turbulence

Physical review. A, 2018-04, Vol.97 (4), Article 043629

2018

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Synchronization to Big Data: Nudging the Navier-Stokes Equations for Data Assimilation of Turbulent Flows

Synchronizing subgrid scale models of turbulence to data

Reconstructing turbulent velocity and pressure fields from under-resolved noisy particle tracks using physics-informed neural networks

Two-point stress–strain-rate correlation structure and non-local eddy viscosity in turbulent flows

Reconstructing Rayleigh–Bénard flows out of temperature-only measurements using Physics-Informed Neural Networks

Assimilation of statistical data into turbulent flows using physics-informed neural networks

On the inverse energy transfer in rotating turbulence

Neural operator prediction of linear instability waves in high-speed boundary layers

Physics-Informed Neural Network for Ultrasound Nondestructive Quantification of Surface Breaking Cracks

Inferring flow parameters and turbulent configuration with physics-informed data assimilation and spectral nudging

Quantifying resonant and near-resonant interactions in rotating turbulence

Instability-wave prediction in hypersonic boundary layers with physics-informed neural operators

Quantitative estimation of effective viscosity in quantum turbulence

Active grid turbulence anomalies through the lens of physics informed neural networks

Optimal Control of Point-to-Point Navigation in Turbulent Time Dependent Flows Using Reinforcement Learning

Reconstructing Rayleigh–Bénard flows out of temperature-only measurements using nudging

Dual cascade and dissipation mechanisms in helical quantum turbulence

Neural operator prediction of linear instability waves in high-speed boundary layers

Dynamics of partially thermalized solutions of the Burgers equation

Finite-temperature effects in helical quantum turbulence

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