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Related papers: Analog-Based Forecasting of Turbulent Velocity: Re…

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We study the predictability of turbulent velocity signals using probabilistic analog-forecasting. Here, predictability is defined by the accuracy of forecasts and the associated uncertainties. We study the Gledzer--Ohkitani--Yamada (GOY)…

We perform a statistical analysis of experimental fully developed turbulence longitudinal velocity data in the Fourier space. We address the controversial issue of statistical intermittency of spatial Fourier modes by acting on the finite…

Statistical Mechanics · Physics 2007-05-23 L. Chevillard , N. Mazellier , C. Poulain , Y. Gagne , C. Baudet

Turbulent flows in three dimensions are characterized by the transport of energy from large to small scales through the energy cascade. Since the small scales are the result of the nonlinear dynamics across the scales, they are often…

Fluid Dynamics · Physics 2025-03-19 Lukas Bentkamp , Michael Wilczek

The statistics obtained from turbulent flow simulations are generally uncertain due to finite time averaging. The techniques available in the literature to accurately estimate these uncertainties typically only work in an offline mode, that…

We report an experimental investigation of the statistical time dynamic of spatial Fourier modes in a fully developped turbulent jet flow. Measurements rely on an original acoustic scattering technique, allowing the direct and continuous…

Statistical Mechanics · Physics 2009-11-11 C. Poulain , N. Mazellier , Y. Gagne , C. Baudet

Turbulence is known to show intermittency. That is, statistical properties vary with the length scale in a way not accounted for by statistical similarity where dimensionless ratios of moments are constant. Intermittency occurs even in the…

Fluid Dynamics · Physics 2007-05-23 Mogens V. Melander , Bruce R. Fabijonas

Large-scale intermittency is a widely observed phenomenon in convective surface layer turbulence that induces non-Gaussian temperature statistics, while such signature is not observed for velocity signals. Although approaches based on…

Fluid Dynamics · Physics 2021-09-15 Subharthi Chowdhuri , Giovanni Iacobello , Tirtha Banerjee

We present a study of the intermittent properties of a shell model of turbulence with unprecedented statistics, about $\sim 10^7$ eddy turn over time, achieved thanks to an implementation on a large-scale parallel GPU factory. This allows…

The scaling of acceleration statistics in turbulence is examined by combining data from the literature with new data from well-resolved direct numerical simulations of isotropic turbulence, significantly extending the Reynolds number range.…

Fluid Dynamics · Physics 2022-06-13 Dhawal Buaria , Katepalli R. Sreenivasan

Intermittency is an essential property of astrophysical fluids, which demonstrate an extended inertial range. As intermittency violates self-similarity of motions, it gets impossible to naively extrapolate the properties of fluid obtained…

Astrophysics · Physics 2011-05-10 A. Lazarian

Estimation of near-wall turbulence in channel flow from outer observations is investigated using adjoint-variational data assimilation. We first consider fully resolved velocity data, starting at a distance from the wall. By enforcing the…

Fluid Dynamics · Physics 2025-04-09 Mengze Wang , Tamer A. Zaki

Turbulent signals are known to exhibit burst-like activities, which affect the turbulence statistics at both large and small scales of the flow. In our study, we pursue this problem from the perspective of an event-based framework, where…

Fluid Dynamics · Physics 2023-01-26 Subharthi Chowdhuri , Tirtha Banerjee

New aspects of turbulence are uncovered if one considers flow motion from the perspective of a fluid particle (known as the Lagrangian approach) rather than in terms of a velocity field (the Eulerian viewpoint). Using a new experimental…

Fluid Dynamics · Physics 2009-11-07 N. Mordant , J. Delour , E. Leveque , A. Arneodo , J. -F. Pinton

For high contrast imaging systems, the time delay is one of the major limiting factors for the performance of the extreme adaptive optics (AO) sub-system and, in turn, the final contrast. The time delay is due to the finite time needed to…

Instrumentation and Methods for Astrophysics · Physics 2019-04-08 Maaike van Kooten , Niek Doelman , Matthew Kenworthy

We present a methodology for the study of the dispersion of trajectories of stochastic processes in reconstructed phase spaces from observed data. The methodology allows to find ensembles of analog states, i.e. states that are close in the…

Chaotic Dynamics · Physics 2026-02-18 Carlos Granero-Belinchon

Intermittency is a hallmark of turbulence, which exists not only in turbulent flows of classical viscous fluids but also in flows of quantum fluids such as superfluid $^4$He. Despite the established similarity between turbulence in…

Fluid Dynamics · Physics 2018-09-12 Emil Varga , Jian Gao , Wei Guo , Ladislav Skrbek

The velocity circulation, a measure of the rotation of a fluid within a closed path, is a fundamental observable in classical and quantum flows. It is indeed a Lagrangian invariant in inviscid classical fluids. In quantum flows, circulation…

Fluid Dynamics · Physics 2021-03-17 Nicolás P. Müller , Juan Ignacio Polanco , Giorgio Krstulovic

The universality of intermittency in hydrodynamic turbulence is considered based on a recent model for the velocity gradient tensor evolution. Three possible versions of the model are investigated differing in the assumed correlation…

Fluid Dynamics · Physics 2007-05-23 Laurent Chevillard , Charles Meneveau

Turbulence is prevalent in nature and industry, from large-scale wave dynamics to small-scale combustion nozzle sprays. In addition to the multi-scale nonlinear complexity and both randomness and coherent structures in its dynamics,…

Tidal energy is one of the key components in increasing the penetration of renewable energy. High tidal energy penetration into the electrical grid depends on accurate tidal current speed forecasting. Model inaccuracies hinder forecast…

Machine Learning · Computer Science 2026-03-03 Tengfei Cheng , Yangdi Huang , Ling Xiao , Yunxuan Dong
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