Results 11 to 20 of about 903,153 (145)

Atmospheric turbulence and superstatistics [PDF]

open access: yesEurophysics News, 2005
Nonequilibrium systems with large-scale fluctuations of a suitable system parameter are often effectively described by a superposition of two statistics, a superstatistics. Here we illustrate this concept by analysing experimental data of fluctuations in atmospheric wind velocity differences at Florence airport.
E.G.D. Cohen, S. Rizzo, Christian Beck
openaire   +4 more sources

The fractal turbulent–non-turbulent interface in the atmosphere

open access: yesWind Energy Science, 2023
Abstract. With their constant increase in size, wind turbines are reaching unprecedented heights. Therefore, at these heights, they are influenced by wind conditions that have not yet been studied in detail. With increasing height, a transition to laminar conditions becomes more and more likely.
L. Neuhaus   +5 more
openaire   +3 more sources

Is isotropic turbulence relevant in the atmosphere? [PDF]

open access: yesGeophysical Research Letters, 2007
The problem of turbulence is ubiquitous in the Earth sciences, astrophysics and elsewhere. Virtually the only theoretical paradigm that has been seriously considered is strongly isotropic in the sense that scaling exponents are the same in all directions so that any remaining anisotropy is “trivial.” Using 235 state‐of‐the‐art drop sonde data sets of ...
S. J. Hovde   +4 more
openaire   +4 more sources

Offshore Wind Turbines Will Encounter Very Low Atmospheric Turbulence [PDF]

open access: yesJournal of Physics: Conference Series, 2019
Turbulence governs the development and erosion of wind farm wakes, which can deplete the offshore wind resource. Therefore, an accurate understanding of atmospheric turbulence is required to support the rapid growth of offshore wind energy.
N. Bodini, J. Lundquist, A. Kirincich
semanticscholar   +1 more source

Atmospheric Turbulence Study with Deep Machine Learning of Intensity Scintillation Patterns

open access: yesApplied Sciences, 2020
A new paradigm for machine learning-inspired atmospheric turbulence sensing is developed and applied to predict the atmospheric turbulence refractive index structure parameter using deep neural network (DNN)-based processing of short-exposure laser beam ...
A. Vorontsov   +3 more
semanticscholar   +1 more source

APPLICATION OF SUPERSTATISTICS TO ATMOSPHERIC TURBULENCE [PDF]

open access: yesComplexity, Metastability and Nonextensivity, 2005
7 pages, 4 figures. To be published in the proceedings of the 31st Workshop of the International School of Solid State Physics Complexity, Metastability And Nonextensivity Erice (Sicily) 20-26 July 2004, Eds. C. Beck, G. Benedek, A. Rapisarda and C. Tsallis, World Scientific (2005)
Andrea Rapisarda, Salvo Rizzo
openaire   +4 more sources

Structure of Atmospheric Turbulence

open access: yesAtmosphere, 2022
Turbulence is a phenomenon observed in the motions of fluids and gases [...]
Artem Yurievich Shikhovtsev   +1 more
openaire   +2 more sources

Deep learning based atmospheric turbulence compensation for orbital angular momentum beam distortion and communication.

open access: yesOptics Express, 2019
Atmospheric transmission distortion is one of the main challenges hampering the practical application of a vortex beam (VB) which carries orbital angular momentum (OAM).
Junmin Liu   +9 more
semanticscholar   +1 more source

Restoration of atmospheric turbulence-distorted images via RPCA and quasiconformal maps [PDF]

open access: yesInverse Problems, 2017
We address the problem of restoring a high-quality image from an observed image sequence strongly distorted by atmospheric turbulence. A novel algorithm is proposed in this paper to reduce geometric distortion as well as space-and-time-varying blur due ...
Chun Pong Lau, Y. Lai, L. Lui
semanticscholar   +1 more source

Joint atmospheric turbulence detection and adaptive demodulation technique using the CNN for the OAM-FSO communication.

open access: yesOptics Express, 2018
A novel joint atmospheric turbulence (AT) detection and adaptive demodulation technique based on convolutional neural network (CNN) are proposed for the OAM-based free-space optical (FSO) communication.
Jin Li   +4 more
semanticscholar   +1 more source

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