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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Physica A Statistica...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Physica A Statistical Mechanics and its Applications
Article . 2004 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
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Superstatistical Lagrangian stochastic modeling

Authors: A.M Reynolds;

Superstatistical Lagrangian stochastic modeling

Abstract

Abstract A simple superstatistical Lagrangian stochastic model (Phys. Fluids 15 (2003) L1; Phys. Rev. Lett. 91 (2003) 84503) that accounts explicitly for fluctuations in the rate of dissipation of turbulent kinetic energy has been shown to be in remarkably close agreement with recently acquired data for unconditional Lagrangian acceleration statistics. In this paper, a more elaborate version of the model is shown to predict correctly the observed conditional dependency of Lagrangian acceleration statistics on velocity. The modeling approach is then extended to the simulation of large/heavy-particle accelerations in turbulence. Model predictions for the distribution of accelerations of 450 μm diameter particles with near-neutral buoyancy are shown to be in excellent agreement with experimental data. Tsallis statistics are found to describe accurately model predictions for distributions of heavy-particle velocities and accelerations.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
10
Average
Average
Top 10%
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