On the self-organizing process of large scale shear flows

Andrew P.L. Newton, Eun Jin Kim, Han Li Liu

Research output: Contribution to journalArticle

14 Citations (Scopus)

Abstract

Self organization is invoked as a paradigm to explore the processes governing the evolution of shear flows. By examining the probability density function (PDF) of the local flow gradient (shear), we show that shear flows reach a quasi-equilibrium state as its growth of shear is balanced by shear relaxation. Specifically, the PDFs of the local shear are calculated numerically and analytically in reduced 1D and 0D models, where the PDFs are shown to converge to a bimodal distribution in the case of finite correlated temporal forcing. This bimodal PDF is then shown to be reproduced in nonlinear simulation of 2D hydrodynamic turbulence. Furthermore, the bimodal PDF is demonstrated to result from a self-organizing shear flow with linear profile. Similar bimodal structure and linear profile of the shear flow are observed in gulf stream, suggesting self-organization.

Original languageEnglish
Article number092306
JournalPhysics of Plasmas
Volume20
Issue number9
DOIs
Publication statusPublished - 24 Sep 2013
Externally publishedYes

ASJC Scopus subject areas

  • Condensed Matter Physics

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