Structure extraction by stochastic estimation with adaptive events

S. Balachandar, R. J. Adrian

Research output: Contribution to journalArticle

4 Scopus citations

Abstract

Various aspects of turbulence structure can be found by a new class of stochasticestimation methods in which the conditional events that define the stochastic estimate are systematically varied. Methods are presented to find the length scale of large periodic structures, the form of structures that have specified geometric constraints such as two-dimensionality, and the structure of small-scale motions embedded in large-scale motions. These methodologies are demonstrated in high Rayleigh number turbulent convection by extracting both the large-scale roll-cell and coherent thermal plumes. A method of compressed representation using a stochastic estimate given data on optimally chosen points is also demonstrated.

Original languageEnglish (US)
Pages (from-to)243-257
Number of pages15
JournalTheoretical and Computational Fluid Dynamics
Volume5
Issue number4-5
DOIs
StatePublished - Nov 1 1993
Externally publishedYes

ASJC Scopus subject areas

  • Computational Mechanics
  • Condensed Matter Physics
  • Engineering(all)
  • Fluid Flow and Transfer Processes

Fingerprint Dive into the research topics of 'Structure extraction by stochastic estimation with adaptive events'. Together they form a unique fingerprint.

  • Cite this