Combining time-resolved multi-point and spatially-resolved measurements for the recovering of very-large-scale motions in high Reynolds number turbulent boundary layer-Reference-Cited by-同舟云学术

Combining time-resolved multi-point and spatially-resolved measurements for the recovering of very-large-scale motions in high Reynolds number turbulent boundary layer

Published:2017-04 Issue: Volume:82 Page:102-115
ISSN:0894-1777
Container-title:Experimental Thermal and Fluid Science
language:en
Short-container-title:Experimental Thermal and Fluid Science

Author:

Kerhervé F.,Roux S.,Mathis R.

Funder

International Campus on Safety and Intermodality in Transport in the Nord-Pas-de-Calais Region

European Community

Regional Delegation for Research and Technology

Ministry of Higher Education and Research

National Centre for Scientific Research

Publisher

Elsevier BV

Subject

Fluid Flow and Transfer Processes,Mechanical Engineering,Aerospace Engineering,Nuclear Energy and Engineering,General Chemical Engineering

Reference64 articles.

1. Stochastic estimation of the structure of turbulent fields;Adrian,1994

2. Hairpin vortex organization in wall turbulence;Adrian;Phys. Fluids,2007

3. Vortex organisation in the outer region of the turbulent boundary layer;Adrian;J. Fluid Mech.,2000

4. Stochastic estimation of organized turbulent structure – homogeneous shear flow;Adrian;J. Fluid Mech.,1988

5. Wavelet analysis of wall turbulence to study large-scale modulation of small scales;Baars;Exp. Fluids,2015

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