Destabilizing turbulence in pipe flow Journal Article


Author(s): Kühnen, Jakob; Song, Baofang; Scarselli, Davide; Budanur, Nazmi B; Riedl, Michael; Willis, Ashley P; Avila, Marc; Hof, Björn
Article Title: Destabilizing turbulence in pipe flow
Affiliation IST Austria
Abstract: Turbulence is the major cause of friction losses in transport processes and it is responsible for a drastic drag increase in flows over bounding surfaces. While much effort is invested into developing ways to control and reduce turbulence intensities, so far no methods exist to altogether eliminate turbulence if velocities are sufficiently large. We demonstrate for pipe flow that appropriate distortions to the velocity profile lead to a complete collapse of turbulence and subsequently friction losses are reduced by as much as 90%. Counterintuitively, the return to laminar motion is accomplished by initially increasing turbulence intensities or by transiently amplifying wall shear. Since neither the Reynolds number nor the shear stresses decrease (the latter often increase), these measures are not indicative of turbulence collapse. Instead, an amplification mechanism measuring the interaction between eddies and the mean shear is found to set a threshold below which turbulence is suppressed beyond recovery.
Keywords: fluid dynamics; Applied physics
Journal Title: Nature Physics
ISSN: 1745-2473
Publisher: Nature Publishing Group  
Date Published: 2018-01-08
URL:
DOI: 10.1038/s41567-017-0018-3
Notes: We acknowledge the European Research Council under the European Union’s Seventh Framework Programme (FP/2007-2013)/ERC Grant Agreement 306589, the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement no. 737549) and the Deutsche Forschungsgemeinschaft (Project No. FOR 1182) for financial support. We thank our technician P. Maier for providing highly valuable ideas and greatly supporting us in all technical aspects. We thank M. Schaner for technical drawings, construction and design. We thank M. Schwegel for a Matlab code to post-process experimental data.
Open access: yes (repository)