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Drag reduction in turbulent flows over superhydrophobic surfaces

Daniello, Robert J., Waterhouse, Nicholas E., Rothstein, Jonathan P.·2009·Physics of Fluids

Abstract

In this paper, we demonstrate that periodic, micropatterned superhydrophobic surfaces, previously noted for their ability to provide laminar flow drag reduction, are capable of reducing drag in the turbulent flow regime. Superhydrophobic surfaces contain micro- or nanoscale hydrophobic features which can support a shear-free air-water interface between peaks in the surface topology. Particle image velocimetry and pressure drop measurements were used to observe significant slip velocities, shear stress, and pressure drop reductions corresponding to drag reductions approaching 50%. At a given Reynolds number, drag reduction is found to increase with increasing feature size and spacing, as in laminar flows. No observable drag reduction was noted in the laminar regime, consistent with previous experimental results for the channel geometry considered. The onset of drag reduction occurs at a critical Reynolds number where the viscous sublayer thickness approaches the scale of the superhydrophobic microfeatures and performance is seen to increase with further reduction in viscous sublayer height. These results indicate superhydrophobic surfaces may provide a significant drag reducing mechanism for marine vessels.

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Metadata

Authors
Daniello, R. J., Waterhouse, N. E., & Rothstein, J. P.
Venue
Physics of Fluids
Published
2009-08-01
Volume
21
Issue
8
ISSN
  • 1070-6631 (ISSN-L)
  • 1089-7666
OpenAlex
W2000180854
Cited by
627
References
0
FWCI
7.71
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Drag reduction in turbulent flows over superhydrophobic surfaces. https://app.cochat.ai/papers/10.1063/1.3207885
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Daniello, R. J., Waterhouse, N. E., & Rothstein, J. P. (2009). Drag reduction in turbulent flows over superhydrophobic surfaces. Physics of Fluids. https://doi.org/10.1063/1.3207885

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.