- Physical Review Journals
All JournalsPhysics Magazine
Access Provided by Xinjiang University

Physical Review Fluids

Reuse & Permissions

It is not necessary to obtain permission to reuse this article or its components as it is available under the terms of the Creative Commons Attribution 4.0 International license. This license permits unrestricted use, distribution, and reproduction in any medium, provided attribution to the author(s) and the published article's title, journal citation, and DOI are maintained. Please note that some figures may have been included with permission from other third parties. It is your responsibility to obtain the proper permission from the rights holder directly for these figures.

Export citation

Export citation

Choose format for download:

Download Citation
  • Gallery of Fluid Motion
  • Open Access
  • Access by Xinjiang University

Painting fluid motion using convolutional neural networks: An album of fluid motion 2.0

Maxime Bassenne*, Andrew Banko, and Sadaf Sobhani

  • Center for Turbulence Research, Stanford University, Stanford, California 94305, USA

  • *Corresponding author: bassenne@stanford.edu
PDF

Phys. Rev. Fluids 4, 100513 – Published 24 October, 2019

DOI: https://doi.org/10.1103/PhysRevFluids.4.100513

Abstract

This paper is associated with a poster winner of a 2018 APS/DFD Gallery of Fluid Motion Award for work presented at the DFD Gallery of Fluid Motion. The original poster is available online at the Gallery of Fluid Motion, https://doi.org/10.1103/APS.DFD.2018.GFM.P0004

View figure in article

Physics Subject Headings (PhySH)

Collections

This article appears in the following collection:

2018 Gallery of Fluid Motion

Collection of papers associated with the 2018 Gallery of Fluid Motion. These award winning works were presented at the annual meeting of the APS Division of Fluid Dynamics.

Article Text

References (9)

  1. M. D. Van Dyke, An Album of Fluid Motion (Parabolic, Stanford, CA, 1982).
  2. R. Camassa, D. M. Harris, D. Holz, R. M. McLaughlin, K. Mertens, P.-Y. Passaggia, and C. Viotti, Variable density vortex ring dynamics in sharply stratified ambient fluids, Phys. Rev. Fluids 1, 050503 (2016).
  3. C. Cohen, M. Berhanu, J. Derr, and S. Courrech du Pont, Erosion patterns on dissolving and melting bodies, Phys. Rev. Fluids 1, 050508 (2016).
  4. P. Chantelot, M. Coux, L. Domino, B. Pype, C. Clanet, A. Eddi, and D. Quéré, Kicked drops, Phys. Rev. Fluids 3, 100503 (2018).
  5. A. Bouillant, T. Mouterde, P. Bourrianne, C. Clanet, and D. Quéré, Symmetry breaking in Leidenfrost flows, Phys. Rev. Fluids 3, 100502 (2018).
  6. N. B. Speirs, M. M. Mansoor, J. Belden, R. C. Hurd, Z. Pan, and T. T. Truscott, Fluted films, Phys. Rev. Fluids 3, 100504 (2018).
  7. A. Krizhevsky, I. Sutskever, and G. E. Hinton, Imagenet classification with deep convolutional neural networks, in Advances in Neural Information Processing Systems (Curran Associates, Inc., Red Hook, NY, 2012), pp. 1097–1105.
  8. L. A. Gatys, A. S. Ecker, and M. Bethge, A neural algorithm of artistic style, Nat. Commun. (2015).
  9. A. Athalye, Neural style, https://github.com/anishathalye/neural-style (2015), commit 4ef159c.

Outline

Information

Phys. Rev. Fluids 4, 100513– Published 24 October, 2019
  • Received 25 January 2019
Crossmark - Check for updates button
Creative Commons Logo

Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.

Published by the American Physical Society

Sign In to Your Journals Account

Filter

Filter

Article Lookup

Enter a citation