Hostname: page-component-76fb5796d-22dnz Total loading time: 0 Render date: 2024-04-26T08:31:19.324Z Has data issue: false hasContentIssue false

Optimal morphokinematics for undulatory swimmers at intermediate Reynolds numbers

Published online by Cambridge University Press:  19 June 2015

Wim M. van Rees
Affiliation:
Chair of Computational Science, ETH Zurich, Clausiusstrasse 33, 8092 Zurich, Switzerland
Mattia Gazzola
Affiliation:
School of Engineering and Applied Sciences, Harvard University, 29 Oxford Street, Cambridge, MA 02138, USA
Petros Koumoutsakos*
Affiliation:
Chair of Computational Science, ETH Zurich, Clausiusstrasse 33, 8092 Zurich, Switzerland
*
Email address for correspondence: petros@ethz.ch

Abstract

Undulatory locomotion is an archetypal mode of propulsion for natural swimmers across scales. Undulatory swimmers convert transverse body oscillations into forward velocity by a complex interplay between their flexural movements, morphological features and the fluid environment. Natural evolution has produced a wide range of morphokinematic examples of undulatory swimmers that often serve as inspiration for engineering devices. It is, however, unknown to what extent natural swimmers are optimized for hydrodynamic performance. In this work, we reverse-engineer the morphology and gait for fast and efficient swimmers by coupling an evolution strategy to three-dimensional direct numerical simulations of flows at intermediate Reynolds numbers. The fastest swimmer is slender with a narrow tail fin and performs a sequence of C-starts to maximize its average velocity. The most efficient swimmer combines moderate transverse movements with a voluminous head, tapering into a streamlined profile via a pronounced inflection point. These optimal solutions outperform anguilliform swimming zebrafish in both efficiency and speed. We investigate the transition between morphokinematic solutions in the speed–energy space, laying the foundations for the design of high-performance artificial swimming devices.

Type
Papers
Copyright
© 2015 Cambridge University Press 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

Present address: School of Engineering and Applied Sciences, Harvard University, USA.

References

Blake, R. W. 2004 Fish function design and swimming performance. J. Fish Biol. 65, 11931222.CrossRefGoogle Scholar
Borazjani, I. & Sotiropoulos, F. 2010 On the role of form and kinematics on the hydrodynamics of self-propelled body/caudal fin swimming. J. Expl Biol. 213 (1), 89107.CrossRefGoogle ScholarPubMed
Bueche, D., Stoll, P., Dornberger, R. & Koumoutsakos, P. 2002 Multi-objective evolutionary algorithm for the optimization of noisy combustion problems. IEEE Trans. Syst. Man Cybern. C 32 (4), 460473.Google Scholar
Domenici, P. & Blake, R. W. 1997 The kinematics and performance of fish fast-start swimming. J. Expl Biol. 200 (8), 11651178.Google Scholar
Eloy, C. 2013 On the best design for undulatory swimming. J. Fluid Mech. 717, 4889.CrossRefGoogle Scholar
Gazzola, M., Argentina, M. & Mahadevan, L. 2014 Scaling macroscopic aquatic locomotion. Nat. Phys. 10, 758761.Google Scholar
Gazzola, M., Chatelain, P., van Rees, W. M. & Koumoutsakos, P. 2011 Simulations of single and multiple swimmers with non-divergence free deforming geometries. J. Comput. Phys. 230 (19), 70937114.Google Scholar
Gazzola, M., van Rees, W. M. & Koumoutsakos, P. 2012 C-start: optimal start of larval fish. J. Fluid Mech. 698, 518.Google Scholar
Griffiths, G.(Ed.) 2003 Technology and Applications of Autonomous Underwater Vehicles. Taylor and Francis.Google Scholar
Hansen, N., Muller, S. D. & Koumoutsakos, P. 2003 Reducing the time complexity of the derandomized evolution strategy with covariance matrix adaptation (CMA-ES). Evol. Comput. 11 (1), 118.CrossRefGoogle ScholarPubMed
Hunt, J. C. R., Wray, A. A. & Moin, P.1988 Eddies, streams, and convergence zones in turbulent flows. Tech. Rep. CTR-S88. Center for Turbulence Research Report.Google Scholar
Ijspeert, A. J., Crespi, A., Ryczko, D. & Cabelguen, J. M. 2007 From swimming to walking with a salamander robot driven by a spinal cord model. Science 315 (5817), 14161420.Google Scholar
Kern, S. & Koumoutsakos, P. 2006 Simulations of optimized anguilliform swimming. J. Expl Biol. 209 (24), 48414857.Google Scholar
Muller, U. K., van den Boogaart, J. G. M. & van Leeuwen, J. L. 2008 Flow patterns of larval fish: undulatory swimming in the intermediate flow regime. J. Expl Biol. 211 (2), 196205.CrossRefGoogle ScholarPubMed
van Rees, W. M., Gazzola, M. & Koumoutsakos, P. 2013 Optimal shapes for intermediate Reynolds number anguilliform swimming. J. Fluid Mech. 722, R3.Google Scholar
Taylor, G. K., Nudds, R. L. & Thomas, A. L. R. 2003 Flying and swimming animals cruise at a Strouhal number tuned for high power efficiency. Nature 425, 707711.CrossRefGoogle Scholar
Tokic, G. & Yue, D. K. P. 2012 Optimal shape and motion of undulatory swimming organisms. Proc. R. Soc. Lond. 279 (1740), 30653074.Google Scholar
Triantafyllou, G. S., Triantafyllou, M. S. & Grosenbaugh, M. A. 1993 Optimal thrust development in oscillating foils with application to fish propulsion. J. Fluids Struct. 7, 205224.CrossRefGoogle Scholar
Triantafyllou, M. S. & Triantafyllou, G. S. 1995 An efficient swimming. Sci. Am. 272 (3), 6470.CrossRefGoogle Scholar
Tytell, E. D., Borazjani, I., Sotiropoulos, F., Baker, T. V., Anderson, E. J. & Lauder, G. V. 2010 Disentangling the functional roles of morphology and motion in the swimming of fish. Integr. Compar. Biol. 50 (6), 11401154.Google Scholar
Webb, P. W. 1984 Body form, locomotion and foraging in aquatic vertebrates. Am. Zool. 24, 107120.CrossRefGoogle Scholar
Supplementary material: File

van Rees supplementary material

van Rees supplementary material 1

Download van Rees supplementary material(File)
File 826.5 KB