Hostname: page-component-586b7cd67f-t7fkt Total loading time: 0 Render date: 2024-11-23T14:50:53.976Z Has data issue: false hasContentIssue false

Pump or coast: the role of resonance and passive energy recapture in medusan swimming performance

Published online by Cambridge University Press:  29 January 2019

Alexander P. Hoover*
Affiliation:
Department of Mathematics, Tulane University, New Orleans, LA 70118, USA
Antonio J. Porras
Affiliation:
Department of Life and Physical Sciences, Fisk University, TN 37208, USA
Laura A. Miller
Affiliation:
Department of Mathematics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA Department of Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
*
Email address for correspondence: [email protected]

Abstract

Diverse organisms that swim and fly in the inertial regime use the flapping or pumping of flexible appendages and cavities to propel themselves through a fluid. It has long been postulated that the speed and efficiency of locomotion are optimized by oscillating these appendages at their frequency of free vibration. In jellyfish swimming, a significant contribution to locomotory efficiency has been attributed to the effects passive energy recapture, whereby the bell is passively propelled through the fluid through its interaction with stopping vortex rings formed during each expansion of the bell. In this paper, we investigate the interplay between resonance and passive energy recapture using a three-dimensional implementation of the immersed boundary method to solve the fluid–structure interaction of an elastic oblate jellyfish bell propelling itself through a viscous fluid. The motion is generated through a fixed duration application of active tension to the bell margin, which mimics the action of the coronal swimming muscles. The pulsing frequency is then varied by altering the length of time between the application of applied tension. We find that the swimming speed is maximized when the bell is driven at its resonant frequency. However, the cost of transport is maximized by driving the bell at lower frequencies whereby the jellyfish passively coasts between active contractions through its interaction with the stopping vortex ring. Furthermore, the thrust generated by passive energy recapture was found to be dependent on the elastic properties of the jellyfish bell.

Type
JFM Papers
Copyright
© 2019 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.)

References

Alben, S., Miller, L. A. & Peng, J. 2013 Efficient kinematics for jet-propelled swimming. J. Fluid Mech. 733, 100133.10.1017/jfm.2013.434Google Scholar
Alexander, R. McN. & Bennet-Clark, H. C. 1977 Storage of elastic strain energy in muscle and other tissues. Nature 265 (5590), 114117.10.1038/265114a0Google Scholar
Arai, M. N. 1997 A Functional Biology of Scyphozoa. Springer.Google Scholar
Balay, S., Abhyankar, S., Adams, M., Brown, J., Brune, P., Buschelman, K, Eijkhout, V., Gropp, W., Kaushik, D., Knepley, M. et al. 2009 PETSc: Web page http://www.mcs.anl.gov/petsc.Google Scholar
Balay, S., Gropp, W. D., McInnes, L. C. & Smith, B. F. 1997 Efficient management of parallelism in object-oriented numerical software libraries. Modern Software Tools for Scientific Computing. pp. 163202. Springer.10.1007/978-1-4612-1986-6_8Google Scholar
Bale, R., Hao, M., Bhalla, A. P. S. & Patankar, N. A. 2014 Energy efficiency and allometry of movement of swimming and flying animals. Proc. Natl Acad. Sci. USA 111 (21), 75177521.10.1073/pnas.1310544111Google Scholar
Bhalla, A. P. S., Bale, R., Griffith, B. E. & Patankar, N. A. 2013 A unified mathematical framework and an adaptive numerical method for fluid–structure interaction with rigid, deforming, and elastic bodies. J. Comput. Phys. 250, 446476.10.1016/j.jcp.2013.04.033Google Scholar
Costello, J. H. & Colin, S. P. 1995 Flow and feeding by swimming scyphomedusae. Mar. Biol. 124 (3), 399406.10.1007/BF00363913Google Scholar
Dabiri, J. O., Colin, S. P., Katija, K. & Costello, J. H. 2010 A wake-based correlate of swimming performance and foraging behavior in seven co-occurring jellyfish species. J. Expl Biol. 213 (8), 12171225.10.1242/jeb.034660Google Scholar
Dabiri, J. O., Colin, S. P. & Costello, J. H. 2007 Morphological diversity of medusan lineages constrained by animal–fluid interactions. J. Expl Biol. 210 (11), 18681873.10.1242/jeb.003772Google Scholar
Dabiri, J. O., Colin, S. P., Costello, J. H. & Gharib, M. 2005a Flow patterns generated by oblate medusan jellyfish: field measurements and laboratory analyses. J. Expl Biol. 208 (7), 12571265.10.1242/jeb.01519Google Scholar
Dabiri, J. O., Gharib, M., Colin, S. P. & Costello, J. H. 2005b Vortex motion in the ocean: in situ visualization of jellyfish swimming and feeding flows. Phys. Fluids 17 (9), 091108.10.1063/1.1942521Google Scholar
Daniel, T. L. 1983 Mechanics and energetics of medusan jet propulsion. Canad. J. Zool. 61 (6), 14061420.10.1139/z83-190Google Scholar
Demont, M. E. & Gosline, J. M. 1988 Mechanics of jet propulsion in the hydromedusan jellyfish, polyorchis pexicillatus: Iii. a natural resonating bell; the presence and importance of a resonant phenomenon in the locomotor structure. J. Expl Biol. 134 (1), 347361.Google Scholar
Falgout, R. D. & Yang, U. M. 2002 hypre: A library of high performance preconditioners. Computational Science—ICCS 2002, pp. 632641. Springer.10.1007/3-540-47789-6_66Google Scholar
Fauci, L. J. & Peskin, C. S. 1988 A computational model of aquatic animal locomotion. J. Comput. Phys. 77 (1), 85108.10.1016/0021-9991(88)90158-1Google Scholar
Gemmell, B. J., Colin, S. P. & Costello, J. H. 2018 Widespread utilization of passive energy recapture in swimming medusae. J. Exp. Biol. 221 (1), 168575.10.1242/jeb.168575Google Scholar
Gemmell, B. J., Colin, S. P., Costello, J. H. & Dabiri, J. O. 2015a Suction-based propulsion as a basis for efficient animal swimming. Nat. Commun. 6, 8790.10.1038/ncomms9790Google Scholar
Gemmell, B. J., Costello, J. H. & Colin, S. P. 2014 Exploring vortex enhancement and manipulation mechanisms in jellyfish that contributes to energetically efficient propulsion. Commun. Integrative Biol. 7 (4), e29014.10.4161/cib.29014Google Scholar
Gemmell, B. J., Costello, J. H., Colin, S. P., Stewart, C. J., Dabiri, J. O., Tafti, D. & Priya, S. 2013 Passive energy recapture in jellyfish contributes to propulsive advantage over other metazoans. Proc. Natl Acad. Sci. USA 110 (44), 1790417909.10.1073/pnas.1306983110Google Scholar
Gemmell, B. J., Troolin, D. R., Costello, J. H., Colin, S. P. & Satterlie, R. A. 2015b Control of vortex rings for manoeuvrability. J. Royal Society Interface 12 (108), 20150389.10.1098/rsif.2015.0389Google Scholar
Griffith, B. E. & Luo, X. 2017 Hybrid finite difference/finite element immersed boundary method. Intl J. Numer. Meth. Biomed. Engng 33 (12), e2888.10.1002/cnm.2888Google Scholar
Griffith, B. E., Hornung, R. D., McQueen, D. M. & Peskin, C. S. 2007 An adaptive, formally second order accurate version of the immersed boundary method. J. Comput. Phys. 223 (1), 1049.10.1016/j.jcp.2006.08.019Google Scholar
Hamlet, C., Santhanakrishnan, A. & Miller, L. A. 2011 A numerical study of the effects of bell pulsation dynamics and oral arms on the exchange currents generated by the upside-down jellyfish cassiopea xamachana. J. Expl Biol. 214 (11), 19111921.10.1242/jeb.052506Google Scholar
Herschlag, G. & Miller, L. 2011 Reynolds number limits for jet propulsion: a numerical study of simplified jellyfish. J. Theoret. Biol. 285 (1), 8495.10.1016/j.jtbi.2011.05.035Google Scholar
Hoover, A. & Miller, L. 2015 A numerical study of the benefits of driving jellyfish bells at their natural frequency. J. Theoret. Biol. 374, 1325.10.1016/j.jtbi.2015.03.016Google Scholar
Hoover, A. P., Griffith, B. E. & Miller, L. A. 2017 Quantifying performance in the medusan mechanospace with an actively swimming three-dimensional jellyfish model. J. Fluid Mech. 813, 11121155.10.1017/jfm.2017.3Google Scholar
Hoover, A. P., Cortez, R., Tytell, E. D. & Fauci, L. J. 2018 Swimming performance, resonance and shape evolution in heaving flexible panels. J. Fluid Mech. 847, 386416.10.1017/jfm.2018.305Google Scholar
Hornung, R. D., Wissink, A. M. & Kohn, S. R. 2006 Managing complex data and geometry in parallel structured amr applications. Engng Comput. 22 (3-4), 181195.10.1007/s00366-006-0038-6Google Scholar
Horridge, G. A. 1954 The nerves and muscles of medusae I. conduction in the nervous system of Aurellia aurita Lamarck. J. Exp. Biol. 31 (4), 594600.Google Scholar
Huang, W.-X. & Sung, H. J. 2009 An immersed boundary method for fluid–flexible structure interaction. Comput. Meth. Appl. Mech. Engng 198 (33), 26502661.10.1016/j.cma.2009.03.008Google Scholar
HYPRE2011 hypre: High performance preconditioners, http://www.llnl.gov/CASC/hypre.Google Scholar
IBAMR2014 IBAMR: An adaptive and distributed-memory parallel implementation of the immersed boundary method, http://ibamr.googlecode.com/.Google Scholar
Jones, S. K., Laurenza, R., Hedrick, T. L., Griffith, B. E. & Miller, L. A. 2015 Lift versus drag based mechanisms for vertical force production in the smallest flying insects. J. Theoret. Biol. 384, 105120.10.1016/j.jtbi.2015.07.035Google Scholar
Kirk, B. S., Peterson, J. W., Stogner, R. H. & Carey, G. F. 2006 libMesh: A C + + Library for Parallel Adaptive Mesh Refinement/Coarsening Simulations. Engng Comput. 22 (3–4), 237254.10.1007/s00366-006-0049-3Google Scholar
McHenry, M. J. & Jed, J. 2003 The ontogenetic scaling of hydrodynamics and swimming performance in jellyfish (aurelia aurita). J. Expl Biol. 206 (22), 41254137.10.1242/jeb.00649Google Scholar
Megill, W. M.2002 The biomechanics of jellyfish swimming. PhD thesis, The University of British Columbia.Google Scholar
Megill, W. M., Gosline, J. M. & Blake, R. W. 2005 The modulus of elasticity of fibrillin-containing elastic fibres in the mesoglea of the hydromedusa polyorchis penicillatus. J. Expl Biol. 208 (220), 38193834.10.1242/jeb.01765Google Scholar
Miller, L. A. & Peskin, C. S. 2004 When vortices stick: an aerodynamic transition in tiny insect flight. J. Expl Biol. 207 (17), 30733088.10.1242/jeb.01138Google Scholar
Miller, L. A. & Peskin, C. S. 2005 A computational fluid dynamics of ‘clap and fling’ in the smallest insects. J. Expl Biol. 208 (2), 195212.10.1242/jeb.01376Google Scholar
Miller, L. A. & Peskin, C. S. 2009 Flexible clap and fling in tiny insect flight. J. Exp. Biol. 212 (19), 30763090.10.1242/jeb.028662Google Scholar
Mittal, R. & Iaccarino, G. 2005 Immersed boundary methods. Annu. Rev. Fluid Mech. 37, 239261.10.1146/annurev.fluid.37.061903.175743Google Scholar
Park, S. G., Chang, C. B., Huang, Wei-Xi & Sung, H. J. 2014 Simulation of swimming oblate jellyfish with a paddling-based locomotion. J. Fluid Mech. 748, 731755.10.1017/jfm.2014.206Google Scholar
Peskin, C. S. 1977 Numerical analysis of blood flow in the heart. J. Comput. Phys. 25 (3), 220252.10.1016/0021-9991(77)90100-0Google Scholar
Peskin, C. S. 2002 The immersed boundary method. Acta Numerica 11, 479517.10.1017/S0962492902000077Google Scholar
Quinn, D. B., Lauder, G. V. & Smits, A. J. 2014 Scaling the propulsive performance of heaving flexible panels. J. Fluid Mech. 738, 250267.10.1017/jfm.2013.597Google Scholar
Ramananarivo, S., Godoy-Diana, R. & Thiria, B. 2011 Rather than resonance, flapping wing flyers may play on aerodynamics to improve performance. Proc. Natl Acad. Sci. USA 108 (15), 59645969.10.1073/pnas.1017910108Google Scholar
Sahin, M. & Mohseni, K. 2009 An arbitrary Lagrangian–Eulerian formulation for the numerical simulation of flow patterns generated by the hydromedusa Aequorea victoria . J. Comput. Phys. 228 (12), 45884605.10.1016/j.jcp.2009.03.027Google Scholar
Sahin, M., Mohseni, K. & Colin, S. P. 2009 The numerical comparison of flow patterns and propulsive performances for the hydromedusae Sarsia tubulosa and Aequorea victoria . J. Exp. Biol. 212 (16), 26562667.10.1242/jeb.025536Google Scholar
SAMRAI2007 SAMRAI: Structured Adaptive Mesh Refinement Application Infrastructure, http://www.llnl.gov/CASC/SAMRAI.Google Scholar
Schmidt-Nielsen, K. 1972 Locomotion: energy cost of swimming, flying, and running. Science 177 (4045), 222228.10.1126/science.177.4045.222Google Scholar
Tytell, E. D., Hsu, C.-Y., Williams, T. L., Cohen, A. H. & Fauci, L. J. 2010 Interactions between internal forces, body stiffness, and fluid environment in a neuromechanical model of lamprey swimming. Proc. Natl Acad. Sci. USA 107 (46), 1983219837.10.1073/pnas.1011564107Google Scholar
Tytell, E. D., Leftwich, M. C., Hsu, C.-Y., Griffith, B. E., Cohen, A. H., Smits, A. J., Hamlet, C. & Fauci, L. J. 2016 Role of body stiffness in undulatory swimming: Insights from robotic and computational models. Phys. Rev. Fluids 1 (7), 073202.10.1103/PhysRevFluids.1.073202Google Scholar
Videler, J. J. 1993 Fish Swimming, vol. 10. Springer.10.1007/978-94-011-1580-3Google Scholar
Zhang, C., Guy, R. D., Mulloney, B., Zhang, Q. & Lewis, T. J. 2014 Neural mechanism of optimal limb coordination in crustacean swimming. Proc. Natl Acad. Sci. USA 111 (38), 1384013845.10.1073/pnas.1323208111Google Scholar
Zhao, H., Freund, J. B. & Moser, R. D. 2008 A fixed-mesh method for incompressible flow–structure systems with finite solid deformations. J. Comput. Phys. 227 (6), 31143140.10.1016/j.jcp.2007.11.019Google Scholar

Hoover et al. supplementary movie 1

Free vibration simulation for $\bar{\eta}_{mathrm{ref}}$. Tension is applied and sustained on the bell and then release. The bell then passively elastic material properties drive the expansion of the bell. The frequency of free vibration is then recorded from the oscillations of the bell radius during the expansion of the bell. Note that the initial contraction causes the bell to propel forward.

Download Hoover et al. supplementary movie 1(Video)
Video 11.8 MB

Hoover et al. supplementary movie 2

Video of $\bar{\omega}_{\mathrm{y}}$ for bells with $\bar{tau}=0.5$ over the propulsive cycle, $\bar{t}^{\mathrm{c}}$, for $\bar{\eta}$ equal to (left)$\frac{1}{3}\bar{\eta}_{\mathrm{ref}}$, (middle)$\frac{2}{3}\bar{\eta}_{\mathrm{ref}}$, and (right) $\bar{\eta}_{\mathrm{ref}}$. Note that the most flexible bell does not fully expand.

Download Hoover et al. supplementary movie 2(Video)
Video 20.9 MB

Hoover et al. supplementary movie 3

Video of $\bar{\omega}_{\mathrm{y}}$ over the same point of phase of the propulsive cycle, $\bar{t}^{\mathrm{c}}, for bells with $\bar{tau}^{*}=2.5$ for $\bar{\eta}$ equal to (left)$\frac{1}{3}\bar{\eta}_{\mathrm{ref}}$, (second from left)$\frac{2}{3}\bar{\eta}_{\mathrm{ref}}$, and (center) $\bar{\eta}_{\mathrm{ref}}$ $\bar{\eta}_{\mathrm{ref}}$, (second from right) $\frac{4}{3}\bar{\eta}_{\mathrm{ref}}$, and (right) $\frac{5}{3}\bar{\eta}_{\mathrm{ref}}$. Note that the driving period, $\bar{t}$, varies for all of the bells, but the resulting swimming speed is similar for bells with $\bar{\eta}\geq\frac{2}{3}\bar{\eta}$.

Download Hoover et al. supplementary movie 3(Video)
Video 19.9 MB