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Abstract

The fluid mechanics employed by aquatic animals in their escape or attack maneuvers, what we call survival hydrodynamics, are fascinating because the recorded performance in animals is truly impressive. Such performance forces us to pose some basic questions on the underlying flow mechanisms that are not yet in use in engineered vehicles. A closely related issue is the ability of animals to sense the flow velocity and pressure field around them in order to detect and discriminate threats in environments where vision or other sensing is of limited or no use. We review work on animal flow sensing and actuation as a source of inspiration and as a way to formulate a number of basic problems and investigate the flow mechanisms that enable animals to perform these remarkable maneuvers. We also describe some intriguing mechanisms of actuation and sensing.

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2016-01-03
2024-06-15
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Literature Cited

  1. Abdel-Latif H, Hassan E, von Campenhausen C. 1990. Sensory performance of blind Mexican cave fish after destruction of the canal neuromasts. Naturwissenschaften 77:237–39 [Google Scholar]
  2. Akanyeti O, Venturelli R, Visentin F, Chambers L, Megill WM, Fiorini P. 2011. What information do Kármán streets offer to flow sensing?. Bioinspir. Biomim. 6:036001 [Google Scholar]
  3. Asadnia M, Kottapalli AGP, Miao J, Triantafyllou MS. 2015. Artificial ciliary bundles with nanofiber tip links. arXiv:1505.02340 [physics.flu-dyn]
  4. Asadnia M, Kottapalli AGP, Shen Z, Miao J, Barbastathis G, Triantafyllou MS. 2013a. Flexible, zero powered, piezoelectric MEMS pressure sensor arrays for fish-like passive underwater sensing in marine vehicles. 2013 IEEE 26th Int. Conf. Micro Electro Mech. Syst. (MEMS)126–29 New York: IEEE [Google Scholar]
  5. Asadnia M, Kottapalli AGP, Shen Z, Miao J, Triantafyllou MS. 2013b. Flexible and surface-mountable piezoelectric sensor arrays for underwater sensing in marine vehicles. J. IEEE Sens. 13:3918–25 [Google Scholar]
  6. Beal D, Hover F, Triantafyllou MS, Liao J, Lauder G. 2006. Passive propulsion in vortex wakes. J. Fluid Mech. 549:385–402 [Google Scholar]
  7. Beem HR, Triantafyllou MS. 2015. Exquisitely sensitive seal whisker-like sensors detect wakes at large distances. arXiv:1501.04582 [physics.flu-dyn]
  8. Bleckmann H, Mogdans J, Coombs SL. 2014. Flow Sensing in Air and Water: Behavioral, Neural and Engineering Principles of Operation New York: Springer [Google Scholar]
  9. Bleckmann H, Zelick R. 1993. The responses of peripheral and central mechanosensory lateral line units of weakly electric fish to moving objects. J. Comp. Physiol. A 172:115–28 [Google Scholar]
  10. Borazjani I, Sotiropoulos F, Tytell ED, Lauder GV. 2012. Hydrodynamics of the bluegill sunfish C-start escape response: three-dimensional simulations and comparison with experimental data. J. Exp. Biol. 215:671–84 [Google Scholar]
  11. Bouffanais R, Weymouth GD, Yue DKP. 2010. Hydrodynamic object recognition using pressure sensing. Proc. R. Soc. A 467:19–38 [Google Scholar]
  12. Chadwell BA, Standen EM, Lauder GV, Ashley-Ross MA. 2012. Median fin function during the escape response of bluegill sunfish (Lepomis macrochirus). I: Fin-ray orientation and movement. J. Exp. Biol. 215:2869–80 [Google Scholar]
  13. Chagnaud BP, Bleckmann H, Engelmann J. 2006. Neural responses of goldfish lateral line afferents to vortex motions. J. Exp. Biol. 209:327–42 [Google Scholar]
  14. Chagnaud BP, Coombs S. 2014. Information encoding and processing by the peripheral lateral line system. See Coombs et al. 2014 151–94
  15. Chambers L, Akanyeti O, Venturelli R, Ježov J, Brown J. et al. 2014. A fish perspective: detecting flow features while moving using an artificial lateral line in steady and unsteady flow. J. R. Soc. Interface 11:20140467 [Google Scholar]
  16. Chen N, Tucker C, Engel JM, Yang Y, Pandya S, Liu C. 2007. Design and characterization of artificial haircell sensor for flow sensing with ultrahigh velocity and angular sensitivity. J. Microelectromech. Syst. 16:999–1014 [Google Scholar]
  17. Conte J, Modarres-Sadeghi Y, Watts M, Hover F, Triantafyllou MS. 2010. A fast-starting mechanical fish that accelerates at 40 m s−2. Bioinspir. Biomim. 5:035004 [Google Scholar]
  18. Coombs S, Bleckmann H, Fay RR, Popper AN. 2014. The Lateral Line System New York: Springer [Google Scholar]
  19. Coombs S, Conley RA. 1997. Dipole source localization by mottled sculpin. I. Approach strategies. J. Comp. Physiol. A 180:387–99 [Google Scholar]
  20. Corey DP, García-Añoveros J, Holt JR, Kwan KY, Lin SY. et al. 2004. TRPA1 is a candidate for the mechanosensitive transduction channel of vertebrate hair cells. Nature 432:723–30 [Google Scholar]
  21. Curcic-Blake B, van Netten SM. 2006. Source location encoding in the fish lateral line canal. J. Exp. Biol. 209:1548–59 [Google Scholar]
  22. Dagamseh AMK, Wiegerink RJ, Lammerink TSJ, Krijnen GJM. 2012. Towards a high-resolution flow camera using artificial hair sensor arrays for flow pattern observations. Bioinspir. Biomim. 7:046009 [Google Scholar]
  23. Dagamseh AMK, Wiegerink RJ, Lammerink TSJ, Krijnen GJM. 2013. Imaging dipole flow sources using an artificial lateral-line system made of biomimetic hair flow sensors. J. R. Soc. Interface 10:20130162 [Google Scholar]
  24. Dehnhardt G. 2001. Hydrodynamic trail-following in harbor seals (Phoca vitulina). Science 293:102–4 [Google Scholar]
  25. Dehnhardt G, Mauck B, Bleckmann H. 1998. Seal whiskers detect water movements. Nature 394:235–36 [Google Scholar]
  26. Domenici P. 2011. Webb scales fast-start maneuvers. J. Exp. Biol. 214:875–77 [Google Scholar]
  27. Domenici P, Blake R. 1997. The kinematics and performance of fish fast-start swimming. J. Exp. Biol. 200:1165–78 [Google Scholar]
  28. Dusek J, Kottapalli AGP, Woo ME, Asadnia M, Miao J. et al. 2013. Development and testing of bio-inspired microelectromechanical pressure sensor arrays for increased situational awareness for marine vehicles. Smart Mater. Struct. 22:014002 [Google Scholar]
  29. Eberhardt W, Shakhsheer Y, Calhoun B, Paulus J, Appleby M. 2011. A bio-inspired artificial whisker for fluid motion sensing with increased sensitivity and reliability. 2011 IEEE Sensors982–85 New York: IEEE [Google Scholar]
  30. Epps BP, Techet AH. 2007. Impulse generated during unsteady maneuvering of swimming fish. Exp. Fluids 43:691–700 [Google Scholar]
  31. Fernandez VI, Dusek J, Schulmeister J, Maertens A, Hou S. et al. 2011a. Pressure sensor arrays to optimize the high speed performance of ocean vehicles. 11th Int. Conf. Fast Sea Transp. TJ Peltzer 363–70 Alexandria, VA: Am. Soc. Nav. Eng. [Google Scholar]
  32. Fernandez VI, Maertens A, Yaul FM, Dahl J, Lang JH, Triantafyllou MS. 2011b. Lateral-line-inspired sensor arrays for navigation and object identification. Mar. Technol. Soc. J. 45:130–46 [Google Scholar]
  33. Gao A, Triantafyllou MS. 2012. Bio-inspired pressure sensing for active yaw control of underwater vehicles. 2012 Oceans1–7 New York: IEEE [Google Scholar]
  34. Gazzola M, Van Rees W, Koumoutsakos P. 2012. C-start: optimal start of larval fish. J. Fluid Mech. 698:5–18 [Google Scholar]
  35. Ginter CC, DeWitt TJ, Fish FE, Marshall CD. 2012. Fused traditional and geometric morphometrics demonstrate pinniped whisker diversity. PLoS ONE 7:e34481 [Google Scholar]
  36. Ginter CC, Fish FE, Marshall CD. 2010. Morphological analysis of the bumpy profile of phocid vibrissae. Mar. Mammal. Sci. 26:733–43 [Google Scholar]
  37. Hanke W, Witte M, Miersch L, Brede M, Oeffner J. et al. 2010. Harbor seal vibrissa morphology suppresses vortex-induced vibrations. J. Exp. Biol. 213:2665–72 [Google Scholar]
  38. Hans H, Miao J, Weymouth G, Triantafyllou MS. 2013. Whisker-like geometries and their force reduction properties. 2013 MTS/IEEE OCEANS - Bergen1–7 New York: IEEE [Google Scholar]
  39. Harper DG, Blake RW. 1991. Prey capture and the fast-start performance of northern pike Esox lucius. J. Exp. Biol. 155:175–92 [Google Scholar]
  40. Hassan ES. 1993. Mathematical description of the stimuli to the lateral line system of fish, derived from a three-dimensional flow field analysis. III. The case of an oscillating sphere near the fish. Biol. Cybern. 69:525–38 [Google Scholar]
  41. Huffard CL. 2006. Locomotion by Abdopus aculeatus (Cephalopoda: Octopodidae): walking the line between primary and secondary defenses. J. Exp. Biol. 209:3697–707 [Google Scholar]
  42. Klein A, Bleckmann H. 2011. Determination of object position, vortex shedding frequency and flow velocity using artificial lateral line canals. Beilstein J. Nanotechnol. 2:276–83 [Google Scholar]
  43. Kottapalli AGP, Asadnia M, Barbastathis G, Triantafyllou MS, Miao J, Tan C. 2012a. Polymer MEMS pressure sensor arrays for fish-like underwater sensing applications. Micro Nano Lett. 7:1189–92 [Google Scholar]
  44. Kottapalli AGP, Asadnia M, Hans H, Miao J, Triantafyllou MS. 2014a. Harbor seal inspired MEMS artificial micro-whisker sensor. 2014 IEEE 27th Int. Conf. Micro Electro Mech. Syst. (MEMS)741–44 New York: IEEE [Google Scholar]
  45. Kottapalli AGP, Asadnia M, Miao JM, Barbastathis G, Triantafyllou MS. 2012b. A flexible liquid crystal polymer MEMS pressure sensor array for fish-like underwater sensing. Smart Mater. Struct. 21:115030 [Google Scholar]
  46. Kottapalli AGP, Asadnia M, Miao JM, Triantafyllou MS. 2013. Electrospun nanofibrils encapsulated in hydrogel cupula for biomimetic MEMS flow sensor development. 2013 IEEE 26th Int. Conf. Micro Electro Mech. Syst. (MEMS)25–28 New York: IEEE [Google Scholar]
  47. Kottapalli AGP, Asadnia M, Miao J, Triantafyllou MS. 2014b. Touch at a distance sensing: lateral-line inspired MEMS flow sensors. Bioinsp. Biomim. 9:046011 [Google Scholar]
  48. Kottapalli AGP, Tan CW, Olfatnia M, Miao JM, Barbastathis G, Triantafyllou MS. 2011. A liquid crystal polymer membrane MEMS sensor for flow rate and flow direction sensing applications. J. Micromech. Microeng. 21:085006 [Google Scholar]
  49. Kriegseis J, Kinzel M, Rival DE. 2013. On the persistence of memory: Do initial conditions impact vortex formation?. J. Fluid Mech. 736:91–106 [Google Scholar]
  50. Liao JC. 2006. The role of the lateral line and vision on body kinematics and hydrodynamic preference of rainbow trout in turbulent flow. J. Exp. Biol. 209:4077–90 [Google Scholar]
  51. Liao JC. 2007. A review of fish swimming mechanics and behaviour in altered flows. Philos. Trans. R. Soc. B 362:1973–93 [Google Scholar]
  52. Liao JC, Beal DN, Lauder GV, Triantafyllou MS. 2003. Fish exploiting vortices decrease muscle activity. Science 302:1566–69 [Google Scholar]
  53. Liu C. 2007. Micromachined biomimetic artificial haircell sensors. Bioinspir. Biomim. 2:S162–69 [Google Scholar]
  54. Maertens AP, Triantafyllou MS. 2014. The boundary layer instability of a gliding fish helps rather than prevents object identification. J. Fluid Mech. 757:179–207 [Google Scholar]
  55. McConney ME, Anderson KD, Brott LL, Naik RR, Tsukruk VV. 2009a. Bioinspired material approaches to sensing. Adv. Funct. Mater. 19:2527–44 [Google Scholar]
  56. McConney ME, Chen N, Lu D, Hu HA, Coombs S. et al. 2009b. Biologically inspired design of hydrogel-capped hair sensors for enhanced underwater flow detection. Soft Matter 5:292–95 [Google Scholar]
  57. McHenry MJ, Liao JC. 2014. The hydrodynamics of flow stimuli. See Coombs et al. 2014 73–98
  58. Miao J, Kottapalli AGP, Asadnia M, Triantafyllou MS. 2013. Assessing flow for sightless underwater surveillance. SPIE Newsroom March 6. doi:10.1117/2.1201302.004734 [Google Scholar]
  59. Miersch L, Hanke W, Wieskotten S, Hanke FD, Oeffner J. et al. 2011. Flow sensing by pinniped whiskers. Philos. Trans. R. Soc. B 366:3077–84 [Google Scholar]
  60. Mogdans J, Bleckmann H. 1998. Responses of the goldfish trunk lateral line to moving objects. J. Comp. Physiol. A 182:659–76 [Google Scholar]
  61. Montgomery JC, Baker CF, Carton AG. 1997. The lateral line can mediate rheotaxis in fish. Nature 389:960–63 [Google Scholar]
  62. Montgomery JC, Coombs S, Baker CF. 2001. The mechanosensory lateral line system of the hypogean form of Astyanax fasciatus. The Biology of Hypogean Fishes A Romero 87–96 New York: Springer [Google Scholar]
  63. Montgomery JC, Coombs S, Halstead M. 1995. Biology of the mechanosensory lateral line in fishes. Rev. Fish Biol. Fish. 5:399–416 [Google Scholar]
  64. Müller HM, Fleck A, Bleckmann H. 1996. The responses of central octavolateralis cells to moving sources. J. Comp. Physiol. A 179:455–71 [Google Scholar]
  65. Müller UK, van den Boogaart JGM, van Leeuwen JL. 2008. Flow patterns of larval fish: undulatory swimming in the intermediate flow regime. J. Exp. Biol. 211:196–205 [Google Scholar]
  66. Niesterok B, Hanke W. 2012. Hydrodynamic patterns from fast-starts in teleost fish and their possible relevance to predator–prey interactions. J. Comp. Physiol. A 199:139–49 [Google Scholar]
  67. Packard A. 1969. Jet propulsion and the giant fibre response of Loligo. Nature 221:875–77 [Google Scholar]
  68. Pitcher T, Partridge B, Wardle C. 1976. A blind fish can school. Science 194:963–65 [Google Scholar]
  69. Plachta DTT, Hanke W, Bleckmann H. 2003. A hydrodynamic topographic map in the midbrain of goldfish Carassius auratus. J. Exp. Biol. 206:3479–86 [Google Scholar]
  70. Rapo MA, Jiang H, Grosenbaugh MA, Coombs S. 2009. Using computational fluid dynamics to calculate the stimulus to the lateral line of a fish in still water. J. Exp. Biol. 212:1494–505 [Google Scholar]
  71. Ren Z, Mohseni K. 2012. A model of the lateral line of fish for vortex sensing. Bioinspir. Biomim. 7:036016 [Google Scholar]
  72. Ristroph L, Liao JC, Zhang J. 2015. Lateral line layout correlates with the differential hydrodynamic pressure on swimming fish. Phys. Rev. Lett. 114:018102 [Google Scholar]
  73. Salumae T, Kruusmaa M. 2013. Flow-relative control of an underwater robot. Proc. R. Soc. A 469:20120671 [Google Scholar]
  74. Schulte-Pelkum N, Wieskotten S, Hanke W, Dehnhardt G, Mauck B. 2007. Tracking of biogenic hydrodynamic trails in harbour seals (Phoca vitulina). J. Exp. Biol. 210:781–87 [Google Scholar]
  75. Sichert A, Bamler R, van Hemmen J. 2009. Hydrodynamic object recognition: when multipoles count. Phys. Rev. Lett. 102:058104 [Google Scholar]
  76. Solomon JH, Hartmann MJ. 2006. Biomechanics: robotic whiskers used to sense features. Nature 443:525 [Google Scholar]
  77. Spagnolie SE, Shelley MJ. 2009. Shape-changing bodies in fluid: hovering, ratcheting, and bursting. Phys. Fluids 21:013103 [Google Scholar]
  78. Spedding GR. 2014. Wake signature detection. Annu. Rev. Fluid Mech. 46:273–302 [Google Scholar]
  79. Stocking JB, Eberhardt WC, Shakhsheer YA, Calhoun BH, Paulus JR, Appleby M. 2010. A capacitance-based whisker-like artificial sensor for fluid motion sensing. 2010 IEEE Sensors2224–29 New York: IEEE [Google Scholar]
  80. Streitlien K, Triantafyllou GS, Triantafyllou MS. 1996. Efficient foil propulsion through vortex control. AIAA J. 34:2315–19 [Google Scholar]
  81. Tao J, Yu XB. 2012. Hair flow sensors: from bio-inspiration to bio-mimicking—a review. Smart Mater. Struct. 21:113001 [Google Scholar]
  82. Taylor GI. 1953. Formation of a vortex ring by giving an impulse to a circular disk and then dissolving it away. J. Appl. Phys. 24:104–5 [Google Scholar]
  83. Triantafyllou MS. 2012. Survival hydrodynamics. J. Fluid Mech. 698:1–4 [Google Scholar]
  84. Tytell ED, Lauder GV. 2008. Hydrodynamics of the escape response in bluegill sunfish, Lepomis macrochirus. J. Exp. Biol. 211:3359–69 [Google Scholar]
  85. Valdivia P, Bhat S. 2014. Whisker-like sensors with tunable follicle sinus complex for underwater applications. Bioinspiration, Biomimetics, and Bioreplication 2014 A Lakhtakia, Art. 90550C Bellingham, WA: SPIE [Google Scholar]
  86. Valdivia P, Subramaniam V, Triantafyllou MS. 2012. Design of a bio-inspired whisker sensor for underwater applications. 2012 IEEE Sensors1–4 New York: IEEE [Google Scholar]
  87. Valdivia P, Subramaniam V, Triantafyllou MS. 2013. Performance analysis and characterization of bio-inspired whisker sensors for underwater applications. 2013 IEEE/RSJ Int. Conf. Intell. Robots Syst.5956–61 New York: IEEE [Google Scholar]
  88. van Netten SM. 2006. Hydrodynamic detection by cupulae in a lateral line canal: functional relations between physics and physiology. Biol. Cybern. 94:67–85 [Google Scholar]
  89. Venturelli R, Akanyeti O, Visentin F, Ježov J, Chambers LD. et al. 2012. Hydrodynamic pressure sensing with an artificial lateral line in steady and unsteady flows. Bioinspir. Biomim. 7:036004 [Google Scholar]
  90. von Campenhausen C, Riess I, Weissert R. 1981. Detection of stationary objects by the blind cave fish Anoptichthys jordani (Characidae). J. Comp. Physiol. 143:369–74 [Google Scholar]
  91. Wakeling JM, Johnston I. 1998. Muscle power output limits fast-start performance in fish. J. Exp. Biol. 201:1505–26 [Google Scholar]
  92. Webb JF. 2014a. Lateral line morphology and development and implications for the ontogeny of flow sensing in fishes. See Bleckmann et al. 2014 247–70
  93. Webb JF. 2014b. Morphological diversity, development, and evolution of mechanosensory lateral line system. See Coombs et al. 2014 17–72
  94. Webb P. 1976. The effect of size on the fast-start performance of rainbow trout Salmo cairdneri, and a consideration of piscivorous predator-prey interactions. J. Exp. Biol. 65:157–77 [Google Scholar]
  95. Weihs D. 1973. The mechanism of rapid starting of slender fish. Biorheology 10:343–50 [Google Scholar]
  96. Weihs D, Webb PW. 1984. Optimal avoidance and evasion tactics in predator-prey interactions. J. Theor. Biol. 106:189–206 [Google Scholar]
  97. Wells M. 1990. Oxygen extraction and jet propulsion in cephalopods. Can. J. Zool. 68:815–24 [Google Scholar]
  98. Weymouth GD, Subramaniam V, Triantafyllou MS. 2015. Ultra-fast escape maneuver of an octopus-inspired robot. Bioinspir. Biomim. 10:016016 [Google Scholar]
  99. Weymouth GD, Triantafyllou MS. 2012. Global vorticity shedding for a shrinking cylinder. J. Fluid Mech. 702:470–87 [Google Scholar]
  100. Weymouth GD, Triantafyllou MS. 2013. Ultra-fast escape of a deformable jet-propelled body. J. Fluid Mech. 721:367–85 [Google Scholar]
  101. Wieskotten S, Dehnhardt G, Mauck B, Miersch L, Hanke W. 2010. Hydrodynamic determination of the moving direction of an artificial fin by a harbour seal (Phoca vitulina). J. Exp. Biol. 213:2194–200 [Google Scholar]
  102. Wieskotten S, Mauck B, Miersch L, Dehnhardt G, Hanke W. 2011. Hydrodynamic discrimination of wakes caused by objects of different size or shape in a harbour seal (Phoca vitulina). J. Exp. Biol. 214:1922–30 [Google Scholar]
  103. Windsor SP, Norris SE, Cameron SM, Mallinson GD, Montgomery JC. 2010. The flow fields involved in hydrodynamic imaging by blind Mexican cave fish (Astyanax fasciatus). Part II: gliding parallel to a wall. J. Exp. Biol. 213:3832–42 [Google Scholar]
  104. Wu G, Yang Y, Zeng L. 2007. Routine turning maneuvers of koi carp Cyprinus carpio koi: effects of turning rate on kinematics and hydrodynamics. J. Exp. Biol. 210:4379–89 [Google Scholar]
  105. Yang Y, Chen J, Engel J, Pandya S, Chen N. et al. 2006. Distant touch hydrodynamic imaging with an artificial lateral line. PNAS 103:18891–95 [Google Scholar]
  106. Yang Y, Klein A, Bleckmann H, Liu C. 2011. Artificial lateral line canal for hydrodynamic detection. Appl. Phys. Lett. 99:023701 [Google Scholar]
  107. Zhu Q, Wolfgang M, Yue DKP, Triantafyllou MS. 2002. Three-dimensional flow structures and vorticity control in fish-like swimming. J. Fluid Mech. 468:1–28 [Google Scholar]
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