Fish use the mechanosensory lateral line to detect water motions in their immediate surroundings and thus are able to avoid predators, track prey, swim in schools, and circumnavigate underwater objects. The basic unit of the lateral line is the neuromast, a sensory structure that consists of mechanosensitive hair cells enveloped in a gelatinous cupula. Lateral line neuromasts are distributed along the head and body of fish, either superficially on the skin or in subepidermal water-filled canals that open to the surroundings through a series of pores (Coombs et al. 1988). Water motions external to the fish induce pressure driven water motions inside the lateral line canal that drag on the cupulae of canal neuromasts causing them to be displaced by a few nanometers. These displacements, in turn, stimulate the underlying hair cells (Kalmijn 1988) which then signal the presence of the external water motions to the fish brain. Researchers have investigated fluid motions inside artificial lateral line canals (ALLCs) in response to sinusoidal external water motions to understand the functional significance of lateral line canals (LLCs). These studies have shown that LLCs behave like straight ALLCs of roughly the same cross sectional area. If an ALLC is stimulated in still water with a small-amplitude vibrating sphere placed adjacent to the canal, the water velocity inside the canal is proportional to the component of the external water acceleration that is parallel to the canal (Denton and Gray 1983). Up to now the filter properties of ALLCs have only been investigated in still water and only with a vibrating sphere as an external stimulus source. However, a fish may face a more complicated situation because either the fish moves, the water moves, or both move. We have conducted a collaborative investigation of this problem by performing numerical calculations at the University of Virginia and experimental measurements at the University of Bonn.
[1]
S. Coombs,et al.
Diversity of Lateral Line Systems: Evolutionary and Functional Considerations
,
1988
.
[2]
J. Humphrey,et al.
A numerical simulation of the convective heat transfer in confined channel flow past square cylinders: comparison of inline and offset tandem pairs
,
2001
.
[3]
Jacob Engelmann,et al.
Neural responses of goldfish lateral line afferents to vortex motions
,
2006,
Journal of Experimental Biology.
[4]
E. Denton,et al.
Mechanical factors in the excitation of clupeid lateral lines
,
1983,
Proceedings of the Royal Society of London. Series B. Biological Sciences.
[5]
J. Liao,et al.
The role of the lateral line and vision on body kinematics and hydrodynamic preference of rainbow trout in turbulent flow
,
2006,
Journal of Experimental Biology.
[6]
E. Bender.
Numerical heat transfer and fluid flow. Von S. V. Patankar. Hemisphere Publishing Corporation, Washington – New York – London. McGraw Hill Book Company, New York 1980. 1. Aufl., 197 S., 76 Abb., geb., DM 71,90
,
1981
.
[7]
Alfonso Ortega,et al.
A Numerical Investigation of the Convective Heat Transfer in Unsteady Laminar Flow Past a Single and Tandem Pair of Square Cylinders in a Channel
,
1998,
Heat Transfer: Volume 1 — Heat Transfer in Flowing Systems.
[8]
C. Peskin.
The immersed boundary method
,
2002,
Acta Numerica.
[9]
H. Bleckmann.
Reception of hydrodynamic stimuli in aquatic and semiaquatic animals
,
1994
.
[10]
E. Balaras,et al.
A general reconstruction algorithm for simulating flows with complex 3D immersed boundaries on Cartesian grids
,
2003
.
[11]
Ad. J. Kalmijn,et al.
Hydrodynamic and Acoustic Field Detection
,
1988
.