The fish ear contains three dense, bony bodies (otoliths) surrounded by fluid (the endolymph) and tissue. Under acoustic stimulation, the surrounding fluid and tissues oscillate relative to the otoliths, stimulating the endolymph as well as the array of hair cell cilia adjacent to the otolith and embedded in tissue. It is believed that the hair cell cilia move with the surrounding fluid. This doctoral thesis studied the steady streaming (i.e., time-independent) component of the acoustically induced fluid motion inside of the fish ear to determine how the hair cell cilia displacements due to the steady streaming could provide acoustically relevant information to the fish.
This research characterizes the fluid flow around oscillating model otoliths, namely spheroids, grooved spheroids, and a 350% scale model of a cod saccular otolith. This study models the otolithic endorgan as an oscillating body in a Newtonian fluid. The model ignores the surrounding tissues and assumes that the hair cell cilia move like the surrounding fluid. Particle pathline visualizations and particle-image velocimetry (PIV) are used to characterize the flow fields at various oscillation orientations, frequencies and amplitudes. These data are used to determine the location of the stagnation points on the body surface and at the boundaries of the inner rotating region of the flow. Studies are also conducted on bodies sinusoidally oscillated at both a single frequency and two (simultaneous) frequencies along the same direction. Both the steady streaming flow patterns and velocity fields are found to contain acoustically relevant information, but given the very small displacements associated with these flows, it is unclear if the steady streaming flows can be sensed by the fish ear.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/26695 |
| Date | 17 November 2008 |
| Creators | Kotas, Charlotte Walker |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Detected Language | English |
| Type | Dissertation |
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