Fig 1.
(A) A representative illustration of the Model 0 tag with a foil-like cross section. As swimming speed increases, the lift generated by this housing shape becomes the dominant force acting on the tag. The tag components that drive the packaging constraint are shown in the bottom left. (B) Illustration of a tag with a flow screen, wing and underbody channel designed to reduce the lift force acting on the tag.
Fig 2.
Tag housing designs in planform view (top row), longitudinal cross-section (middle row) and side view (bottom row).
The longitudinal cross-sections are taken along the center line of the tags (marked A to D in the top row). The Model A design has a hydrodynamic body, channel and wing. Dimensions are in millimeters.
Fig 3.
Detailed cross sectional views of the wing design.
The cross sectional segment is highlighted in red. Top left: frontal view with section locations indicated. Top right: sections taken from the frontal view. Bottom left: side elevation with section locations indicated. Bottom right: sections taken from the side elevation.
Fig 4.
A) Illustration of the computational domain used for the simulations of all models. Streamlines from a representative simulation are also included in the figure. Representative orientations, β, of the tag in plan view during the examination of off-axis flow are shown below panel A. B) Illustration of the experimental PIV setup used to measure the flow around the Model A design. The figure inset presents how the illuminated particles are used to measure the velocity of the fluid. The fluid flow in both cases is from left to right, and dimensions are in millimeters.
Fig 5.
Longitudinal cross-section views in 5.6 m/s inline flow with a color map corresponding to the speed of the fluid flow (V).
Areas of low speed are shown in blue, while areas of high speed are shown in red.
Fig 6.
Longitudinal cross-section views in 5.6 m/s inline flow with a color map corresponding to the coefficient of pressure (Cp).
Areas of low pressure are shown in green, while areas of high pressure are shown in red.
Table 1.
Component and net tag force contributions from the individual flow control elements for the Model A design in 5.6 m/s flow.
Fig 7.
Net drag and lift forces for each tag design in variable-speed inline flow.
At the higher speeds the wings generates a net downward force but also more drag. Less drag is created without the wing but the lift forces increase greatly. Second order polynomial fits (solid lines) were used to interpolate between simulation data points. Fitting parameters and R2 values are presented in Table 3.
Table 2.
Comparisons of peak forces and dimensionless force coefficients for the tag designs in 6 m/s aligned flow.
Adding the wing increases the drag coefficient (Cd) but decreases the lift coefficient (Cl). This results in a negative efficiency (E) indicating that the Model A design creates a net downforce.
Table 3.
Coefficients and R2 values for the second order polynomial fits presented in Fig 7.
Fig 8.
Net drag and lift forces for the Model A tag in off-axis 5.6 m/s flow.
Simulation results for four orientations (0°, 30°, 45° and 90°) with the corresponding stream lines and color map of the resulting pressure field acting on a transverse plane parallel to the attachment surface.
Fig 9.
Comparison of simulated (A) and experimental (B) coefficients of pressure (Cp) acting on the Model A tag. The experimental measurements were made using particle image velocimetry and compare well to the simulated results. This agreement is highlighted by the small differences in coefficients of pressure (Cpdiff) presented in subplot (C). The black mask shown in (A), (B) and (C) identify areas that were shadowed in the PIV measurements.