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==Initial Thoughts== Let's examine the elliptical trajectory of a Lagrangian particle that is moving in the equatorial plane of a Riemann S-Type ellipsoid. As viewed in a frame that is spinning about the Z-axis at angular frequency, <math>~\Omega</math>, the trajectory is defined by, <table align="center" border=0 cellpadding="3"> <tr> <td align="right"> <math> r^2 </math> </td> <td align="center"> <math> ~= </math> </td> <td align="left"> <math>~ \biggl(\frac{x}{a} \biggr)^2 + \biggl(\frac{y}{b}\biggr)^2 \, , </math> </td> </tr> </table> where <math>~0 < r \le 1</math>. (The surface of the relevant ellipsoid is associated with the value, <math>~r=1</math>.) Let's choose a pair of axis ratios — for example, <math>~b/a = 0.28</math> and <math>~c/a = 0.231</math> — then, from Table 1 of our [[#Models_Examined_by_Ou_.282006.29|above discussion]], draw the associated value of either <math>~\lambda</math> or <math>~\zeta</math> that corresponds to the Jacobi-like equilibrium configuration — in this example, <math>~\lambda = -0.04714</math> and <math>~\zeta = +0.18156</math>. Then, for any point <math>~(x,y)</math> inside of the ellipsoid, the fluid's velocity components (as viewed from the rotating frame of reference) are, <table align="center" border=0 cellpadding="3"> <tr> <td align="right"> <math> v_x = \frac{dx}{dt} = \lambda \biggl( \frac{ay}{b} \biggr) = -0.16836 ~y </math> </td> <td align="center"> and, </td> <td align="left"> <math>~ v_y = \frac{dy}{dt} = - \lambda \biggl( \frac{bx}{a} \biggr) = + 0.01320~x \, . </math> </td> </tr> </table> Alternatively, we have, <table align="center" border=0 cellpadding="3"> <tr> <td align="right"> <math> u_x = \frac{dx}{dt} = Q_1 y = - \biggl[ 1 + \frac{b^2}{a^2} \biggr]^{-1}\zeta ~y = -0.16836 ~y </math> </td> <td align="center"> and, </td> <td align="left"> <math>~ u_y = \frac{dy}{dt}= Q_2 x = + \biggl[ 1 + \frac{a^2}{b^2} \biggr]^{-1}\zeta ~x = + 0.01320~x \, . </math> </td> </tr> </table> Now, each Lagrangian fluid element's motion is oscillatory in both the <math>~x</math> and <math>~y</math> coordinate directions. So let's see how this plays out. Suppose, <table align="center" border=0 cellpadding="3"> <tr> <td align="right"> <math> x = x_\mathrm{max} \cos(\varphi t) </math> </td> <td align="center"> and, </td> <td align="left"> <math>~ y = y_\mathrm{max} \sin(\varphi t) \, . </math> </td> </tr> </table> Then, <table align="center" border=0 cellpadding="3"> <tr> <td align="right"> <math> \frac{dx}{dt} = - x_\mathrm{max}\varphi \sin(\varphi t) = - \biggl( \frac{x_\mathrm{max}}{y_\mathrm{max}}\biggr) \varphi y = - \varphi \biggl(\frac{ay}{b}\biggr) </math> </td> <td align="center"> and, </td> <td align="left"> <math>~ \frac{dy}{dt} = y_\mathrm{max} \varphi \cos(\varphi t) = + \biggl( \frac{y_\mathrm{max}}{x_\mathrm{max}}\biggr) \varphi x = + \varphi \biggl(\frac{bx}{a}\biggr) \, . </math> </td> </tr> </table> Hence our functional representation of the time-dependent behavior of both <math>~x</math> and <math>~y</math> works perfectly if, for each orbit inside of or on the surface of the configuration, we set <math>~\varphi = - \lambda</math> and if the ratio <math>~y_\mathrm{max}/x_\mathrm{max} = (b/a)</math>. Hooray!
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