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Integrated Computation of Finite Time Lyapunov Exponent During ...

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Definition and typical computation <strong>of</strong> the FTLE<br />

1 Release a grid <strong>of</strong> tracers and see where they go: This gives us the The flow map,<br />

Φ(x 0 , t 0 , )<br />

∫ t1<br />

Φ t 1<br />

t0<br />

(x 0 , t 0 ) = x 0 + u(x(τ), τ)dτ (1)<br />

t 0<br />

2 Differentiate the flow map W.R.T. x 0 : Then, compose the right Cauchy-Green deformation<br />

tensor, ∆<br />

⎡<br />

⎤∗ ⎡ ⎤<br />

∆ t 1<br />

t0<br />

(x 0 , t 0 ) = ⎣ dΦt 1<br />

t0<br />

(x 0 , t 0 )<br />

⎦ ⎣ dΦt 1<br />

t0<br />

(x 0 , t 0 )<br />

⎦ , (2)<br />

dx 0<br />

dx 0<br />

3 Determine the largest eigenvalue <strong>of</strong> this tensor. This is then used to compute the<br />

(maximum) FTLE field.<br />

√<br />

σ t 1<br />

1<br />

t0<br />

(x 0 , t 0 ) =<br />

|t 1 − t 0 | log λ max (∆ t 1<br />

t0<br />

(x 0 , t 0 )) (3)<br />

4 Detect FTLE ridges visually or analytically: Forward time ridges ⇒ repelling LCS<br />

candidates. Backward time ridges ⇒ attracting LCS candidates. Recent, more exact<br />

theory [Haller, 2011]<br />

Note: Separate computations for forward (t 1 > t 0 ) and backward (t 1 < t 0 ) time<br />

Note: Let T be the absolute value <strong>of</strong> the integration time, |t 1 − t 0 |<br />

We can then write forward and backward time T flow maps as Φ t 0+T<br />

t and Φ t 0−T<br />

0<br />

t 0<br />

Finn & Apte FTLE & DNS Integration 4

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