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Ergodicity and invariant measures for a diffusing passive scalar advected by a random channel shear flow and the connection between the Kraichnan-Majda model and Taylor-Aris dispersion. (English) Zbl 1539.82350

Summary: We study the long time behavior of an advection-diffusion equation with a random shear flow which depends on a stationary Ornstein-Uhlenbeck (OU) process in parallel-plate channels enforcing the no-flux boundary conditions. We derive a closed form formula for the long time asymptotics of the arbitrary \(N\)-point correlator using the ground state eigenvalue perturbation approach proposed in [J. C. Bronski and R. M. McLaughlin, Phys. Fluids 9, No. 1, 181–190 (1997; Zbl 1185.76678)]. In turn, appealing to the conclusion of the Hausdorff moment problem [J. A. Shohat and J. D. Tamarkin, The problem of moments. Providence, RI: American Mathematical Society (AMS)(1943; Zbl 0063.06973)], we discover a diffusion equation with a random drift and deterministic enhanced diffusion possessing the exact same probability density function at long times. The strategy we presented is not only restricted to the parallel-plate channel domain. The same methods can derive effective equations for a straight channel with uniform arbitrary cross-section. Such equations enjoy many ergodic properties which immediately translate to ergodicity results for the original problem. In particular, we establish that the first two Aris moments using a single realization of the random field can be used to explicitly construct all ensemble averaged moments. Also, the first two ensemble averaged moments explicitly predict any long time centered Aris moment. Our formulae quantitatively depict the dependence of the deterministic effective diffusion on the interaction between spatial structure of flow and random temporal fluctuation. Further, this approximation provides many identities regarding the stationary OU process dependent time integral. We derive explicit formulae for the decaying passive scalar’s long time limiting probability density function (PDF) for different types of initial conditions (e.g. deterministic and random).

MSC:

82C70 Transport processes in time-dependent statistical mechanics
35Q82 PDEs in connection with statistical mechanics
76R50 Diffusion

References:

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