Projects per year
Abstract
The dispersion of a diffusive scalar in a fluid flowing through a network has many applications including to biological flows, porous media, water supply, and urban pollution. Motivated by this, we develop a large-deviation theory that predicts the evolution of the concentration of a scalar released in a rectangular network in the limit of large time t≫1. This theory provides an approximation for the concentration that remains valid for large distances from the center of mass, specifically for distances up to O(t) and thus much beyond the O(t1/2) range where a standard Gaussian approximation holds. A byproduct of the approach is a closed-form expression for the effective diffusivity tensor that governs this Gaussian approximation. Monte Carlo simulations of Brownian particles confirm the large-deviation results and demonstrate their effectiveness in describing the scalar distribution when t is only moderately large.
Original language | English |
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Article number | 114501 |
Number of pages | 7 |
Journal | Physical Review Letters |
Volume | 117 |
Issue number | 11 |
Early online date | 7 Sept 2016 |
DOIs | |
Publication status | Published - 9 Sept 2016 |
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Dive into the research topics of 'Dispersion in Rectangular Networks: Effective Diffusivity and Large-Deviation Rate Function'. Together they form a unique fingerprint.Projects
- 1 Finished
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Passive scalars in complex fluid flows: variability and extreme events
1/10/11 → 30/11/14
Project: Research
Datasets
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Scattering of inertial waves by random flows
Danioux, E. (Creator), Edinburgh DataShare, 1 Feb 2016
DOI: 10.7488/ds/1332, http://arxiv.org/abs/1510.00784
Dataset
Profiles
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Jacques Vanneste
- School of Mathematics - Personal Chair in Fluid Dynamics
Person: Academic: Research Active