2014
DOI: 10.1103/physreve.90.063012
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Anomalous transport and chaotic advection in homogeneous porous media

Abstract: The topological complexity inherent to all porous media imparts persistent chaotic advection under steady flow conditions, which, in concert with the no-slip boundary condition, generates anomalous transport. We explore the impact of this mechanism upon longitudinal dispersion via a model random porous network and develop a continuous-time random walk that predicts both preasymptotic and asymptotic transport. In the absence of diffusion, the ergodicity of chaotic fluid orbits acts to suppress longitudinal disp… Show more

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Cited by 36 publications
(39 citation statements)
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“…This result is generic to any macroscopic concentration distribution, hence exponentially accelerated mixing persists in both heterogeneous and homogeneous media. Likewise macroscopic longitudinal dispersion is also strongly augmented by chaotic advection (Lester et al 2014). These results have significant implications for the development of macroscopic models of dispersion and dilution which recover the pore-scale mechanisms which arise from chaotic mixing in 3D porous media.…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…This result is generic to any macroscopic concentration distribution, hence exponentially accelerated mixing persists in both heterogeneous and homogeneous media. Likewise macroscopic longitudinal dispersion is also strongly augmented by chaotic advection (Lester et al 2014). These results have significant implications for the development of macroscopic models of dispersion and dilution which recover the pore-scale mechanisms which arise from chaotic mixing in 3D porous media.…”
Section: Discussionmentioning
confidence: 99%
“…While the impact of broad transit time distributions on the spatial spreading of transported elements is well understood, their control on mixing dynamics is still an open question. As shown in (Lester et al 2014), Lagrangian chaos generates ergodic particle trajectories at the pore-scale, and the associated decaying correlations allows the advection process to be modelled as a stochastic process. During advection through the pore-space, fluid elements undergo punctuated stretching and folding (transverse to the mean flow direction) events at stagnation points, leading to persistent chaotic advection in random porous media.…”
Section: Introductionmentioning
confidence: 99%
“…These phenomena persist in the presence of additional pore-scale features outlined above [26], which only act to alter the quantitative aspects of transport and dispersion. As the network model considered herein is the simplest representation of porous media with non-trivial pore-scale topology (which is common to all porous media), we contend that the qualitative transport dynamics of this model are universal.…”
Section: Flow and Transport In A Model Open Porous Networkmentioning
confidence: 97%
“…In Lester et al [26] we formalized this CTRW in terms of the displacements ∆x and transition times ∆t over each pore branch and merge element of the flow (shown in Figure 6) which are populated from the CFD computations outlined in Section 4. If we consider the evolution of a fluid particle propagating in the mean flow direction z, then in the absence of diffusion the longitudinal position z and residence time t of fluid particle evolves via the CTRW as t n+1 = t n + ∆t n ,…”
Section: Impact Of Chaotic Advection Upon Longitudinal Dispersionmentioning
confidence: 99%
“…In a Markov process the particle motion can be seen as a correlated continuous time random walk (CTRW). Using a correlated CTRW, several signatures of anomalous transport behavior were accurately reproduced such as the long tails of the first passage time distribution [6], the non-linear scaling of the second centered moment of the particles longitudinal and transverse displacements [3,6,8], the probability distribution function of the Lagrangian velocity increments for different time lags among others [1].…”
Section: Introductionmentioning
confidence: 97%