scholarly journals Correction: Wright, E.E., et al. Upscaling Mixing in Highly Heterogeneous Porous Media via a Spatial Markov Model. Water 2019, 11, 53

Water ◽  
2020 ◽  
Vol 12 (8) ◽  
pp. 2194
Author(s):  
Elise E. Wright ◽  
Nicole L. Sund ◽  
David H. Richter ◽  
Giovanni M. Porta ◽  
Diogo Bolster
Keyword(s):  
Porous Media ◽  
Markov Model ◽  
Heterogeneous Porous Media ◽  
Model Water

The authors wish to make the following corrections to this paper [...]

scholarly journals Upscaling Mixing in Highly Heterogeneous Porous Media via a Spatial Markov Model

Water ◽  
2018 ◽  
Vol 11 (1) ◽  
pp. 53 ◽  
Author(s):  
Elise Wright ◽  
Nicole Sund ◽  
David Richter ◽  
Giovanni Porta ◽  
Diogo Bolster
Keyword(s):  
Porous Media ◽  
Markov Model ◽  
Heterogeneous Porous Media ◽  
Lagrangian Model ◽  
Small Scale ◽  
Heterogeneous Porous Medium ◽  
The Mean ◽  
Fully Resolved Simulation ◽  
Solute Mixing ◽  
Good Agreement

In this work, we develop a novel Lagrangian model able to predict solute mixing in heterogeneous porous media. The Spatial Markov model has previously been used to predict effective mean conservative transport in flows through heterogeneous porous media. In predicting effective measures of mixing on larger scales, knowledge of only the mean transport is insufficient. Mixing is a small scale process driven by diffusion and the deformation of a plume by a non-uniform flow. In order to capture these small scale processes that are associated with mixing, the upscaled Spatial Markov model must be extended in such a way that it can adequately represent fluctuations in concentration. To address this problem, we develop downscaling procedures within the upscaled model to predict measures of mixing and dilution of a solute moving through an idealized heterogeneous porous medium. The upscaled model results are compared to measurements from a fully resolved simulation and found to be in good agreement.

Sign in / Sign up

Export Citation Format

Share Document