Random walk particle tracking simulations of non-Fickian transport in heterogeneous media
Abstract
Derivations of continuum nonlocal models of non-Fickian (anomalous) transport require assumptions that might limit their applicability. We present a particle-based algorithm, which obviates the need for many of these assumptions by allowing stochastic processes that represent spatial and temporal random increments to be correlated in space and time, be stationary or non-stationary, and to have arbitrary distributions. The approach treats a particle trajectory as a subordinated stochastic process that is described by a set of Langevin equations, which represent a continuous time random walk (CTRW). Convolution-based particle tracking (CBPT) is used to increase the computational efficiency and accuracy of these particle-based simulations. The combined CTRW-CBPT approach enables one to convert any particle tracking legacy code into a simulator capable of handling non-Fickian transport.
- Authors:
-
- Earth and Environmental Sciences Division, Los Alamos National Laboratory, Los Alamos, New Mexico (United States)
- Department of Environmental Sciences and Energy Research, Weizmann Institute of Science, Rehovot (Israel)
- Publication Date:
- OSTI Identifier:
- 21333909
- Resource Type:
- Journal Article
- Journal Name:
- Journal of Computational Physics
- Additional Journal Information:
- Journal Volume: 229; Journal Issue: 11; Other Information: DOI: 10.1016/j.jcp.2010.02.014; PII: S0021-9991(10)00087-2; Copyright (c) 2010 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved; Country of input: International Atomic Energy Agency (IAEA); Journal ID: ISSN 0021-9991
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS; ALGORITHMS; GRAPH THEORY; LANGEVIN EQUATION; PARTICLES; RANDOMNESS; SIMULATION; SIMULATORS; STOCHASTIC PROCESSES; TRANSPORT THEORY
Citation Formats
Srinivasan, G., Tartakovsky, D.M., Dentz, M., Viswanathan, H, Berkowitz, B, and Robinson, B A. Random walk particle tracking simulations of non-Fickian transport in heterogeneous media. United States: N. p., 2010.
Web. doi:10.1016/j.jcp.2010.02.014.
Srinivasan, G., Tartakovsky, D.M., Dentz, M., Viswanathan, H, Berkowitz, B, & Robinson, B A. Random walk particle tracking simulations of non-Fickian transport in heterogeneous media. United States. https://doi.org/10.1016/j.jcp.2010.02.014
Srinivasan, G., Tartakovsky, D.M., Dentz, M., Viswanathan, H, Berkowitz, B, and Robinson, B A. 2010.
"Random walk particle tracking simulations of non-Fickian transport in heterogeneous media". United States. https://doi.org/10.1016/j.jcp.2010.02.014.
@article{osti_21333909,
title = {Random walk particle tracking simulations of non-Fickian transport in heterogeneous media},
author = {Srinivasan, G. and Tartakovsky, D.M. and Dentz, M. and Viswanathan, H and Berkowitz, B and Robinson, B A},
abstractNote = {Derivations of continuum nonlocal models of non-Fickian (anomalous) transport require assumptions that might limit their applicability. We present a particle-based algorithm, which obviates the need for many of these assumptions by allowing stochastic processes that represent spatial and temporal random increments to be correlated in space and time, be stationary or non-stationary, and to have arbitrary distributions. The approach treats a particle trajectory as a subordinated stochastic process that is described by a set of Langevin equations, which represent a continuous time random walk (CTRW). Convolution-based particle tracking (CBPT) is used to increase the computational efficiency and accuracy of these particle-based simulations. The combined CTRW-CBPT approach enables one to convert any particle tracking legacy code into a simulator capable of handling non-Fickian transport.},
doi = {10.1016/j.jcp.2010.02.014},
url = {https://www.osti.gov/biblio/21333909},
journal = {Journal of Computational Physics},
issn = {0021-9991},
number = 11,
volume = 229,
place = {United States},
year = {Tue Jun 01 00:00:00 EDT 2010},
month = {Tue Jun 01 00:00:00 EDT 2010}
}