Evaluation of hydraulic conductivity of reconstructed granular media generated using low-order probability functions

Tae Sup Yun, Tongseok Han, Sang Yeop Chung, Guillermo A. Narsilio

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

The hydraulic conductivity of three-dimensional artificial two-phase (fluid phase and solid phase) models with varying solid clustering sizes are evaluated to explore the effect of phase clustering, using low-order probability functions. The original random and heterogeneous microstructure models are made by placing randomly dispersed voxels with varying clustering sizes and the same porosity. The two-point correlation and lineal-path functions are applied to extract characteristics of phase clustering. The reconstructed models whose low-order probability functions are analogous to the original models are then made by a stochastic optimization process. This process allows one to generate equivalent reconstructed models to the original microstructure. The hydraulic conductivity values of both original and reconstructed models along three perpendicular directions are evaluated by solving Navier-Stoke's equation and averaging local velocity values of fluids with the aid of finite element scheme. Results are analyzed to evaluate the applicability of reconstruction approach depending on the phase clustering. The fluid flow through porous media is further examined with the observation of flow resistance and percolation path. The effects of anisotropy of the fluid phase are also discussed to explore the applicability of stochastic optimization process. It is concluded that the low-order probabilistic functions provide an efficient tool to reconstruct three dimensional microstructures up to certain degree of clustering sizes and to simulate the flow behavior in porous media.

Original languageEnglish
Pages (from-to)132-141
Number of pages10
JournalKSCE Journal of Civil Engineering
Volume18
Issue number1
DOIs
Publication statusPublished - 2014 Jan 1

Fingerprint

Hydraulic conductivity
Microstructure
Fluids
Porous materials
Navier Stokes equations
Flow of fluids
Anisotropy
Porosity

All Science Journal Classification (ASJC) codes

  • Civil and Structural Engineering

Cite this

@article{3922c8a178294bf8bac2bc629ce4f15e,
title = "Evaluation of hydraulic conductivity of reconstructed granular media generated using low-order probability functions",
abstract = "The hydraulic conductivity of three-dimensional artificial two-phase (fluid phase and solid phase) models with varying solid clustering sizes are evaluated to explore the effect of phase clustering, using low-order probability functions. The original random and heterogeneous microstructure models are made by placing randomly dispersed voxels with varying clustering sizes and the same porosity. The two-point correlation and lineal-path functions are applied to extract characteristics of phase clustering. The reconstructed models whose low-order probability functions are analogous to the original models are then made by a stochastic optimization process. This process allows one to generate equivalent reconstructed models to the original microstructure. The hydraulic conductivity values of both original and reconstructed models along three perpendicular directions are evaluated by solving Navier-Stoke's equation and averaging local velocity values of fluids with the aid of finite element scheme. Results are analyzed to evaluate the applicability of reconstruction approach depending on the phase clustering. The fluid flow through porous media is further examined with the observation of flow resistance and percolation path. The effects of anisotropy of the fluid phase are also discussed to explore the applicability of stochastic optimization process. It is concluded that the low-order probabilistic functions provide an efficient tool to reconstruct three dimensional microstructures up to certain degree of clustering sizes and to simulate the flow behavior in porous media.",
author = "Yun, {Tae Sup} and Tongseok Han and Chung, {Sang Yeop} and Narsilio, {Guillermo A.}",
year = "2014",
month = "1",
day = "1",
doi = "10.1007/s12205-013-0381-2",
language = "English",
volume = "18",
pages = "132--141",
journal = "KSCE Journal of Civil Engineering",
issn = "1226-7988",
publisher = "Korean Society of Civil Engineers",
number = "1",

}

Evaluation of hydraulic conductivity of reconstructed granular media generated using low-order probability functions. / Yun, Tae Sup; Han, Tongseok; Chung, Sang Yeop; Narsilio, Guillermo A.

In: KSCE Journal of Civil Engineering, Vol. 18, No. 1, 01.01.2014, p. 132-141.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Evaluation of hydraulic conductivity of reconstructed granular media generated using low-order probability functions

AU - Yun, Tae Sup

AU - Han, Tongseok

AU - Chung, Sang Yeop

AU - Narsilio, Guillermo A.

PY - 2014/1/1

Y1 - 2014/1/1

N2 - The hydraulic conductivity of three-dimensional artificial two-phase (fluid phase and solid phase) models with varying solid clustering sizes are evaluated to explore the effect of phase clustering, using low-order probability functions. The original random and heterogeneous microstructure models are made by placing randomly dispersed voxels with varying clustering sizes and the same porosity. The two-point correlation and lineal-path functions are applied to extract characteristics of phase clustering. The reconstructed models whose low-order probability functions are analogous to the original models are then made by a stochastic optimization process. This process allows one to generate equivalent reconstructed models to the original microstructure. The hydraulic conductivity values of both original and reconstructed models along three perpendicular directions are evaluated by solving Navier-Stoke's equation and averaging local velocity values of fluids with the aid of finite element scheme. Results are analyzed to evaluate the applicability of reconstruction approach depending on the phase clustering. The fluid flow through porous media is further examined with the observation of flow resistance and percolation path. The effects of anisotropy of the fluid phase are also discussed to explore the applicability of stochastic optimization process. It is concluded that the low-order probabilistic functions provide an efficient tool to reconstruct three dimensional microstructures up to certain degree of clustering sizes and to simulate the flow behavior in porous media.

AB - The hydraulic conductivity of three-dimensional artificial two-phase (fluid phase and solid phase) models with varying solid clustering sizes are evaluated to explore the effect of phase clustering, using low-order probability functions. The original random and heterogeneous microstructure models are made by placing randomly dispersed voxels with varying clustering sizes and the same porosity. The two-point correlation and lineal-path functions are applied to extract characteristics of phase clustering. The reconstructed models whose low-order probability functions are analogous to the original models are then made by a stochastic optimization process. This process allows one to generate equivalent reconstructed models to the original microstructure. The hydraulic conductivity values of both original and reconstructed models along three perpendicular directions are evaluated by solving Navier-Stoke's equation and averaging local velocity values of fluids with the aid of finite element scheme. Results are analyzed to evaluate the applicability of reconstruction approach depending on the phase clustering. The fluid flow through porous media is further examined with the observation of flow resistance and percolation path. The effects of anisotropy of the fluid phase are also discussed to explore the applicability of stochastic optimization process. It is concluded that the low-order probabilistic functions provide an efficient tool to reconstruct three dimensional microstructures up to certain degree of clustering sizes and to simulate the flow behavior in porous media.

UR - http://www.scopus.com/inward/record.url?scp=84891663237&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84891663237&partnerID=8YFLogxK

U2 - 10.1007/s12205-013-0381-2

DO - 10.1007/s12205-013-0381-2

M3 - Article

VL - 18

SP - 132

EP - 141

JO - KSCE Journal of Civil Engineering

JF - KSCE Journal of Civil Engineering

SN - 1226-7988

IS - 1

ER -