Estimation of laboratory-scale dispersivities using an annulus-and-core device

Frippiat, Christophe; Pérez, P. Conde; Holeyman, Alain

doi:10.1016/j.jhydrol.2008.08.007

Cited by 20 publications

(5 citation statements)

References 47 publications

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“…Observational techniques to derive dispersion coefficients are standardized [Grane, 1961;Harleman and Rumer, 1963;Perkins and Johnston, 1963;Blackwell, 1962;Hassinger and Von Rosenberg, 1968;Han et al, 1985;Robbins, 1989;Seagren et al, 1999;Klenk and Grathwohl, 2002;Eberhardt and Grathwohl, 2002;Cirpka et al, 2006;Benekos et al, 2006;Massabo et al, 2007;Frippiat et al, 2008]. However, observations that can distinguish between spreading and mixing and identify larger scale transport processes are restricted to unconsolidated sand or bead pack models.…”

Section: Introductionmentioning

confidence: 99%

Observations of the impact of rock heterogeneity on solute spreading and mixing

Boon

Bijeljic

Krevor

2017

Water Resources Research

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Rock heterogeneity plays an important role in solute spreading and mixing in hydrogeologic systems. Few observations, however, have been made that can spatially resolve these processes in 3-D, in consolidated rocks. We make observations of the spatially resolved steady state concentration of a sodium iodide solute while flowing brine through cylindrical rock cores using X-ray CT imaging. Three rocks with an increasing level of heterogeneity are chosen: a Berea sandstone, a Ketton carbonate, and an Indiana carbonate. The impact of heterogeneity on solute transport is analyzed by: (1) quantifying spreading and mixing using metrics such as the transverse dispersion coefficient, the dilution index, the reactor ratio, and the scalar dissipation rate and (2) visualizing and analyzing flow structures such as meandering, flow-focusing, and flow-splitting using isoconcentration contour maps. The transverse dispersion coefficient, D t , and the variation in D t throughout the rock core, increases with Pecl et number (Pe) and rock heterogeneity. The reactor ratio indicates that mixing is Fickian for the Berea sandstone and Ketton carbonate, but diverges for the Indiana carbonate. The temporal evolution of the scalar dissipation rate, a measure of the mixing rate, remains close to that of Fickian mixing for the Berea and Ketton rocks but not for the Indiana. Heterogeneous rock features are observed to cause meandering, focusing, or splitting of the plume depending on Pe.

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Section: Introductionmentioning

confidence: 99%

Observations of the impact of rock heterogeneity on solute spreading and mixing

Boon

Bijeljic

Krevor

2017

Water Resources Research

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“…The simulations of the tests on the other samples (sample 1, 3, 4) are performed with the calibrated values from the simulation of the test on sample 2. Case3 5e-3, (-) [18] Constitutive parameters (Eqs. 6, 17)…”

Section: Model Set-upmentioning

confidence: 99%

Micro-feature-motivated numerical analysis of the coupled bio-chemo-hydro-mechanical behaviour in MICP

Wang

Nackenhorst

2022

Acta Geotech.

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A coupled bio-chemo-hydro-mechanical model (BCHM) is developed to investigate the permeability reduction and stiffness improvement in soil by microbially induced calcite precipitation (MICP). Specifically, in our model based on the geometric method a link between the micro- and macroscopic features is generated. This allows the model to capture the macroscopic material property changes caused by variations in the microstructure during MICP. The developed model was calibrated and validated with the experimental data from different literature sources. Besides, the model was applied in a scenario simulation to predict the hydro-mechanical response of MICP-soil under continuous biochemical, hydraulic and mechanical treatments. Our modelling study indicates that for a reasonable prediction of the permeability reduction and stiffness improvement by MICP in both space and time, the coupled BCHM processes and the influences from the microstructural aspects should be considered. Due to its capability to capture the dynamic BCHM interactions in flexible settings, this model could potentially be adopted as a designing tool for real MICP applications.

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“…In many investigations, dispersivity is estimated through adjustments until the modeled concentrations best approximate observed concentrations [2][3][4][5][6][7][8][9][10][11][12]. An alternative approach to estimating dispersivity is through field and laboratory experiments conducted at different spatial scales [12][13][14][15][16][17][18][19][20][21][22]. However, field tracer tests are often time-consuming and very expensive.…”

Section: Introductionmentioning

confidence: 99%

Determination of Contaminant Transport Parameters for a Local Aquifer by Numerical Modeling of Two Plumes: Trichloroethylene and Hexavalent Chromium

Ibn Salam,

Waldron,

Schoefernacker

et al. 2024

Hydrology

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The municipal wellfield in Collierville, Tennessee, is contaminated with trichloroethylene (TCE) and hexavalent chromium (Cr (VI)) due to industrial operations dating back to the 1970s and 1980s. This study aims to elucidate the aquifer’s contaminant transport mechanisms by determining longitudinal and transverse dispersivities through inverse modeling. Utilizing MT3DMS for contaminant transport simulation, based on a well-calibrated groundwater flow model, and leveraging Python’s multiprocessing library for efficiency, the study employs a trial-and-error methodology. Key findings reveal that longitudinal dispersivity values range from 5.5 m near the source to 20.5 m further away, with horizontal and vertical transverse dispersivities between 0.28 m and 3.88 m and between 0.03 m and 0.08 m, respectively. These insights into the aquifer’s dispersivity coefficients, which reflect the scale-dependent nature of longitudinal dispersivity, are crucial for optimizing remediation strategies and achieving cleanup goals. This study underscores the importance of accurate parameter estimation in contaminant transport modeling and contributes to a better understanding of contaminant dynamics in the Collierville wellfield.

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Estimation of laboratory-scale dispersivities using an annulus-and-core device

Cited by 20 publications

References 47 publications

Observations of the impact of rock heterogeneity on solute spreading and mixing

Observations of the impact of rock heterogeneity on solute spreading and mixing

Micro-feature-motivated numerical analysis of the coupled bio-chemo-hydro-mechanical behaviour in MICP

Determination of Contaminant Transport Parameters for a Local Aquifer by Numerical Modeling of Two Plumes: Trichloroethylene and Hexavalent Chromium

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