Dispersivity and velocity relationship from laboratory and field experiments

Klotz, D.; Seiler, Klaus-Peter; Moser, H. C.; Neumaier, F.

doi:10.1016/0022-1694(80)90018-9

Cited by 133 publications

(54 citation statements)

References 3 publications

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“…Level set percolation [20,21] is used to generate the porous media. Each node on a three dimensional regular grid is assigned an independent identically distributed random value sampled from a uniform distribution on the closed interval [0,1]. This random field is convolved with a symmetric Gaussian kernel to generate an isotropic correlated random topography.…”

Section: A Pore Space Constructionmentioning

confidence: 99%

“…The ability to investigate details of flow within a pore network is important as it can guide applications ranging from design of engineered materials to evaluation of environmental risks. Detailed predictions of fluxes in pore networks can be limited by observational constraints and analytical inadequacies in dealing with complex boundary conditions arising from variable material properties [1][2][3][4]. Computational experiments are alternatives for investigating detailed characteristics of flow within networks of pores and can yield detailed velocity and pressure fields in complex pore spaces [5][6][7][8][9][10][11][12][13][14][15][16][17][18][19].…”

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confidence: 99%

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Heterogeneities of flow in stochastically generated porous media

2012

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Heterogeneous flows are observed to result from variations in the geometry and topology of pore structures within stochastically generated three dimensional porous media. A stochastic procedure generates media comprised of complex networks of connected pores. Inside each pore space, the Navier-Stokes equations are numerically integrated until steady state velocity and pressure fields are attained. The intricate pore structures exert spatially variable resistance on the fluid, and resulting velocity fields have a wide range of magnitudes and directions. Spatially non-uniform fluid fluxes are observed, resulting in principal pathways of flow through the media. In some realizations, up to 25% of the flux occurs in 5% of the pore space depending on porosity. The degree of heterogeneity in the flow is quantified over a range of porosities by tracking particle trajectories and calculating their attributes including tortuosity, length, and first passage time. A representative elementary volume is first computed so the dependence of particle based attributes on the size of the domain through which they are followed is minimal. High correlations between the dimensionless quantities of porosity and tortuosity are calculated and a logarithmic relationship is proposed. As the porosity of a medium increases the flow field becomes more uniform.

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Section: A Pore Space Constructionmentioning

confidence: 99%

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confidence: 99%

Heterogeneities of flow in stochastically generated porous media

2012

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“…In this analysis,  L = 1.0 m and  T = 0.1 m are assumed because dispersivities are from 10 -2 to 1 cm for laboratory experiments and range from 10 -1 to 10 2 m for tracer test in the more heterogeneous porous materials typically encountered in the field [12]. D 0 is ignored in respect of high velocity.…”

Section: +mentioning

confidence: 99%

Effect of Climatic Change on Groundwater Quality Around the Subsurface Dam

Adham¹,

Kobayashi²,

Murakami³

2011

geomate

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ABSTRACT:The effect of climatic change on groundwater quality around subsurface dam area has been observed using numerical simulation. The study is related to sustainable groundwater development from subsurface dams constructed in the south islands of Japan where limestone is the underground geology. The model includes dispersion/diffusion, advection, ion exchange, formation of complexes in the aqueous phase, and the dissociation of water. The mass action, transport, and site action equations are expressed in a differential/algebraic form and solved by FEM. Results reveal that dissolution of limestone is proportional to the acidification of rainwater i.e. inversely proportional to the pH of rainwater. The resulting increase in calcium ion concentration is expected to block the filter of the pumping well and deteriorate the quality of groundwater as well. Again, dissolution of limestone is proportional to the increase of intensity of rain that leads to the increase of velocity of water. Dissolution of limestone was inversely proportional to the temperature.

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“…Hence the magnitude of transverse dispersivity is directly associated not only with the shape of plume but also with the attenuation of tracer concentration. Laboratory values of the ratio reported in the literature range from 0Ð04 to 0Ð2 (Anderson, 1979;Freeze and Cherry, 1979;Klotz et al, 1980). In contrast, field values obtained from natural gradient dispersion tests have been as low as 0Ð002 (Jensen et al, 1993) and as high as 0Ð1 (Moltyaner and Killey, 1988a).…”

Section: Introductionmentioning

confidence: 98%

“…As an alternative, a laboratory experiment was used to acquire dispersive parameters, and its results scaled upward to the field regime. Laboratory column tests in combination with field tracer tests have been performed in the past to investigate the applicability of laboratory-derived dispersive parameters to field conditions (Klotz et al, 1980), to examine the scale-dependent nature of dispersive parameters (Pickens and Grisak, 1981) and to compare laboratory results with field values (Taylor et al, 1987). However, the early works (Dagan, 1986;Gelhar, 1986) showed that the field-scale macrodispersion is affected by parameters including the integral scale of the log-conductivity and variance and thus cannot be assessed from the laboratory-scale experiment, which provides only a local dispersion.…”

Section: Introductionmentioning

confidence: 99%

Determination of two‐dimensional laboratory‐scale dispersivities

Kim

et al. 2004

Hydrological Processes

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Abstract:A tracer test was conducted in a laboratory chamber representing a two-dimensional aquifer to investigate the longitudinal dispersivity ˛L and the ratio ˛T/˛L of transverse to longitudinal dispersivity of sandy aquifer materials. Dispersive parameters were obtained by matching the observed chloride plumes at 9 hours and 16 hours after tracer injection with those simulated by a flow and transport model. The best match was found for˛L D 0Ð2 0Ð25 cm and˛T/˛L D 0Ð2. The ratio of˛T/˛L D 0Ð2 was within the range of laboratory values reported in the literature. Sensitivity analysis revealed that the tracer plume concentration and shape were more sensitive to variations in longitudinal dispersivity than to the ratio of transverse to longitudinal dispersivity. This result contrasted with findings of others, showing that the dispersivity ratio greatly affects contaminant plume shape. However, our experimental boundary conditions restricted expansion of the plume normal to the direction of flow and thus affected the parameter estimation.

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Dispersivity and velocity relationship from laboratory and field experiments

Cited by 133 publications

References 3 publications

Heterogeneities of flow in stochastically generated porous media

Heterogeneities of flow in stochastically generated porous media

Effect of Climatic Change on Groundwater Quality Around the Subsurface Dam

Determination of two‐dimensional laboratory‐scale dispersivities

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