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2006, Water Resources Research
Longitudinal dispersion coefficients in given realizations of the transport computed by two currently used approximations of the first-order in velocity variance are compared with accurate global random walk simulations. The comparisons are performed for the same ensemble of realizations of the Darcy velocity field, approximated by a quasi-periodic random field, for log-normal hydraulic conductivity with small variance and finite correlation lengths. The results show that, at finite times of about one dispersion time scale, the mean coefficient is underestimated by ≈ 20% and the fluctuations are overestimated by ≈ 80%. At larger times the errors decrease monotonously and the first-order approximations yield fairly good predictions for the mean and the fluctuations of the dispersion coefficient.
Water Resources Research, 2002
The basic conceptual picture and theoretical basis for development of transport equations in porous media are examined. The general form of the governing equations is derived for conservative chemical transport in heterogeneous geological formations, for single realizations and for ensemble averages of the domain. The application of these transport equations is focused on accounting for the appearance of non-Fickian (anomalous) transport behavior. The general ensemble-averaged transport equation is shown to be equivalent to a continuous time random walk (CTRW) and reduces to the conventional forms of the advection-dispersion equation (ADE) under highly restrictive conditions. Fractional derivative formulations of the transport equations, both temporal and spatial, emerge as special cases of the CTRW. In particular, the use in this context of Lévy flights is critically examined. In order to determine chemical transport in field-scale situations, the CTRW approach is generalized to non-stationary systems. We outline a practical numerical scheme, similar to those used with extended geological models, to account for the often important effects of unresolved heterogeneities. * Electronic address: brian.berkowitz@weizmann.ac.il † Electronic address: klafter@post.tau.ac.il ‡ Electronic address: metz@nordita.dk § Electronic address: harvey.scher@weizmann.ac.il
Water Resources Research, 2016
We derive a general formulation of the time domain random walk (TDRW) approach to model the hydrodynamic transport of inert solutes in complex geometries and heterogeneous media. We demonstrate its formal equivalence with the discretized advection-dispersion equation and show that the TDRW is equivalent to a continuous time random walk (CTRW) characterized by space-dependent transition times and transition probabilities. The transition times are exponentially distributed. We discuss the implementation of different concentration boundary conditions and initial conditions as well as the occurrence of numerical dispersion. Furthermore, we propose an extension of the TDRW scheme to account for mobile-immobile multirate mass transfer. Finally, the proposed TDRW scheme is validated by comparison to analytical solutions for spatially homogeneous and heterogeneous transport scenarios.
Water Resources Research, 1996
The random-walk method for simulating solute transport in porous media is typically based on the assumption that the velocity and velocity-dependent dispersion tensor vary smoothly in space. However, in cases where sharp interfaces separate materials with contrasting hydraulic properties, these quantities may be discontinuous. Normally, velocities are interpolated to arbitrary particle locations when finite difference or finite element methods are used to solve the flow equation. The use of interpolation schemes that preserve discontinuities in velocity at material contacts can result in a random-walk model that does not locally conserve mass unless a correction is applied at these contacts. Test simulations of random-walk particle tracking with and without special treatment of material contacts demonstrate the problem. Techniques for resolving the problem, including interpolation schemes and a reflection principle, are reviewed and tested. Results from simulations of transport in porous media with discontinuities in the dispersion tensor show which methods satisfy continuity. Simulations of transport in twodimensional heterogeneous porous media demonstrate the potentially significant effect of using a nonconservative model to compute spatial moments and breakthrough of a solute plume.
1] A new approach has been developed for solving solute transport problems in randomly heterogeneous media using the Karhunen-Loève-based moment equation (KLME) technique proposed by . The KLME approach combines the Karhunen-Loève decomposition of the underlying random conductivity field and the perturbative and polynomial expansions of dependent variables including the hydraulic head, flow velocity, dispersion coefficient, and solute concentration. The equations obtained in this approach are sequential, and their structure is formulated in the same form as the original governing equations such that any existing simulator, such as Modular Three-Dimensional Multispecies Transport Model for Simulation of Advection, Dispersion, and Chemical Reactions of Contaminants in Groundwater Systems (MT3DMS), can be directly applied as the solver. Through a series of two-dimensional examples, the validity of the KLME approach is evaluated against the classical Monte Carlo simulations. Results indicate that under the flow and transport conditions examined in this work, the KLME approach provides an accurate representation of the mean concentration. For the concentration variance, the accuracy of the KLME approach is good when the conductivity variance is 0.5. As the conductivity variance increases up to 1.0, the mismatch on the concentration variance becomes large, although the mean concentration can still be accurately reproduced by the KLME approach. Our results also indicate that when the conductivity variance is relatively large, neglecting the effects of the cross terms between velocity fluctuations and local dispersivities, as done in some previous studies, can produce noticeable errors, and a rigorous treatment of the dispersion terms becomes more appropriate.
2001
We present two-and three-dimensional calculations for the longitudinal and transverse macrodispersion coefficient for conservative solutes derived by particle tracking in a velocity field which is based on the linearized flow equation. The simulations were performed upto 5000 correlation lengths in order to reach the asymptotic regime. We used a simulation method which does not need any grid and therefore allows simulations of very large transport times and distances.
Progress in Computational Fluid Dynamics, An International Journal, 2008
Lattice Boltzmann models simulate solute transport in porous media traversed by conduits. Resulting solute breakthrough curves are fitted with Continuous Time Random Walk models. Porous media are simulated by damping flow inertia and, when the damping is large enough, a Darcy's Law solution instead of the Navier-Stokes solution normally provided by the lattice Boltzmann model is obtained. Anisotropic dispersion is incorporated using a directiondependent relaxation time. Our particular interest is to simulate transport processes outside the applicability of the standard Advection-Dispersion Equation (ADE) including eddy mixing in conduits. The ADE fails to adequately fit any of these breakthrough curves.
Journal of Scientific Computing, 2010
Solute transport in randomly heterogeneous porous media is commonly described by stochastic flow and advection-dispersion equations with a random hydraulic conductivity field. The statistical distribution of conductivity of engineered and naturally occurring porous material can vary, depending on its origin. We describe solutions of a three-dimensional stochastic advection-dispersion equation using a probabilistic collocation method (PCM) on sparse grids for several distributions of hydraulic conductivity. Three random distributions of log hydraulic conductivity are considered: uniform, Gaussian, and truncated Gaussian (beta). Log hydraulic conductivity is represented by a Karhunen-Loève (K-L) decomposition as a second-order random process with an exponential covariance function. The convergence of PCM has been demonstrated. It appears that the accuracy in both the mean and the standard deviation of PCM solutions can be improved by using the Jacobi-chaos representing the truncated Gaussian distribution rather than the Hermite-chaos for the Gaussian distribution. The effect of type of distribution and parameters such as the variance and correlation length of log hydraulic conductivity and dispersion coefficient on leading moments of the advection velocity and solute concentration was investigated.
Transport in Porous Media, 1999
The stochastic approach has been shown to be an excellent tool for the characterisation and analysis of velocity fields and transport processes through heterogeneous porous formations. The main results (linear theory) have been obtained for problems with simplified flow conditions, usually in the assumption of uniform in the average flow, but a great effort is spent to reach theoretical results for more complex situations. This paper deals with 2D heterogeneous aquifers subject to uniform recharge; the stochastic approach is adopted to characterise, as ensemble behaviour, the velocity field and transport processes of a nonreactive solute. The impact of transmissivity conditioning on solute particles’ trajectories is analysed and an application is carried out. The analytical formulations, obtained by a first order analysis, are compared to the one resulting from constant in the average hydraulic gradient, and their reliability is investigated with numerical tests performed by a Monte Carlo method. The result of this study is that strong non-stationarities are present in the flow and transport process. A detailed analysis shows that the theoretical results cannot be extended to cases with high heterogeneity level, unlike the uniform in the average flow fields.
Vadose Zone Journal, 2006
One-dimensional transport models that predict field-scale averaged solute fluxes are often used to estimate the risk of nonpoint source groundwater contamination by widespread surface-applied chemicals. However, within-field variability of soil hydraulic properties leads to lateral variation in local solute fluxes. When this smaller scale variability is characterized in a geostatistical sense, stochastic threedimensional flow and transport equations can be used to predict fieldscale averaged transport in terms of geostatistical parameters. We discuss the use of stochastic equations for the parameterization of equivalent one-dimensional models predicting averaged solute fluxes. First, we consider the equivalent one-dimensional convection dispersion model and the equivalent dispersivity, which characterizes the spreading of laterally averaged concentrations or solute fluxes. Second, we discuss the parameterization of a stream tube model to predict local transport variables (i.e., distributions of local concentrations and local arrival times) These local transport variables are shown to be important for predicting nonlinear local transport processes and useful for inversely inferring the spatial structure of soil properties. Stochastic flow and transport equations reveal a dependency of equivalent model parameters on transport distance and flow rate, which reflects the importance of smaller scale heterogeneities on field-scale transport. Approximate solutions of stochastic flow and transport equations are obtained for steady-state and uniform flow. The effect of transient flow conditions on transport is discussed. Throughout the paper we refer to experimental and numerical data that confirm or contradict results from stochastic flow and transport equations.
2002
Fickian assumptions are used in deriving the advection-dispersion equation which models the solute transport in porous media. The hydrodynamic dispersion coefficient defined as a result of these assumptions has been found to be scale dependent. Kulasiri and Verwoerd [1999] developed a stochastic computational model for solute transport in saturated porous media without using Fickian assumptions. The model consists of two main parameters; correlation length and variance, and the velocity of solute was assumed as a fundamental stochastic variable. In this paper, the stochastic model was investigated to understand its behaviour. As the statistical nature of the model changes with the parameters, the computational solution of the model was explored in relation to the parameters. The variance is found to be the dominant parameter, however, there is a cOlTelation between two parameters and they influence the stochasticity of the flow in a complex manner. We hypothesised that the variance ...
Monte Carlo Methods and Applications, 2009
A stochastic simulation method is developed for a numerical study of particle transport in random porous medium. The hydraulic conductivity is assumed to be a random field of a given statistical structure, the flow is modelled in a cylinder with prescribed boundary conditions. Numerical experiments are carried out by solving the random Darcy equation for each sample of the hydraulic conductivity by a SOR iteration method, and tracking Lagrangian trajectories in the simulated flow.
In this study we present a numerical analysis for the self-averaging of the longitudinal dispersion coefficient for transport in heterogeneous media. This is done by investigating the mean-square sample-to-sample fluctuations of the dispersion for finite times and finite numbers of modes for a quasi-periodic random field using analytical arguments as well as numerical simulations. We consider transport of point-like injections in a quasi-periodic random field with a Gaussian correlation function. In particular, we focus on the asymptotic and pre-asymptotic behaviour of the fluctuations with the aid of a probability density function for the dispersion, and we verify the logarithmic growth of the sample-tosample fluctuations as earlier reported in . We also comment on the choice of the relevant parameters to generate quasi-periodic realizations with respect to the self-averaging of transport in statistically homogeneous Gaussian velocity fields.
Computer experiments for diffusion and dispersion in a capillary tube have been used to learn something of the functional dependence of the dispersion vector and the dispersion coefficient. At short times we find the latter to be a function of time and strongly dependent on the concentration gradient.
Transport in Porous Media, 2016
Random walk (RW) methods are recurring Monte Carlo methods used to model convective and diffusive transport in complex heterogeneous media. Many applications can be found, including fluid mechanic, hydrology, and chemical reactors modeling. These methods are easy to implement, very versatile and flexible enough to become appealing for many applications because they generally overlook or deeply simplify the building of explicit complex meshes required by deterministic methods. RW provide a good physical understanding of the interactions between the space scales of heterogeneities and the transport phenomena under consideration. In addition, they can result in efficient up-scaling methods, especially in the context of flow and transport in fractured media. In the present study, we review the applications of RW to several situations that cope with diverse spatial scales, and different insights into up-scaling problems. The advantages and down-B.
Water Resources Research, 1996
Recently, an exact Eulerian-Lagrangian theory of advective transport in spacetime random velocity fields was developed by one of us. We present a formal extension of this theory that accounts for anisotropic local dispersion. The resultant (conditional) mean transport equation is generally nonlocal in space-time. To assess the impact of local dispersion on the prediction of transport under uncertainty, we adopt a first-order pseudo-Fickian approximation for this equation. We then solve it numerically by Galerkin finite elements for two-dimensional transport from an instantaneous square source in a uniform (unconditional) mean flow field subject to isotropic local dispersion. We use a higherorder approximation to compute explicitly the standard deviation and coefficient of variation of the predicted concentrations. Our theory shows (in an exact manner), and our numerical results demonstrate (under the above closure approximations), that the effect of local dispersion on first and second concentration moments varies monotonically with the magnitude of the local dispersion coefficient. When this coefficient is small relative to macrodispersion, its effect on the prediction of nonreactive transport under uncertainty can, for all practical purposes, be disregarded. This is contrary to some recent assertions in the literature that local dispersion must always be taken into account, no matter how small.
Water Resources Research, 2009
1] In this paper we present flow and travel time ensemble statistics based on a new simulation methodology, the adaptive Fup Monte Carlo method (AFMCM). As a benchmark case, we considered two-dimensional steady flow in a rectangular domain characterized by multi-Gaussian heterogeneity structure with an isotropic exponential correlation and lnK variance s Y 2 up to 8. Advective transport is investigated using the travel time framework where Lagrangian variables (e.g., velocity, transverse displacement, or travel time) depend on space rather than on time. We find that Eulerian and Lagrangian velocity distributions diverge for increasing lnK variance due to enhanced channeling. Transverse displacement is a nonnormal for all s Y 2 and control planes close to the injection area, but after xI Y = 20 was found to be nearly normal even for high s Y 2 . Travel time distribution deviates from the Fickian model for large lnK variance and exhibits increasing skewness and a power law tail for large lnK variance, the slope of which decreases for increasing distance from the source; no anomalous features are found. Second moment of advective transport is analyzed with respect to the covariance of two Lagrangian velocity variables: slowness and slope which are directly related to the travel time and transverse displacement variance, which are subsequently related to the longitudinal and transverse dispersion. We provide simple estimators for the Eulerian velocity variance, travel time variance, slowness, and longitudinal dispersivity as a practical contribution of this analysis. Both two-parameter models considered (the advection-dispersion equation and the lognormal model) provide relatively poor representations of the initial part of the travel time probability density function in highly heterogeneous porous media. We identify the need for further theoretical and experimental scrutiny of early arrival times, and the need for computing higher-order moments for a more accurate characterization of the travel time probability density function. A brief discussion is presented on the challenges and extensions for which AFMCM is suggested as a suitable approach.
International Journal of Rock Mechanics and Mining Sciences & Geomechanics Abstracts, 1992
isotropic l•orous media show that longitudinal macrodispersivity is a function of mean concentration and concentration gradient. The dependence of macrodispersivity on mean concentration and concentration gradient giv.es rise to a nonlinear mean solute transport equation. To evaluate this behavior, a one-dimensional finite difference formulation of the mean solute transport equation that incorporates the analytically derived expression for longitudinal macrodispersivity is used t.o simulate a step input problem. This approach allows effects of a spatially and temporally varying macrodispersivity on breakthrough curves to be observed and effects on dispersed-zone width to be calculated.
Advances in Water Resources, 2007
We investigate effective solute transport in a chemically heterogeneous medium subject to temporal fluctuations of the flow conditions. Focusing on spatial variations in the equilibrium adsorption properties, the corresponding fluctuating retardation factor is modeled as a stationary random space function. The temporal variability of the flow is represented by a stationary temporal random process. Solute spreading is quantified by effective dispersion coefficients, which are derived from the ensemble average of the second centered moments of the normalized solute distribution in a single disorder realization. Using first-order expansions in the variances of the respective random fields, we derive explicit compact expressions for the time behavior of the disorder induced contributions to the effective dispersion coefficients. Focusing on the contributions due to chemical heterogeneity and temporal fluctuations, we find enhanced transverse spreading characterized by a transverse effective dispersion coefficient that, in contrast to transport in steady flow fields, evolves to a disorder-induced macroscopic value (i.e., independent of local dispersion). At the same time, the asymptotic longitudinal dispersion coefficient can decrease. Under certain conditions the contribution to the longitudinal effective dispersion coefficient shows superdiffusive behavior, similar to that observed for transport in s stratified porous medium, before it decreases to its asymptotic value. The presented compact and easy to use expressions for the longitudinal and transverse effective dispersion coefficients can be used for the quantification of effective spreading and mixing in the context of the groundwater remediation based on hydraulic manipulation and for the effective modeling of reactive transport in heterogeneous media in general.
Fickian assumptions are used in deriving the advection-dispersion equation which models the solute transport in porous media. The hydrodynamic dispersion coefficient defined as a result of these assumptions has been found to be scale dependent. developed a stochastic computational model for solute transport in saturated porous media without using Fickian assumptions. The model consists of two main parameters; correlation length and variance, and the velocity of solute was assumed as a fundamental stochastic variable. In this paper, the stochastic model was investigated to understand its behaviour. As the statistical nature of the model changes with the parameters, the computational solution of the model was explored in relation to the parameters. The variance is found to be the dominant parameter, however, there is a correlation between two parameters and they influence the stochasticity of the flow in a complex manner. We hypothesised that the variance is inversely proportional to the pore size and the correlation length represents the geometry of flow. The computational results of different scales show that the hypotheses are reasonable. The model illustrates that it could capture the scale dependence of dispersivity and mimic the advection-dispersion equation in more deterministic situations.
Physical Review Letters, 2013
We study the intermittency of fluid velocities in porous media and its relation to anomalous dispersion. Lagrangian velocities measured at equidistant points along streamlines are shown to form a spatial Markov process. As a consequence of this remarkable property, the dispersion of fluid particles can be described by a continuous time random walk with correlated temporal increments. This new dynamical picture of intermittency provides a direct link between the microscale flow, its intermittent properties, and non-Fickian dispersion.
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