Combining the radial basis function Eulerian and Lagrangian schemes with geostatistics for modeling of radionuclide migration through the geosphere

To assess the long-term safety of a radioactive waste disposal system, mathematical models are used to describe groundwater flow, chemistry, and potential radionuclide migration through geological formations. A number of processes need to be considered, when predicting the movement of radionuclides through the geosphere. The most important input data are obtained from field measurements, which are not available for all regions of interest. For example, the hydraulic conductivity as an input parameter varies from place to place. In such cases, geostatistical science offers a variety of spatial estimation procedures. Methods for solving the solute transport equation can also be classified as Eulerian, Lagrangian and mixed. The numerical solution of partial differential equations (PDE) has usually been obtained by finite-difference methods (FDM), finite-element methods (FEM), or finite-volume methods (FVM). Kansa introduced the concept of solving partial differential equations using radial basis functions (RBF) for hyperbolic, parabolic, and elliptic PDEs. The aim of this study was to present a relatively new approach to the modeling of radionuclide migration through the geosphere using radial basis function methods in Eulerian and Lagrangian coordinates. In this study, we determine the average and standard deviation of radionuclide concentration with regard to variable hydraulic conductivity, which was modelled by a geostatistical approach. Radionuclide concentrations will also be calculated in heterogeneous and partly heterogeneous 2D porous media. (C) 2004 Elsevier Ltd. All rights reserved

Transport of ferrihydrite nanoparticles in saturated porous media: role of ionic strength and flow rate

The use of nanoscale ferrihydrite particles, which are known to effectively enhance microbial degradation of a wide range of contaminants, represents a promising technology for in situ remediation of contaminated aquifers. Thanks to their small size, ferrihydrite nanoparticles can be dispersed in water and directly injected into the subsurface to create reactive zones where contaminant biodegradation is promoted. Field applications would require a detailed knowledge of ferrihydrite transport mechanisms in the subsurface, but such studies are lacking in the literature. The present study is intended to fill this gap, focusing in particular on the influence of flow rate and ionic strength on particle mobility. Column tests were performed under constant or transient ionic strength, including injection of ferrihydrite colloidal dispersions, followed by flushing with particle-free electrolyte solutions. Particle mobility was greatly affected by the salt concentration, and particle retention was almost irreversible under typical salt content in groundwater. Experimental results indicate that, for usual ionic strength in European aquifers (2 to 5 mM), under natural flow condition ferrihydrite nanoparticles are likely to be transported for 5 to 30 m. For higher ionic strength, corresponding to contaminated aquifers, (e.g., 10 mM) the travel distance decreases to few meters. A simple relationship is proposed for the estimation of travel distance with changing flow rate and ionic strength. For future applications to aquifer remediation, ionic strength and injection rate can be used as tuning parameters to control ferrihydrite mobility in the subsurface and therefore the radius of influence during field injection

Nanoparticle transport in saturated porous medium using magnetic resonance imaging

Transport study of nanoparticle (NP) through matrix flow dominated aquifer sand and soils have significant influence in natural systems. To quantify the transport behaviour, magnetic resonance imaging (MRI) was used to image the iron oxide based nanoparticle, Molday ION (carboxyl terminated) through saturated sandstone rock core. T2-weighted images were acquired and the changes in image intensity were calibrated to get a quantitative concentration profiles at various time intervals. These profiles were evaluated through CXTFIT transport model to estimate the transport parameters. These parameters are estimated at various points along the length of the column while classical breakthrough curve analysis cannot provide these details. NP–surface interactions were investigated using DLVO (Derjaguin–Landau–Verwey–Overbeek) theory. The dispersion coefficients (2.55–1.21 × 10−7 m2/s) were found to be decrease with distance, deposition rate constant k (6.70–9.13 × 10−4 (1/s)) and fast deposition rate constant kfast (4.32–8.79 × 10−2 (1/s)) were found to be increase with distance. These parameter variations over length will have a scaling up impact in developing transport models for environmental remediation and risk assessment schemes

Optimum Identification of Dispersion Coefficients in Porous Media

Recently, the problem of predicting the movement of pollutants in groundwater has gained attentions. To solve such problems a number of numerical methods has been developed. But dispersion coefficients are always assumed to be a Known values, the result of such numerical approach then becomes questionable. In this paper, dispersion coefficients were investigated using laboratory column and sand aquifer tracer tests. Powell\u27s conjugate direction method was applied together with the error function type solution to obtain the dispersion coefficients. Powell\u27s method is efficient technique for the parameter identification of dispersion phenomena in porous media. Comparing the observed data and analytical solutions, obtained dispersion coefficients were reasonable