A New Method for Laboratory Estimation of the Transverse Dispersion Coefficient
Identifieur interne : 001D38 ( Main/Exploration ); précédent : 001D37; suivant : 001D39A New Method for Laboratory Estimation of the Transverse Dispersion Coefficient
Auteurs : Marco Massab [Italie] ; Federico Catania [Italie] ; Ombretta Paladino [Italie]Source :
- Groundwater [ 0017-467X ] ; 2007-05.
Descripteurs français
- KwdFr :
- MESH :
- analyse : Eau, Sol.
- Algorithmes, Cinétique, Diffusion, Eau, Modèles théoriques, Mouvements de l'eau.
English descriptors
- KwdEn :
- MESH :
- chemical , analysis : Soil, Water.
- chemical , chemistry : Water.
- Algorithms, Diffusion, Kinetics, Models, Theoretical, Water Movements.
Abstract
We introduce a method for identifying the transverse dispersion coefficient in laboratory experiments based on the analytical solution of a pulse injection of a nonreactive solute in a soil column (cylindrical geometry) packed with a homogeneous porous medium. This method takes into account the effect of boundary conditions such as no flux on the column perimeter, and it does not need a priori knowledge of the longitudinal dispersion coefficient. Numerical applications of the method show that it is stable and robust and that the results are reasonably in accordance with those found using the classical maximum likelihood method.
Url:
DOI: 10.1111/j.1745-6584.2007.00301.x
Affiliations:
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Le document en format XML
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<front><div type="abstract" xml:lang="en">We introduce a method for identifying the transverse dispersion coefficient in laboratory experiments based on the analytical solution of a pulse injection of a nonreactive solute in a soil column (cylindrical geometry) packed with a homogeneous porous medium. This method takes into account the effect of boundary conditions such as no flux on the column perimeter, and it does not need a priori knowledge of the longitudinal dispersion coefficient. Numerical applications of the method show that it is stable and robust and that the results are reasonably in accordance with those found using the classical maximum likelihood method.</div>
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