Keywords
parameter estimation, column outflow experiments, solute transport
Start Date
1-7-2004 12:00 AM
Abstract
In this paper some analytical solutions of the advection-dispersion equation are proposed andadopted to solve a non-linear parameter estimation problem. To test the robustness of the analyticalsolutions if adopted in inverse problems, the anisotropic dispersion coefficients are estimated using sets ofexperimental data simulated by Monte Carlo techniques. Cylindrical geometry is considered since largecolumns are the most common devices adopted to study both dispersion and kinetics mechanisms and, evenif the solutions are expressed in terms of Bessel function expansion and equations solved only for particularinitial and boundary conditions, they give very good results in terms of reliability and precision of ourestimates. Discussion of results is based on the analysis of residuals, variance-covariance matrix and biasof parameters. The influence of location and time of sampling, number of samples and data uncertainty onthe dispersion coefficients estimates is also analyzed by means of ANOVA tests.
Parameters Estimation Using Some Analytical Solutions of the Anisotropic Advection-dispersion Model
In this paper some analytical solutions of the advection-dispersion equation are proposed andadopted to solve a non-linear parameter estimation problem. To test the robustness of the analyticalsolutions if adopted in inverse problems, the anisotropic dispersion coefficients are estimated using sets ofexperimental data simulated by Monte Carlo techniques. Cylindrical geometry is considered since largecolumns are the most common devices adopted to study both dispersion and kinetics mechanisms and, evenif the solutions are expressed in terms of Bessel function expansion and equations solved only for particularinitial and boundary conditions, they give very good results in terms of reliability and precision of ourestimates. Discussion of results is based on the analysis of residuals, variance-covariance matrix and biasof parameters. The influence of location and time of sampling, number of samples and data uncertainty onthe dispersion coefficients estimates is also analyzed by means of ANOVA tests.
