1,720,972 research outputs found
Optimal sampling for the estimation of dispersion parameters in soil columns using an Iterative Genetic Algorithm
No full textIn groundwater modelling, an appropriate soil characterization is strongly recommended to evaluate both the fate and transport of solutes and the performance of groundwater remediation criteria, though parameter estimation techniques are often blocked by several inherent difficulties (i.e. ill-posedness and insufficient quantity and quality of observation data). In this paper, an iterative decision model is built and tested in order to locate the position of a fixed number of sample points in a soil column experiment to obtain optimal parameters estimation (OPE), minimizing the parameters uncertainty and the overall cost of the experimental campaign. Starting from an initial guess of chosen points (given by a fraction of the total disposable ones), an Iterative Genetic Algorithm (IGA) is capable to find the best points able to minimize a first-order approximation of the parameters covariance matrix. The parameter estimates are updated under a Bayesian point of view, using exclusively the observations collected after the earlier run of minimization, and the iterative process stops when the imposed convergence criterion based on the parameter values is reached. An important contribution of this work is the development of an effective direct search algorithm (IGA) for solving the sampling network optimization problem at a laboratory scale
Estimation of transport and kinetic parameters using analytical solutions of the 2D advection-dispersion-reaction model
No full textWe propose some analytical solutions of the advection-dispersion equation and adopt them to solve a non-linear parameter estimation problem. A solution with no reactive term and another one with a unique coefficient representing the kinetic mechanisms of the solute decay in groundwater are described in detail and are then considered in the estimation procedure. To test the robustness of these analytical solutions if adopted in inverse problems, the anisotropic dispersion and kinetics are estimated using sets of experimental data simulated by Monte Carlo techniques. Cylindrical geometry is considered since large columns are the most common devices adopted to study both
dispersion and kinetics mechanisms and, even if the solutions are expressed in terms of Bessel function expansion, they give very good results in terms of reliability and precision of our estimates. Discussion of results is based on the analysis of residuals, variance-covariance matrix and bias of parameters. The influence of location and time of sampling and of the number of samples on the estimates of dispersion and kinetic parameters is also analysed by means of Analysis of Variance and Fisher tests
Parameters estimation in pollutant dispersion into sorbing soils with low conductivity lenses
No full textParameters estimation using some analytical solutions of the anisotropic advection-dispersion model
No full textA new method for laboratory estimation of the transverse dispersion coefficient
No full textWe introduce a method for identifying the transverse dispersion coefficient in laboratory experiments based on the analytical solution of 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 perimetr, 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
Groundwater risk assessment of PCE at contaminated sites
No full textHuman risk assessment of a former industrial plant situated in the South of Italy is analyzed. Risk is estimated by simulating tetrachloroethylene (PCE) degradation and the formation of breakdown products. Transport of PCE, tri-chloroethylene (TCE), di-chloroethylene (DCE) and vinyl-chloride (VC) in groundwater is modelled accounting for sorption, dispersion and kinetics degradation within a time horizon of 90 years. Since reliable values of sorption parti-tioning coefficients and degradation kinetics are rarely avail-able at contaminated sites, risk is evaluated in several sce-narios in which the physical-chemical parameters values are varied according to literature values. The risk results are highly influenced by different but feasible scenarios, em-phasizing that reliable site specific field data are necessary to accurately assess the risk. Moreover, naturally occurring PCE degradation does not always result in a decreasing cancer risk with time and the human health risk can increase because of the formation of more toxic substances and, only after a really long time, attenuated by further degradation
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