We perform Global Sensitivity Analysis (GSA) through Polynomial Chaos Expansion (PCE) to evaluate the relative influence of the parameters and boundary conditions that control key processes described by two popular models adopted to interpret conservative transport in laboratory-scale columns filled with uniform porous material. We consider one-dimensional transport scenarios depicted by (a) the classical Advection Dispersion Equation (ADE) and (b) a dual-porosity model with mass transfer between mobile and immobile regions. The PCE allows (a) quantifying with acceptable computational burden the way parametric uncertainty propagates to system states through these selected models and (b) identifying space-time locations where the adopted models are most sensitive to the corresponding parameters. Designing of laboratory-scale column experiments on the basis of the methodology we propose can lead to robust estimates of the parameters of the selected transport models.
V. Ciriello, V. Di Federico, A. Guadagnini (2012). Sensitivity analysis of conservative transport models for uniform porous media. COSENZA : EdiBios.
Sensitivity analysis of conservative transport models for uniform porous media
CIRIELLO, VALENTINA;DI FEDERICO, VITTORIO;
2012
Abstract
We perform Global Sensitivity Analysis (GSA) through Polynomial Chaos Expansion (PCE) to evaluate the relative influence of the parameters and boundary conditions that control key processes described by two popular models adopted to interpret conservative transport in laboratory-scale columns filled with uniform porous material. We consider one-dimensional transport scenarios depicted by (a) the classical Advection Dispersion Equation (ADE) and (b) a dual-porosity model with mass transfer between mobile and immobile regions. The PCE allows (a) quantifying with acceptable computational burden the way parametric uncertainty propagates to system states through these selected models and (b) identifying space-time locations where the adopted models are most sensitive to the corresponding parameters. Designing of laboratory-scale column experiments on the basis of the methodology we propose can lead to robust estimates of the parameters of the selected transport models.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.