AIChE Journal, Vol.55, No.8, 1959-1968, 2009
Reactive Transport Parameter Estimation: Genetic Algorithm vs. Monte Carlo Approach
This article concerns reactive transport in porous media with an emphasis on the optimization of the chemical parameters. The transport of Cadmium (Cd) and tributyltin (TBT) in column experiments were used as test cases. The reactive transport Model is described by a set of chemical reactions with equilibrium constants as the main adjustable parameters. As such a problem is highly nonlinear and can have multiple minima, global parameter estimation methods are more suitable than local gradient-based methods. This article focuses on the application of a genetic algorithm (GA) in estimating chemical equilibrium parameters of a reactive transport model. The GA is capable of minimizing the difference between the measured and modeled breakthrough curves for both Cd and TBT. A comparison between GA and Monte-Carlo approaches shows that the GA performance is better than the Monte-Carlo, especially for a small number of evaluations of the cost function. The results of this study show that the use of GA to estimate the parameters of reactive transport models is promising. (C) 2009 American Institute of Chemical Engineers AIChE J. 55: 1959-1968, 2009
Keywords:reactive transport;chemical equilibrium constants;surface complexation modeling;parameter estimation;genetic algorithm;Monte-Carlo