Optimization of the Groundwater Remediation Process Using a Coupled Genetic Algorithm-Finite Difference Method

In situ chemical oxidation using permanganate as an oxidant is a remediation technique often used to treat contaminated groundwater. In this paper, groundwater flow with a full hydraulic conductivity tensor and remediation process through in situ chemical oxidation are simulated. The numerical approach was verified with a physical sandbox experiment and analytical solution for 2D advection-diffusion with a first-order decay rate constant. The numerical results were in good agreement with the results of physical sandbox model and the analytical solution. The developed model was applied to two different studies, using multi-objective genetic algorithm to optimise remediation design. In order to reach the optimised design, three objectives considering three constraints were defined. The time to reach the desired concentration and remediation cost regarding the number of required oxidant sources in the optimised design was less than any arbitrary design.

Automated summary

This paper studied the remediation of contaminated groundwater using permanganate as an oxidant through in situ chemical oxidation, and verified the model through numerical simulation, showing good agreement between numerical results, physical sandbox experiment, and analytical solution. By applying a genetic algorithm to optimize the design, the time to reach desired concentration and remediation cost can be reduced compared to arbitrary designs.