Optimal remediation design and simulation of groundwater flow coupled to contaminant transport using genetic...

Area of Science:

• Environmental Engineering
• Hydrogeology
• Computational Modeling

Background:

• Groundwater resource management and remediation design require robust simulation-optimization tools.
• Contaminant transport in groundwater poses significant environmental challenges.
• Existing models may lack the precision for complex reactive transport processes.

Purpose of the Study:

• To develop a coupled groundwater flow and reactive contaminant transport model using the Meshfree method.
• To optimize contaminant remediation strategies using genetic algorithms and permanganate as an oxidant.
• To validate the model's accuracy against a physical sandbox experiment.

Main Methods:

• Implemented a Meshfree method with Multiquadratic Radial Basis Function (MRBF) for groundwater flow and reactive transport.
• Performed parameter analysis to determine the optimal shape parameter (0.97) for the MRBF.
• Utilized a genetic algorithm approach to optimize remediation design, considering two objectives and two constraints.

Main Results:

• The developed model showed good agreement when compared with a physical sandbox model.
• Optimized remediation strategies significantly reduced contaminant breakthrough time.
• A substantial decrease in contaminant concentration in the downstream area of interest was achieved through optimization.

Conclusions:

• The simulation-optimization model is a powerful tool for groundwater resource management and remediation design.
• The Meshfree method coupled with MRBF provides an accurate framework for modeling groundwater flow and reactive transport.
• Genetic algorithm optimization effectively enhances remediation strategies, minimizing contaminant spread and concentration.