Multi-Objective Optimization of Active Spreading Strategies to Improve in Situ Remediation of Contaminated Groundwater

Graduate Thesis Or Dissertation

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Citeable URL: https://scholar.colorado.edu/concern/graduate_thesis_or_dissertations/ht24wj59d

Abstract

In situ remediation methods are commonly used to clean up contaminated aquifers; however, at many sites, these methods fail to reduce contaminant concentrations to acceptable levels. During in situ remediation, a treatment chemical is injected into the contaminated aquifer to react with and degrade the contaminant. To be effective, the injected treatment chemical must contact the extent of the contaminant plume for a long enough period for degradation to occur. The contact of these reactants during in situ remediation can be enhanced using an innovative technique known as active spreading, in which contact is engineered by generating flow fields in the aquifer that actively spread the treatment chemical throughout the contaminant plume. In this dissertation, I use a multi-objective evolutionary algorithm to optimize the performance of active spreading systems in a variety of remediation scenarios characterized by different aquifer and contaminant properties. The active spreading designs generated during optimization reflect the tradeoffs between the remediation objectives, e.g. maximizing contaminant degradation and minimizing energy requirements, and represent feasible options for project stakeholders to use to improve in situ remediation. Analysis of the contaminant transport and reaction that corresponds to different active spreading designs indicates that the designs reflect the underlying aquifer and contaminant properties of the remediation scenarios.

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