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

Seyedpour, Seyed Morteza ; Valizadeh, Iman ; Kirmizakis, Panagiotis ; Doherty, Rory ; Ricken, Tim (2022):
Optimization of the Groundwater Remediation Process Using a Coupled Genetic Algorithm-Finite Difference Method. (Publisher's Version)
In: Water, 13 (3), MDPI, e-ISSN 2073-4441,
DOI: 10.26083/tuprints-00017800,
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Item Type: Article
Origin: Secondary publication DeepGreen
Status: Publisher's Version
Title: Optimization of the Groundwater Remediation Process Using a Coupled Genetic Algorithm-Finite Difference Method
Language: English
Abstract:

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.

Journal or Publication Title: Water
Volume of the journal: 13
Issue Number: 3
Publisher: MDPI
Collation: 18 Seiten
Uncontrolled Keywords: groundwater flow, reactive contaminant transport, in situ chemical oxidation, finite difference method, genetic algorithm, physical sandbox experiment
Classification DDC: 600 Technik, Medizin, angewandte Wissenschaften > 620 Ingenieurwissenschaften
Divisions: 16 Department of Mechanical Engineering > Cyber-Physical Simulation (CPS)
Date Deposited: 09 Feb 2022 14:41
Last Modified: 02 May 2022 12:07
DOI: 10.26083/tuprints-00017800
Corresponding Links:
URN: urn:nbn:de:tuda-tuprints-178003
SWORD Depositor: Deep Green
URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/17800
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