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.
In: Water, 2022, 13 (3)
doi: 10.26083/tuprints-00017800
Artikel, Zweitveröffentlichung, Verlagsversion
 | Es ist eine neuere Version dieses Eintrags verfügbar. |
Kurzbeschreibung (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.
| Typ des Eintrags: | Artikel |
|---|---|
| Erschienen: | 2022 |
| Autor(en): | Seyedpour, Seyed Morteza ; Valizadeh, Iman ; Kirmizakis, Panagiotis ; Doherty, Rory ; Ricken, Tim |
| Art des Eintrags: | Zweitveröffentlichung |
| Titel: | Optimization of the Groundwater Remediation Process Using a Coupled Genetic Algorithm-Finite Difference Method |
| Sprache: | Englisch |
| Publikationsjahr: | 2022 |
| Publikationsdatum der Erstveröffentlichung: | 2022 |
| Verlag: | MDPI |
| Titel der Zeitschrift, Zeitung oder Schriftenreihe: | Water |
| Jahrgang/Volume einer Zeitschrift: | 13 |
| (Heft-)Nummer: | 3 |
| Kollation: | 18 Seiten |
| DOI: | 10.26083/tuprints-00017800 |
| URL / URN: | https://tuprints.ulb.tu-darmstadt.de/17800 |
| Zugehörige Links: | |
| Herkunft: | Zweitveröffentlichung |
| Kurzbeschreibung (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. |
| Freie Schlagworte: | groundwater flow, reactive contaminant transport, in situ chemical oxidation, finite difference method, genetic algorithm, physical sandbox experiment |
| Status: | Verlagsversion |
| URN: | urn:nbn:de:tuda-tuprints-178003 |
| Sachgruppe der Dewey Dezimalklassifikatin (DDC): | 600 Technik, Medizin, angewandte Wissenschaften > 620 Ingenieurwissenschaften und Maschinenbau |
| Fachbereich(e)/-gebiet(e): | 16 Fachbereich Maschinenbau 16 Fachbereich Maschinenbau > Fachgebiet Cyber-Physische Simulation (CPS) |
| Hinterlegungsdatum: | 09 Feb 2022 14:41 |
| Letzte Änderung: | 10 Feb 2022 06:38 |
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| Suche nach Titel in: | TUfind oder in Google |
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- Optimization of the Groundwater Remediation Process Using a Coupled Genetic Algorithm-Finite Difference Method. (deposited 09 Feb 2022 14:41) [Gegenwärtig angezeigt]
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