Titelangaben
Schulz, Raphael ; Gärttner, Stephan ; Ray, Nadja:
Investigations of effective dispersion models for electroosmotic flow with rigid and free boundaries in a thin strip.
In: Mathematical methods in the applied sciences. 47 (2023) 1.
- S. 206-228.
ISSN 1099-1476 ; 0170-4214
Volltext
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Link zum Volltext (externe URL): https://doi.org/10.1002/mma.9651 |
Kurzfassung/Abstract
Reactive flow and transport in porous media is topic of intense research since decades. Since dispersion is one of the key parameters in solute transport, its accurate modeling is essential to avoid wrong predictions of flow and transport behavior. In this research, we investigate novel effective dispersion models for reactive transport of electrically charged chemical species in a thin, potentially evolving strip taking into account Taylor–Aris and electroosmotic-induced dispersion as well as their cross-coupling effects. We prove positivity of the dispersion coefficient and the existence and uniqueness of strong solutions in the fixed geometry setting. Moreover, we numerically investigate scenarios for both the fixed and evolving geometry situation. The simulation results illustrate the possibility of separating charged species, such that the findings of this study can lead to a better understanding of mixing and separation processes of charged solutes and an improved prediction of breakthrough curves. Finally, we study the limits of vanishing channel width, precipitation layer thickness, and molecular diffusion. We show convergence of the solutions to the corresponding limit cases such as a hyperbolic model or the fixed geometry case. From these results, we can rate the impact of distinct dispersion mechanisms and evaluate the necessity of a detailed modeling for different parameter regimes.
Weitere Angaben
Publikationsform: | Artikel |
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Schlagwörter: | electrodispersion; electroosmosis; evolving microstructure; existence; numerical simulations; Taylor dispersion |
Sprache des Eintrags: | Englisch |
Institutionen der Universität: | Mathematisch-Geographische Fakultät > Mathematik > Mathematisches Institut für Maschinelles Lernen und Data Science (MIDS) |
DOI / URN / ID: | 10.1002/mma.9651 |
Open Access: Freie Zugänglichkeit des Volltexts?: | Ja |
Peer-Review-Journal: | Ja |
Verlag: | Wiley |
Die Zeitschrift ist nachgewiesen in: | |
Titel an der KU entstanden: | Ja |
KU.edoc-ID: | 33679 |
Letzte Änderung: 18. Sep 2024 12:12
URL zu dieser Anzeige: https://edoc.ku.de/id/eprint/33679/