| Issue |
ESAIM: M2AN
Volume 59, Number 5, September-October 2025
|
|
|---|---|---|
| Page(s) | 2491 - 2514 | |
| DOI | https://doi.org/10.1051/m2an/2025054 | |
| Published online | 17 September 2025 | |
An abstract tool for comparing mixed- and equidimensional modeling
1
Center for Modeling of Coupled Subsurface Dynamics, Department of Mathematics, University of Bergen, Allégaten 41, Bergen, Norway
2
Department of Economics, BI Norwegian Business School, Kong Christian Frederiks plass 5, Bergen, Norway
* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.
Received:
6
November
2024
Accepted:
18
June
2025
Many coupled problems in engineering and science can be described by elliptic partial differential equations on adjacent domains, where the coupling can be considered either as a thin equidimensional overlap between the model domains, or as a lower-dimensional interface. Thereby we distinguish equidimensional and mixed-dimensional models of the same system, and the relationship between these modeling approaches is of natural interest. In this paper, we construct an overlapping open cover for a class of simplicial geometries and construct a bounded cochain map from the simplicial de Rham complex to the Čech-de Rham complex associated with the overlapping cover. Thus, we establish an isomorphism between simplicial de Rham complexes (i.e. functions and forms on mixed-dimensional partitions and their differentials) and subcomplexes of Čech-de Rham complexes (i.e. functions and forms on equidimensional partitions and their differentials), which serves as an abstract approximation tool for comparing mixed-dimensional problems to the equidimensional version of the same problem.
Mathematics Subject Classification: 46C05 / 58A12 / 58J10
Key words: de Rham complex / Hilbert complex / mixed-dimensional modeling / dimensionality reduction
© The authors. Published by EDP Sciences, SMAI 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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