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A Localized Orthogonal Decomposition method for heterogeneous mixed-dimensional problems

Published: October 10, 2025 | arXiv ID: 2510.09442v1

By: Moritz Hauck, Axel Målqvist, Malin Mosquera

Potential Business Impact:

Solves hard math problems in rocks faster.

Business Areas:
Big Data Data and Analytics

We propose a multiscale method for mixed-dimensional elliptic problems with highly heterogeneous coefficients arising, for example, in the modeling of fractured porous media. The method is based on the Localized Orthogonal Decomposition (LOD) framework and constructs locally supported, problem-adapted basis functions on a coarse mesh that does not need to resolve the coefficient oscillations. These basis functions are obtained in parallel by solving localized fine-scale problems. Our a priori error analysis shows that the method achieves optimal convergence with respect to the coarse mesh size, independent of the coefficient regularity, with an exponentially decaying localization error. Numerical experiments validate these theoretical findings and demonstrate the computational viability of the method.

Page Count
22 pages

Category
Mathematics:
Numerical Analysis (Math)