| Issue |
ESAIM: M2AN
Volume 59, Number 6, November-December 2025
|
|
|---|---|---|
| Page(s) | 3107 - 3130 | |
| DOI | https://doi.org/10.1051/m2an/2025085 | |
| Published online | 17 November 2025 | |
Arbitrary order approximations at constant cost for Timoshenko beam network models
1
Institute for Applied and Numerical Mathematics, Karlsruhe Institute of Technology, Englerstr. 2, 76131 Karlsruhe, Germany
2
Department of Mathematical Sciences, University of Gothenburg and Chalmers University of Technology, 41296 Göteborg, Sweden
3
Department of Mathematics, Saarland University, 66123 Saarbrücken, Germany
* Corresponding author: moritz.hauck@kit.edu
Received:
6
August
2024
Accepted:
30
September
2025
This paper considers the numerical solution of Timoshenko beam network models, comprised of Timoshenko beam equations on each edge of the network, which are coupled at the nodes of the network using rigid joint conditions. Through hybridization, we can equivalently reformulate the problem as a symmetric positive definite system of linear equations posed on the network nodes. This is possible since the nodes, where the beam equations are coupled, are zero-dimensional objects. To discretize the beam network model, we propose a hybridizable discontinuous Galerkin method that can achieve arbitrary orders of convergence under mesh refinement without increasing the size of the global system matrix. As a preconditioner for the typically very poorly conditioned global system matrix, we employ a two-level overlapping additive Schwarz method. We prove uniform convergence of the corresponding preconditioned conjugate gradient method under appropriate connectivity assumptions on the network. Numerical experiments support the theoretical findings of this work.
Mathematics Subject Classification: 05C50 / 65F10 / 65N15 / 65N30 / 65N55
Key words: Timoshenko beam network / elastic graph / hybridizable discontinuous Galerkin / arbitrary order approximation / a priori error analysis / additive Schwarz preconditioner
© 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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