Numerical analysis of a locking-free primal hybrid method for linear elasticity with $H(\mathrm{div})$-conforming stress recovery
Giovanni Taraschi, Maicon Ribeiro Correa

TL;DR
This paper introduces a locking-free primal hybrid finite element method for linear elasticity that ensures optimal convergence and robust stress recovery, particularly effective for nearly incompressible materials.
Contribution
The work develops a general analysis for stable approximation spaces and proposes a stress recovery strategy, enhancing robustness and accuracy in linear elasticity simulations.
Findings
Achieves optimal convergence orders on triangular and quadrilateral meshes.
Provides a stress recovery method that yields $H(\mathrm{div})$-conforming, locally equilibrated stress fields.
Demonstrates robustness in nearly incompressible elasticity problems.
Abstract
In this work, we study a primal hybrid finite element method for the approximation of linear elasticity problems, posed in terms of displacement, an auxiliary pressure field, and a Lagrange multiplier related to the traction. We develop a general analysis for the existence and uniqueness of the solution for the discrete problem, which is applied to the construction of stable approximation spaces on triangular and quadrilateral meshes. The use of these spaces lead to optimal convergence orders, resulting in a locking-free method capable of providing robust approximations for nearly incompressible problems. Finally, we propose a strategy for recovering the stress field from the hybrid solution by solving element-wise sub-problems. The resulting stress approximation is -conforming, locally equilibrated, weakly symmetric, and robust to locking.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAdvanced Numerical Methods in Computational Mathematics · Matrix Theory and Algorithms · Numerical methods in engineering
