Carlos García Vera | Searcharxiv

arXiv2026

Minimum residual discretization of a semilinear elliptic problem

We propose a least-squares penalization as a means to extend the discontinuous Petrov-Galerkin (DPG) method with optimal test functions to a class of semilinear elliptic problems. The nonlinear contributions are replaced with independent unknowns so that standard DPG techniques apply to the then linear problem with non-trivial kernel. The nonlinear relations are added as least-squares constraints. Assuming solvability of the semilinear problem and an Aubin-Nitsche-type approximation property for the primal variable, we prove a Cea estimate for the approximation error in canonical norms. Numerical results with uniform and adaptively refined meshes illustrate the performance of the scheme.

math.NA↗

arXiv2020

A locking-free DPG scheme for Timoshenko beams

We develop a discontinuous Petrov-Galerkin scheme with optimal test functions (DPG method) for the Timoshenko beam bending model with various boundary conditions, combining clamped, supported, and free ends. Our scheme approximates the transverse deflection and bending moment. It converges quasi-optimally in $L_2$ and is locking free. In particular, it behaves well (converges quasi-optimally) in the limit case of the Euler-Bernoulli model. Several numerical results illustrate the performance of our method.

math.NA↗