An a posteriori error estimator for the weak Galerkin least-squares finite-element method

In this paper, we derive an a posteriori error estimator for the weak Galerkin least squares (WG-LS) method applied to the reaction-diffusion equation. We show that this estimator is both reliable and efficient, allowing it to be used for adaptive refinement. Due to the flexibility of the WG-LS discretization, we are able to design a simple and straightforward refinement scheme that is applicable to any shape regular polygonal mesh. Finally, we present numerical experiments that confirm the effectiveness of the estimator, and demonstrate the robustness and efficiency of the proposed adaptive WG-LS approach. (C) 2018 Elsevier B.V. All rights reserved.