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The PCD (piecewise constant distributions) method is a discretization technique of the boundary value problems in which the unknown distribution and its derivatives are represented by piecewise constant distributions but on distinct meshes. It has the advantage of producing the most sparse stiffness matrix resulting from the approximate problem. In this contribution, we propose a general PCD triangulation by combining rectangular elements and triangular elements. We also apply this discretization technique for the elasticity problem. We end with presentation of numerical results of the proposed method for the 2D diffusion equation.

We propose in this contribution a successive local mesh refinement with the PCD method. The multilevel local refinement improves the accuracy and gives a better precision, locally and globally, with a lower computational costs particularly if the considered problem has an anomaly. Here we present how a successive local mesh refinement can be handled. We conclude by presenting numerical experiments to show the interest of a multilevel local mesh refinement for the 2D diffusion equation.

We introduce a discretization method of boundary value problems (BVP) in the case of the two dimensional diffusion equation on a rectangular mesh with refined zones. The method consists in representing the unknown distribution and its derivatives by piecewise constant distributions (PCD) on distinct meshes together with an appropriate approximate variational formulation of the exact BVP on this piecewise constant distributions space. This method, named the PCD method, has the advantage of producing the most compact possible discrete stencil. Here, we analyze and prove the convergence of the PCD method and determine upper bounds on its convergence rate.