Title of article :
A second-order sharp numerical method for solving the linear elasticity equations on irregular domains and adaptive grids – Application to shape optimization
Author/Authors :
Mohammad and Theillard، نويسنده , , Maxime and Djodom، نويسنده , , Landry Fokoua and Vié، نويسنده , , Jean-Léopold and Gibou، نويسنده , , Frédéric، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2013
Abstract :
We present a numerical method for solving the equations of linear elasticity on irregular domains in two and three spatial dimensions. We combine a finite volume and a finite difference approaches to derive discretizations that produce second-order accurate solutions in the L ∞ -norm. Our discretization is ‘sharp’ in the sense that the physical boundary conditions (mixed Dirichlet/Neumann-type) are imposed at the interface and the solution is computed inside the irregular domain only, without the need of smearing the solution across the interface. The irregular domain is represented implicitly using a level-set function so that this approach is applicable to free moving boundary problems; we provide a simple example of shape optimization to illustrate this capability. In addition, we provide an extension of our method to the case of adaptive meshes in both two and three spatial dimensions: we use non-graded quadtree (2D) and octree (3D) data structures to represent the grid that is automatically refined near the irregular domain’s boundary. This extension to quadtree/octree grids produces second-order accurate solutions albeit non-symmetric linear systems, due to the node-based sampling nature of the approach. However, the linear system can be solved with simple linear solvers; in this work we use the BICGSTAB algorithm.
Keywords :
Second-order discretization , level-set , Linear Elasticity , Octree data structure , Quadtree/octree data structure , Non-graded adaptive grid , Irregular Domains , Hybrid finite volume/finite difference
Journal title :
Journal of Computational Physics
Journal title :
Journal of Computational Physics