首页> 外文期刊>International Journal for Numerical Methods in Fluids >Adjoint-based error estimation and mesh adaptation for hybridized discontinuous Galerkin methods
【24h】

Adjoint-based error estimation and mesh adaptation for hybridized discontinuous Galerkin methods

机译:混合不连续Galerkin方法的基于伴随的误差估计和网格自适应

获取原文
获取原文并翻译 | 示例
           

摘要

We present a robust and efficient target-based mesh adaptation methodology, building on hybridized discontinuous Galerkin schemes for (nonlinear) convection-diffusion problems, including the compressible Euler and Navier-Stokes equations. The hybridization of finite element discretizations has the main advantage that the resulting set of algebraic equations has globally coupled degrees of freedom (DOFs) only on the skeleton of the computational mesh. Consequently, solving for these DOFs involves the solution of a potentially much smaller system. This not only reduces storage requirements but also allows for a faster solution with iterative solvers. The mesh adaptation is driven by an error estimate obtained via a discrete adjoint approach. Furthermore, the computed target functional can be corrected with this error estimate to obtain an even more accurate value. The aim of this paper is twofold: Firstly, to show the superiority of adjoint-based mesh adaptation over uniform and residual-based mesh refinement and secondly, to investigate the efficiency of the global error estimate.
机译:我们提出了一种鲁棒且有效的基于目标的网格自适应方法,该方法基于混合的不连续Galerkin方案来解决(非线性)对流扩散问题,包括可压缩的Euler和Navier-Stokes方程。有限元离散化的混合具有主要优势,即所得的代数方程组仅在计算网格的骨架上具有全局耦合的自由度(DOF)。因此,解决这些自由度需要解决一个可能更小的系统的问题。这不仅减少了存储需求,而且还允许使用迭代求解器实现更快的解决方案。网格自适应由通过离散伴随方法获得的误差估计来驱动。此外,可以使用该误差估计来校正计算出的目标功能,以获得更准确的值。本文的目的是双重的:首先,证明基于伴随的网格自适应优于均匀和基于残差的网格细化;其次,研究全局误差估计的效率。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号