目标导向局部均衡超收敛面片恢复驱动的网格自适应
Mesh adaptivity driven by goal-oriented locally equilibrated superconvergent patch recovery
摘要：
在过去的十年中，越来越多地使用目标导向的误差估计，这有助于量化和控制可能与设计目的相关的感兴趣的量（QoI）上的局部误差（例如，特定区域的平均应力或平均位移，断裂问题的应力强度因子等）。基于残差的误差估计器已被用于估计有限元近似的感兴趣的量的误差。这项工作提出了一种基于恢复的误差估计技术的生活质量，其主要特点是使用增强版的超收敛补丁恢复（SPR）技术开发的Zienkiewicz和朱。这种增强版的SPR技术，用于恢复原始和对偶解，提供了一个几乎静态容许的应力场，导致在QoI的误差的准确估计。
英文摘要：
During the last decade there has been an increase on the use of goal-oriented error estimates which help to quantify and control the local error on a quantity of interest (QoI) that might result relevant for design purposes (e.g. the mean stress or mean displacement in a particular area, the stress intensity factor for fracture problems,...). Residual-based error estimators have been used to estimate the error in quantities of interest for finite element approximations. This work presents a recovery-based error estimation technique for QoI whose main characteristic is the use of an enhanced version of the Superconvergent Patch Recovery (SPR) technique developed by Zienkiewicz and Zhu. This enhanced version of the SPR technique, used to recover the primal and dual solutions, provides a nearly statically admissible stress field that results in accurate estimations of the error in the QoI.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
