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A Two-mesh Superconvergence Method for Mesh Adaptivity

机译:网格自适应的两网格超收敛方法

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摘要

A two-mesh superconvergent gradient recovery mechanism for elliptic equations is presented. The method first computes the gradient over a fine mesh and then project it to a coarser mesh. This projected gradient has superconvergence properties for general unstructured meshes. The difference between the computed and projected gradient is used as the error indicator in refining a mesh adaptively. This new superconvergence mesh refinement technique is easy to implement and can be used for a large class of problems. Numerical experiments for smooth and singular elliptic problems given in this work show the efficiency of this technique. Comparisons with a classical mesh adaptivity method is also given here to show the advantages.
机译:提出了椭圆方程的两网格超收敛梯度恢复机制。该方法首先计算细网格上的梯度,然后将其投影到较粗的网格上。对于一般的非结构化网格,此投影梯度具有超收敛性。在自适应地细化网格时,将计算出的梯度与投影出的梯度之差用作误差指标。这种新的超收敛网格细化技术易于实现,可用于处理大量问题。这项工作中给出的光滑和奇异椭圆问题的数值实验表明了该技术的有效性。这里还给出了与经典网格自适应方法的比较,以显示其优势。

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