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首页> 外文期刊>Journal of Computational Science and Technology >Convergence Acceleration of Parallel CG-FEM with Controlled Domain Decomposition for Singularity Problems
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Convergence Acceleration of Parallel CG-FEM with Controlled Domain Decomposition for Singularity Problems

机译:奇异问题下具有受控域分解的并行CG-FEM的收敛加速

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References(8) Stress singularity is usually observed in practical stress analysis, and it may lead to the deterioration of the convergence rate of the preconditioned conjugate gradient method (PCG). Until now, parallel PCG has been used without considering the practical issues; therefore, the deterioration was induced in the problem in which stress singularity was observed. The convergence acceleration method was developed in parallel PCG based on controlled domain decomposition. The acceleration method can be achieved by considering the spatial locality of stress singularity and preconditioning of conjugate gradient method. The convergence acceleration method reduces the 15% of iteration of PCG as a maximum, where the singular area is included in one domain.
机译:参考文献(8)应力奇异性通常在实际应力分析中观察到,并且可能导致预处理共轭梯度法(PCG)的收敛速度变差。到目前为止,并行PCG一直被使用,没有考虑实际问题。因此,在观察到应力奇异性的问题中引起了劣化。基于控制域分解,在并行PCG中开发了收敛加速方法。通过考虑应力奇异性的空间局部性和共轭梯度法的预处理可以实现加速方法。收敛加速方法最大程度地减少了PCG迭代的15%,其中单个区域包含在一个域中。

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