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In search of optimal acceleration approach to iterative solution methods of simultaneous algebraic equations

机译:在寻求最优加速方法的同时代数方程的迭代解法

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This paper presents several new proposals for acceleration of iterative solution methods of both linear and non-linear Simultaneous Algebraic Equations (SAE). The main concept is based on the successive over-relaxation technique (SOR). A new simple and effective way of evaluation of the relaxation parameter is based on either minimization or annihilation of the subsequent solution residuum. The other concept effectively uses features of the infinite geometrical progression. Its quotient is built using solution increments in several initial series of subsequent iterative steps. Both acceleration mechanisms were also combined in order to obtain the best acceleration of the solution process for Simultaneous Linear Algebraic Equations (SLAE). These concepts were tested on many 1D and 2D benchmark problems, with banded and/or sparse systems. For the relaxed Gauss-Seidel (G-S) approach, the convergence rates were up to 200 times better when compared with the standard G-S one. Significant convergence improvement was also reached while testing non-linear SAEs (with the relaxed Newton-Raphson method). The numerical models of the selected engineering problems were based on the meshless approach, due to their more sophisticated nature (when compared e.g. with the finite element analysis).
机译:本文提出了一些加速线性和非线性同时代数方程(SAE)迭代求解方法的新建议。主要概念基于连续超松弛技术(SOR)。一种新的简单有效的松弛参数评估方法是基于最小化或消除随后的求解残差。另一个概念有效地利用了无限几何级数的特征。它的商是通过在后续迭代步骤的几个初始系列中使用解决方案增量来构建的。两种加速机制也被组合在一起,以便获得同时线性代数方程(SLAE)求解过程的最佳加速。这些概念已在带状和/或稀疏系统的许多一维和二维基准问题上进行了测试。对于宽松的高斯-赛德尔(G-S)方法,收敛速度比标准G-S快200倍。在测试非线性SAE(使用轻松的Newton-Raphson方法)时,还达到了显着的收敛性改进。所选工程问题的数值模型基于无网格方法,因为它们具有更复杂的性质(例如,与有限元分析相比)。

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