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A novel fast overrelaxation updating method for continuous-discontinuous cellular automaton

机译:连续-不连续细胞自动机的一种新的快速过松弛更新方法

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Because of its local property, cellular automaton method has been widely applied in different subjects, but the main problem is that the cellular updating is time-consuming. In order to improve its calculation efficiency, a fast successive relaxation updating method is proposed in this paper. Firstly, an accelerating factor ω is defined, and a fast successive relaxation updating theory and its corresponding convergence conditions are developed. In each updating step, the displacement increment is enlarged ω times as a new increment to replace the old one, similarly, the nodal forces for its neighbors caused by this displacement increment are also enlarged by the same accelerating factor, and do those updating operations until the convergence is achieved. By this method, the convergence rate is greatly improved, by a suitable accelerating factor, 90 to 98% of iteration steps are decreased compared to that of the traditional method. Besides, the influence factors for the accelerating factor are studied, and numerical studies show that the suitable accelerating factor is 1.85 ω 1.99, which is greatly influenced by cell stiffness, and the optimal accelerating factor is 1.96 ω 1.99. Finally, numerical examples are given to illustrate that the present method is effective and high convergence rate compared to the traditional method.
机译:由于细胞自动机方法的局限性,它已经在不同的学科中得到了广泛的应用,但是主要的问题是细胞的更新是费时的。为了提高其计算效率,提出了一种快速连续松弛更新方法。首先,定义了一个加速因子ω,建立了快速连续松弛更新理论及其对应的收敛条件。在每个更新步骤中,将位移增量放大ω倍,作为新的增量来替代旧的增量,类似地,由该位移增量引起的相邻节点的节点力也以相同的加速因子进行放大,并进行这些更新操作,直到收敛。通过这种方法,收敛速度大大提高,通过适当的加速因子,与传统方法相比,迭代步骤减少了90%至98%。此外,对加速因子的影响因素进行了研究,数值研究表明,合适的加速因子为1.85 <ω<1.99,受细胞刚度的影响很大,最佳加速因子为1.96 <ω<1.99。最后,通过数值算例说明了与传统方法相比,该方法有效且收敛速度快。

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