弹性问题的一种阻尼系数快速自适应Galerkin有限体积求解器

IF 0.5 Q4 ENGINEERING, MULTIDISCIPLINARY
S. R. Yazdi, T. Amiri, S. A. Gharebaghi
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引用次数: 4

摘要

本文提出了平面弹性问题Cauchy动量方程的快速自适应Galerkin有限体积(QAGFV)解。引入了一个新的阻尼系数来保持迭代伪显式求解过程的效率。结果表明,所提出的阻尼系数不仅有效地阻尼了数值振荡,而且提高了QAGFV算法的收敛速度。此外,数值结果表明,所提出的系数对空间离散化不敏感。为了提高计算应力场和位移场的精度,采用了一种自动的二维h自适应网格细化程序来求解控制方程的形状函数自由解。为了验证,研究了两个经典问题及其解析解。第一种是带孔的单轴加载板,第二种是集中荷载下的悬臂梁。结果表明,QAGFV与分析方法有很好的一致性。此外,有限元法的直接和迭代方法已在FORTRAN中实现,以评估所提出算法的效率和准确性。最后,将一些问题的相应结果与QAGFV的解决方案进行了比较。结果证实,所提出的h自适应QAGFV求解器是准确和高效的,尤其是在大计算域中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Proposed Damping Coefficient of Quick Adaptive Galerkin Finite Volume Solver for Elasticity Problems
A Quick Adaptive Galerkin Finite Volume (QAGFV) solution of Cauchy momentum equations for plane elastic problems is presented in this research. A new damping coefficient is introduced to preserve the efficiency of the iterative pseudo-explicit solution procedure. It is shown that the numerical oscillations are not only effectively damped by the proposed damping coefficient, but also that the rate of the convergence of QAGFV algorithm increases. Furthermore, the numerical results show that the proposed coefficient is not sensitive to the spatial discretization. In order to improve the accuracy of the computed stress and displacement fields, an automatic twodimensional h–adaptive mesh refinement procedure is adopted for shape-function-free solution of the governing equations. For verification, two classical problems and their analytical solutions have been investigated. The first is a uniaxial loaded plate with holes, and the second is a cantilever beam under a concentrated load. The results show a good agreement between QAGFV and analytical method. Moreover, the direct and iterative approaches of the finite element method have been implemented in FORTRAN to evaluate the efficiency and accuracy of the presented algorithm. In the end, the corresponding results of some problems have been compared to the QAGFV solutions. The results confirm that the presented h-adaptive QAGFV solver is accurate and highly efficient especially in a large computational domain.
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