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期刊论文

On accelerated symmetric stiffness techniques for non-associated plasticity with application to soil problems

陈曦Xi Chen; YG Cheng

Engineering Computations,-0001,():

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摘要/描述

Purpose – The initial stiffness method has been extensively adopted for elasto-plastic finite element analysis. The main problem associated with the initial stiffness method, however, is its slow convergence, even when it is used in conjunction with acceleration techniques. The Newton-Raphson method has a rapid convergence rate, but its implementation resorts to non-symmetric linear solvers, and hence the memory requirement may be high. The purpose of this paper is to develop more advanced solution techniques which may overcome the above problems associated with the initial stiffness method and the Newton-Raphson method. Design/methodology/approach – In this work, the accelerated symmetric stiffness matrix methods, which cover the accelerated initial stiffness methods as special cases, are proposed for non-associated plasticity. Within the computational framework for the accelerated symmetric stiffness matrix techniques, some symmetric stiffness matrix candidates are investigated and evaluated. Findings – Numerical results indicate that for the accelerated symmetric stiffness methods, the elasto-plastic constitutive matrix, which is constructed by mapping the yield surface of the equivalent material to the plastic potential surface, appears to be appealing. Even when combined with the Krylov iterative solver using a loose convergence criterion, they may still provide good nonlinear convergence rates. Originality/value – Compared to the work by Sloan et al., the novelty of this study is that a symmetric stiffness matrix is proposed to be used in conjunction with acceleration schemes and it is shown to be more appealing; it is assembled from the elasto-plastic constitutive matrix by mapping the yield surface of the equivalent material to the plastic potential surface. The advantage of combining the proposed accelerated symmetric stiffness techniques with the Krylov subspace iterative methods for large-scale applications is also emphasized.

【免责声明】以下全部内容由[陈曦]上传于[2012年03月12日 17时17分52秒],版权归原创者所有。本文仅代表作者本人观点,与本网站无关。本网站对文中陈述、观点判断保持中立,不对所包含内容的准确性、可靠性或完整性提供任何明示或暗示的保证。请读者仅作参考,并请自行承担全部责任。

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