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On the behaviour of the ANM continuation in the presence of bifurcations

机译:在分叉情况下ANM连续的行为

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The asymptotic-numerical method (ANM) is a path following technique which is based on high order power series expansions. In this paper, we analyse its behaviour when it is applied to the continuation of a branch with bifurcation points. We show that when the starting point of the continuation is near a bifurcation, the radius of convergence of the power series is exactly the distance from the starting point to the bifurcation. This leads to an accumulation of small steps around the bifurcation point. This phenomenon is related to the presence of inevitable imperfections in the FE models. We also explain that, depending on the maximal tolerated residual error (out-of-balance error), the ANM continuation may continue to follow the fundamental path or it may turn onto the bifurcated path without applying any branch switching technique.
机译:渐进数值方法(ANM)是一种基于高阶幂级数展开的路径跟踪技术。在本文中,我们分析了将其应用于具有分支点的分支的连续性时的行为。我们表明,当连续的起点靠近分叉点时,幂级数的收敛半径恰好是从起点到分叉点的距离。这导致在分叉点周围积累了小台阶。这种现象与有限元模型中不可避免的缺陷的存在有关。我们还解释说,根据最大容许残留误差(失衡误差),ANM延续可能会继续遵循基本路径,或者可能会转向分叉路径,而无需应用任何分支切换技术。

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