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A new adaptive mesh refinement strategy based on a probabilistic error estimation

机译:一种基于概率误差估计的新自适应网格细化策略

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In this paper, an automatic adaptive mesh refinement procedure is presented for two-dimensional problems on the basis of a new probabilistic error estimator. First-order perturbation theory is employed to determine the lower and upper bounds of the structural displacements and stresses considering uncertainties in geometric sizes, material properties and loading conditions. A new probabilistic error estimator is proposed to reduce the mesh dependency of the responses dispersion. The suggested error estimator neglects the refinement at the critical points with stress concentration. Therefore, the proposed strategy is combined with the classic adaptive mesh refinement to achieve an optimal mesh refined properly in regions with either high gradients or high dispersion of the responses. Several numerical examples are illustrated to demonstrate the efficiency, accuracy and robustness of the proposed computational algorithm and the results are compared with the classic adaptive mesh refinement strategy described in the literature.
机译:在本文中,基于新的概率误差估计器呈现自动自适应网格细化过程。主要采用一阶扰动理论来确定结构位移的下限和上限,并考虑几何尺寸,材料性质和装载条件的不确定性。提出了一种新的概率误差估计器来减少响应色散的网格依赖性。建议的误差估计器忽略了应力集中的关键点处的细化。因此,所提出的策略与经典的自适应网格精制相结合,以在具有高梯度或响应的高分子的区域中正确地改进的最佳网格。示出了若干数值示例以展示所提出的计算算法的效率,准确性和鲁棒性,并将结果与​​文献中描述的经典自适应网格细化策略进行比较。

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