Evolutionary topology optimization of elastoplastic structures
Evolutionary topology optimization of elastoplastic structures
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DOI：
10.1007/s00158-016-1523-1
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发表时间：
2017-02
影响因子：
3.9
通讯作者：
L. Xia;F. Fritzen;P. Breitkopf
中科院分区：
文献类型：
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作者：
L. Xia;F. Fritzen;P. Breitkopf
我们最近在（Fritzen et al., Int J NumerMethods Eng 106(6):430–453, 2016）中提出了一种用于多尺度弹塑性结构设计的演化拓扑优化模型，该模型通常独立于所应用的材料定律。面对塑料结构设计时最终设计因微小参数变化而产生的可变性，我们通过引入灵敏度数阻尼方案并逐步减小灵敏度滤波半径，进一步提高了BESO优化过程的鲁棒性和有效性。限制灵敏度数方差的阻尼方案稳定了拓扑演化过程，特别是对于耗散结构设计。通过最初设置较大的滤波器半径值并逐渐减小它，可以避免出现多余的结构分支，这些多余的结构分支随后需要被消除，并且是设计过程恶化的主要原因。通过常规均质结构的基准数值算例验证了改进模型的鲁棒性和有效性。
We have recently proposed in (Fritzen et al., Int J Numer Methods Eng 106(6):430–453, 2016) an evolutionary topology optimization model for the design of multiscale elastoplastic structures, which is in general independent of the applied material law. Facing the variability of the final design for minor parameter changes when dealing with plastic structural designs, we further improve the robustness and the effectiveness of the BESO optimization procedure in this work by introducing a damping scheme on sensitivity numbers and by progressively reducing the sensitivity filtering radius. The damping scheme constraining the variance of the sensitivity numbers stabilizes the topological evolution process in particular for dissipative structural designs. By setting initially a large filter radius value and reducing it gradually, the emergence of the redundant structural branches, which are to be eliminated afterwards and are the main reasons deteriorating the design process, could be avoided. The robustness and the effectiveness of the improved model has been validated by means of benchmark numerical examples of conventional homogeneous structures.