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Layout optimization of continuum structures considering the probabilistic and fuzzy directional uncertainty of applied loads based on the cloud model

机译:基于云模型的考虑应用载荷概率和模糊方向不确定性的连续体结构布局优化

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摘要

This paper reports an efficient approach for uncertain topology optimization in which the uncertain optimization problem is equivalent to that of solving a deterministic topology optimization problem with multiple load cases. Probabilistic and fuzzy property of the directional uncertainty of the applied loads is considered in the topology optimization; the cloud model is employed to describe that property which can also take the correlations of the probability and fuzziness into account. Convergent and mesh-independent bi-directional evolutionary structural optimization (BESO) algorithms are utilized to obtain the final optimal solution. The proposed method is suitable for linear elastic problems with uncertain applied loads, subject to volume constraint. Several numerical examples are presented to demonstrate the capability and effectiveness of the proposed approach. In-depth discussions are also given on the effects of considering the probability and fuzziness of the directions of the applied loads on the final layout.
机译:本文报告了一种有效的不确定拓扑优化方法,其中不确定优化问题等同于解决具有多个载荷工况的确定性拓扑优化问题。在拓扑优化中考虑了所施加载荷的方向不确定性的概率和模糊性质;云模型用于描述该属性,该属性也可以考虑概率和模糊性的相关性。利用收敛和独立于网格的双向进化结构优化(BESO)算法获得最终的最优解。所提出的方法适用于线性弹性问题,具有不确定的施加载荷,受体积约束。几个数值例子被提出来证明所提出的方法的能力和有效性。还对考虑施加载荷的方向的概率和模糊性对最终布局的影响进行了深入讨论。

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