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Evolutionary topology optimization of continuum structures under uncertainty using sensitivity analysis and smooth boundary representation

机译:基于灵敏度分析和光滑边界表示的不确定性下连续体结构的演化拓扑优化

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This paper presents an evolutionary approach for the Robust Topology Optimization (RTO) of continuum structures under loading and material uncertainties. The method is based on an optimality criterion obtained from the stochastic linear elasticity problem in its weak form. The smooth structural topology is determined implicitly by an iso-value of the optimality criterion field. This iso-value is updated using an iterative approach to reach the solution of the RTO problem. The proposal permits to model the uncertainty using random variables with different probability distributions as well as random fields. The computational burden, due to the high dimension of the random field approximation, is efficiently addressed using anisotropic sparse grid stochastic collocation methods. The numerical results show the ability of the proposal to provide smooth and clearly defined structural boundaries. Such results also show that the method provides structural designs satisfying a trade-off between conflicting objectives in the RTO problem. (C) 2018 Elsevier Ltd. All rights reserved.
机译:本文提出了一种在载荷和材料不确定性条件下连续体结构的稳健拓扑优化(RTO)的进化方法。该方法基于从随机形式的线性弹性问题中获得的最优准则。平滑的结构拓扑由最佳性标准字段的等值值隐式确定。使用迭代方法更新此等值以解决RTO问题。该建议允许使用具有不同概率分布的随机变量以及随机字段对不确定性进行建模。使用各向异性的稀疏网格随机配置方法可以有效地解决由于随机字段近似值高而引起的计算负担。数值结果表明了该提议提供平滑且清晰定义的结构边界的能力。这些结果还表明,该方法提供了满足RTO问题中相互矛盾的目标之间进行折衷的结构设计。 (C)2018 Elsevier Ltd.保留所有权利。

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