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Topology optimization of self-sensing nanocomposite structures with designed boundary conditions

机译:具有设计边界条件的自感应纳米复合结构的拓扑优化

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Controlling volume fractions of nanoparticles in a matrix can have a substantial influence on composite performance. This paper presents a topology optimization algorithm that designs nanocomposite structures for objectives pertaining to stiffness and strain sensing. Local effective properties are obtained by controlling local volume fractions of carbon nanotubes (CNTs) in an epoxy matrix, which are assumed to be well dispersed and randomly oriented. The method is applied to the optimization of a plate with a hole structure. Several different allowable CNT volume fraction constraints are examined, and the results show a tradeoff in preferred CNT distributions for the two objectives. It is hypothesized that the electrode location plays an important role in the strain sensing performance, and a surrogate model is developed to incorporate the electrode boundary as a set of additional design variables. It is shown that optimizing the topology and boundary electrode location together leads to further improvements in resistance change.
机译:控制基质中纳米颗粒的体积分数可以对复合性能具有显着影响。本文介绍了一种拓扑优化算法,其设计用于与刚度和应变感应有关的物镜的纳米复合材料结构。通过控制环氧基质中的碳纳米管(CNT)的局部体积分数来获得局部有效性质,该碳纳米管(CNTs)被假设良好分散和随机取向。该方法应用于具有孔结构的板的优化。检查几种不同的允许的CNT体积分数约束,结果显示了两个目标的首选CNT分布中的权衡。假设电极位置在应变感测性能中起重要作用,并且开发了替代模型以将电极边界包含为一组附加的设计变量。结果表明,优化拓扑和边界电极位置在一起导致电阻变化的进一步改进。

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