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Optimal complexity of deployable compressive structures

机译:可展开压缩结构的最佳复杂性

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The usual use of fractals involves self-similar geometrical objects to fill a space, where the self-similar iterations may continue ad infinitum. This is the first paper to propose the use of self-similar mechanical objects that fill an alloted space, while achieving an invariance property as the self-similar iterations continue (e.g. invariant strength). Moreover, for compressive loads, this paper shows how to achieve minimal mass and invariant strength from self-similar structures. The topology optimization procedure uses self-similar iteration until minimal mass is achieved, and this problem is completely solved, with global optimal solutions given in closed form. The optimal topology remains independent of the magnitude of the load. Mass is minimized subject to yield and/or buckling constraints. Formulas are also given to optimize the complexity of the structure, and the optimal complexity turns out to be finite. That is, a continuum is never the optimal structural for a compressive load under any constraints on the physical dimension (diameter). After each additional self-similar iteration, the number of bars and strings increase, but, for a certain choice of unit topology shown, the total mass of bars and strings decreases. For certain structures, the string mass monotonically increases with iteration, while the bar mass monotonically reduces, leading to minimal total mass in a finite number of iterations, and hence a finite optimal complexity for the structure. The number of iterations required to achieve minimal mass is given explicitly in closed form by a formula relating the chosen unit geometry and the material properties. It runs out that the optimal structures produced by our theory fall in the category of structures we call tensegrity. Hence our self-similar algorithms can generate tensegrity fractals.
机译:分形的通常用法是使用自相似的几何对象来填充空间,自相似的迭代可能会无限期地继续进行。这是第一篇提出使用自相似机械对象的论文,该对象填充了分配的空间,同时随着自相似迭代的继续(例如不变强度)实现了不变性。此外,对于压缩载荷,本文显示了如何通过自相似结构获得最小的质量和不变强度。拓扑优化过程使用自相似迭代,直到达到最小质量,并使用封闭形式给出的全局最优解完全解决了这个问题。最佳拓扑保持与负载大小无关。受屈服和/或屈曲约束,质量被最小化。还给出了用于优化结构复杂度的公式,并且最佳复杂度被证明是有限的。也就是说,在任何物理尺寸(直径)的约束下,连续体绝不是压缩载荷的最佳结构。在每次其他自相似迭代之后,条和弦的数量会增加,但是,对于所示的单元拓扑的某种选择,条和弦的总质量会减少。对于某些结构,弦的质量随迭代单调增加,而钢筋的质量单调减小,从而导致有限数量的迭代中的总质量最小,因此结构的最佳优化复杂性有限。达到最小质量所需的迭代次数由封闭的形式明确地给出,该公式由与所选单元几何形状和材料属性相关的公式给出。结果证明,我们的理论所产生的最优结构属于我们称为张力结构的类别。因此,我们的自相似算法可以生成张力分形。

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