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Dual approach using a variant perimeter constraint and efficient sub-iteration scheme for topology optimization

机译:使用变体周界约束和有效子迭代方案进行拓扑优化的双重方法

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To prevent numerical instabilities associated with the mesh-dependence, checkerboards and grey regions in topology optimization, a variant perimeter-constrained version of the SIMP algorithm is proposed using a smooth and quadratic function. In order to have an efficient implementation and to make sure the strict satisfaction of such an upper-bound perimeter constraint, a diagonal quadratic approximation of the perimeter constraint is used in the construction of each explicit optimization subproblem. The latter is then solved by a dual sub-iteration scheme. Numerical results show that the incorporation of such a sub-iteration scheme leads to a convergent solution without needs of move-limits or artificial control parameters. In addition to this, it is found that successive relaxations of the perimeter constraint by increasing the upper-bound tend to regularize the topology solution and result in a checkerboard free and satisfactory design solution without grey regions.
机译:为了防止拓扑优化中与网格相关性,棋盘格和灰色区域相关的数值不稳定性,提出了使用平滑和二次函数的SIMP算法的变体边界约束版本。为了有效地实现并确保严格满足这种上限边界约束,在构造每个显式优化子问题时都使用了边界约束的对角二次逼近。然后通过双重子迭代方案解决后者。数值结果表明,这种子迭代方案的引入导致了收敛的解决方案,而无需移动限制或人工控制参数。除此之外,还发现通过增加上限来连续放松边界约束会趋于规范化拓扑解决方案,并导致没有棋盘格的令人满意的设计解决方案而没有灰色区域。

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