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A study on ranked bidirectional evolutionary structural optimization (R-BESO) method for fully stressed structure design based on displacement sensitivity

机译:基于位移敏感性的全应力结构分级双向演化结构优化(R-BESO)方法研究

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Evolutionary Structural Optimization (ESO) method is well known as one of several topology optimization methods and has been applied to a lot of optimization problems. While ESO method evolves the given model into an optimum by subtracting several elements, in AESO method elements are added in a previous step of the evolutionary procedure. And in BESO (Bidirectional ESO) method, some elements are either generated or eliminated from a previous model of evolutionary procedure. In this paper, Ranked Bidirectional Evolutionary Structural Optimization(R-BESO) method is introduced as one of the topology optimization methods using an evolutionary algorithm and is applied to several optimization problems. The method can get optimum topologies of the structures throughout fewer iterations comparing with previous several methods based on ESO. R-BESO method is similar to BESO method except that elements are generated near a candidate element according to the rank calculated by sensitivity analyses. The displacement sensitivity analysis was adopted by the nodal displacements of a candidate element in order to determine a rank on the free edges for two dimensional model or the free surfaces for three dimensional model. In this paper, R-BESO method is proposed as another useful design tool like the previous ESO and BESO method for the two bar frame problem, the Michell type structure problem and the three dimension short cantilever beam problem, which had been used to verify reasonability of ESO method family. For the three dimensions short cantilever beam problem an optimized topology could be obtained with much fewer iterations with respect to the results of other ESO methods.
机译:进化结构优化(ESO)方法是几种拓扑优化方法之一,众所周知,并已应用于许多优化问题。 ESO方法通过减去几个元素将给定的模型演化为最优模型,而在AESO方法中,在演化过程的前一步中添加了元素。并且在BESO(双向ESO)方法中,某些元素是从先前的演化过程模型中生成或消除的。本文介绍了一种排序双向进化结构优化(R-BESO)方法作为一种使用进化算法的拓扑优化方法,并将其应用于若干优化问题。与以前的几种基于ESO的方法相比,该方法可以在更少的迭代过程中获得结构的最佳拓扑。 R-BESO方法与BESO方法类似,不同之处在于,根据敏感度分析计算出的等级,在候选元素附近生成元素。通过对候选元素的节点位移进行位移敏感性分析,以便确定二维模型的自由边缘或三维模型的自由表面的等级。本文提出了R-BESO方法作为另一种有用的设计工具,像以前的ESO和BESO方法一样,用于验证两根钢筋框架问题,米歇尔型结构问题和三维短悬臂梁问题,这些方法已用于验证合理性ESO方法家族。对于三维短悬臂梁问题,相对于其他ESO方法的结果,可以通过更少的迭代获得优化的拓扑。

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