| 匡兵,林瑞,刘夫云,周峰.一种基于自适应单元删除率的BESO方法[J].计算力学学报,2019,36(1):144~151 |
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| 一种基于自适应单元删除率的BESO方法 |
| A BESO method based on adaptive element removal ratio |
| 投稿时间：2017-09-22 修订日期：2018-03-29 |
| DOI：10.7511/jslx20170922001 |
| 中文关键词: BESO 单元删除率 单元灵敏度 均匀化程度 自适应 |
| 英文关键词:BESO element removal ratio element sensitivity homogenization degree self-adaption |
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| 中文摘要: |
| 在ESO中采用动态删除率能有效地提高优化效率和稳定性，但现有的动态删除率策略都含有经验参数，确定删除率的过程较为复杂。本文提出了一种用于BESO的无经验参数自适应单元删除率确定方法。通过分析单元删除率对优化稳定性的影响，得到了结构优化过程中单元删除率的理想变化规律和单元灵敏度均匀化信息对删除率的影响情况，并据此分析了经验参数引入的原因，从而构造了评价单迭代步的单元灵敏度均匀化程度指标。然后，基于单迭代步的单元灵敏度均匀化程度指标，构造了全部迭代步信息下的单元灵敏度均匀化程度相对指标，结合单元删除率的推荐范围值，给出了一种自适应于结构优化进程的单元删除率自适应函数。最后，给出了基于自适应单元删除率的BESO方法实现流程。经典算例的结果对比说明，本文方法在保证优化质量相近的情况下，具有更好的优化效率和稳定性。 |
| 英文摘要: |
| In ESO,dynamic removal ratio is a strategy that can effectively improve the optimization efficiency and stability.However,the existing dynamic removal ratio strategy contains empirical parameters,and the process of determining removal ratio is quite complex.Therefore,an adaptive element removal ratio determination method which has no empirical parameters for BESO is proposed in this paper.By analyzing the effect of element removal ratio on optimization stability,the ideal trend of element removal ratio and the effect of element sensitivity homogenization information on removal ratio are obtained in the process of structural optimization.Based on these,the reasons for the introduction of empirical parameters are analyzed,and an index of element sensitivity homogenization for evaluating a single iteration step is constructed.Then the relative index of element sensitivity homogenization degree under all iteration step information is constructed.Based on the element sensitivity homogenization index of a single iteration step,a function of element removal ratio adaptive to the process of structural optimization is given in combination with the recommended range of element removal ratio.Finally,the implementation procedure of BESO method based on the adaptive element removal ratio is presented.The comparison results of classical examples show that the proposed method has better optimization efficiency and stability while having similar quality in order aspects. |
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