计算力学学报
計算力學學報
계산역학학보
CHINESE JOURNAL OF COMPUTATIONAL MECHANICS
2015年
2期
274-279
,共6页
罗静%张大可%李海军%龚姣
囉靜%張大可%李海軍%龔姣
라정%장대가%리해군%공교
ESO%单元删除数量%删除策略%动态删除率
ESO%單元刪除數量%刪除策略%動態刪除率
ESO%단원산제수량%산제책략%동태산제솔
ESO%element deletion number%strategy for element deletion%dynamic deletion rate
渐进结构优化方法ESO(Evolutionary Structural Optimization)的基本思想是基于单元灵敏度,通过把无效或低效的单元逐步从结构中删除,从而得到优化的拓扑结构。经过20年的发展,其算法结构、理论研究以及实际工程应用领域已经取得了大量成果。在原始ESO算法中删除单元的数目是由固定删除率RR的取值决定的,设计者无法预期每一个迭代步删除单元的数量。对于一个初始满设计区域,合理的删除策略为随着迭代的进行,随着结构应力分布越均布,应该逐渐减少单元删除数量。基于此,本文构造了一种动态删除率,使得随着迭代的进行单元的删除数量逐渐减少,相对于前人构造的动态删除率更为简单明了,人为控制参数更少,并且通过算例证明该方法相比原始删除策略具有更好的优化效果。
漸進結構優化方法ESO(Evolutionary Structural Optimization)的基本思想是基于單元靈敏度,通過把無效或低效的單元逐步從結構中刪除,從而得到優化的拓撲結構。經過20年的髮展,其算法結構、理論研究以及實際工程應用領域已經取得瞭大量成果。在原始ESO算法中刪除單元的數目是由固定刪除率RR的取值決定的,設計者無法預期每一箇迭代步刪除單元的數量。對于一箇初始滿設計區域,閤理的刪除策略為隨著迭代的進行,隨著結構應力分佈越均佈,應該逐漸減少單元刪除數量。基于此,本文構造瞭一種動態刪除率,使得隨著迭代的進行單元的刪除數量逐漸減少,相對于前人構造的動態刪除率更為簡單明瞭,人為控製參數更少,併且通過算例證明該方法相比原始刪除策略具有更好的優化效果。
점진결구우화방법ESO(Evolutionary Structural Optimization)적기본사상시기우단원령민도,통과파무효혹저효적단원축보종결구중산제,종이득도우화적탁복결구。경과20년적발전,기산법결구、이론연구이급실제공정응용영역이경취득료대량성과。재원시ESO산법중산제단원적수목시유고정산제솔RR적취치결정적,설계자무법예기매일개질대보산제단원적수량。대우일개초시만설계구역,합리적산제책략위수착질대적진행,수착결구응력분포월균포,응해축점감소단원산제수량。기우차,본문구조료일충동태산제솔,사득수착질대적진행단원적산제수량축점감소,상대우전인구조적동태산제솔경위간단명료,인위공제삼수경소,병차통과산예증명해방법상비원시산제책략구유경호적우화효과。
T he main idea of the evolutionary structural optimization ESO method is that the invalid ele‐ment gradually be removed from the structure based on the element sensitivity ,and so the topology opti‐mization result is formed .T he element deletion number in the original ESO algorithm is decided by the value of rejection ration(RR) ,and the designer cannot expect the element deletion number every itera‐tion .For an initial full design area ,a reasonable strategy for element deletion should gradually reduce the number of element deletion as the iteration proceeds ,w hile the structural stress distribution is more uni‐form .Based on this ,this paper constructs a dynamic deletion rate ,the element deletion number gradually reduce as the iteration proceeds .It is more simple ,and has less controlled parameters relative to the pre‐vious dynamic deletion rates .Through the examples it shows that the method can get slightly a better optimization effect compared with the original deletion strategies .