類免疫基因演算法於結構拓樸最佳化之研究

Structural Topology Optimization by Artificial Immune System and Genetic Algorithm

林廷釗(Lin-Ting Chao)

指導教授 ： 張永康

淡江大學/工學院/航空太空工程學系碩士班/碩士(2009年)

https://doi.org/10.6846/TKU.2009.01096

摘要

本論文是應用類免疫基因演算法於結構拓樸最佳化設計之研究。研究中使用ANSYS做為結構分析的工具，並利用拓樸設計方法中之複合材料分配法配合線性規劃法與類免疫基因演算法以獲得最佳結構。在本文中利用線性規劃法找出初始結構，再以基因演算法對現有結構改善不必要之模糊元素與結構不連續性以求得更佳之結構外形，最後再以類免疫演算法之體細胞高度突變，利用輕重鏈突變，改善基因演算法所獲得之拓樸外形。應用以上之演算技術可以達到最小結構順從度，並滿足體積之限制要求，而且得到較合理之拓樸結構。
本研究以六個不同結構範例執行結構最佳化設計，不管是二維平面之結構甚至到三維之結構，可以明顯看出吾人所採用的方法在拓樸設計上之效用，並能得到明確的結構幾何形狀，更可提供製造加工上之便利性。

關鍵字

類免疫演算法 ； 基因演算法 ； 拓樸最佳化

並列摘要

A methodology of topology optimization design by Artificial Immune System and Genetic Algorithm was used in this study. The finite element analysis software ANSYS was used for structural analysis. The optimal topology design was obtained by the concept of material distribution borrowed from density method with Linear Programming, Artificial Immune System and Genetic Algorithm. The first stage topology design was executed by linear programming, then the 2nd stage was used by Genetic Algorithm to improve the unnecessary and discontinuity element. The final stage was used by somatic hypermutation of Artificial Immune System to employ the different mutation range to eliminate indefinite element which obtained by Genetic Algorithm. Finally, the smallest compliance and reasonable topology design shape were obtain by the above techniques.
There are six different structures were discussed in this study. The final results of optimum design was better than the first stage design in two dimensional as well as three dimensional structures. The proposed algorithm in this study was proved effectively.

並列關鍵字

Artificial Immune System ； Genetic Algorithm ； Topology Optimization

參考文獻

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