Evolutionary multi-objective optimization of truss topology for additively manufactured components

被引:7
|
作者
David, Petr [1 ]
Mares, Tomas [1 ]
Chakraborti, Nirupam [1 ]
机构
[1] Czech Tech Univ, Fac Mech Engn, Dept Mech Biomech & Mechatron, Prague, Czech Republic
关键词
Truss; topology; evolutionary; genetic; algorithms; optimization; multi-objective; mechanics; 3D printing; additive; manufacturing; EvoDN2; deep; learning; GENETIC ALGORITHMS;
D O I
10.1080/10426914.2023.2196325
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
This paper focuses on the use of truss topology optimization using an evolutionary approach to find optimized, additively manufactured components through a multi-objective formulation, keeping in mind application areas like 3D printing. Additive manufacturing plays a key role here, as the inherent complexity of most optimized truss structures would not allow for any different manufacturing techniques. The multi-optimization formulation consists of optimizing two conflicting objectives: minimization of structural compliance and minimization of heat flowing from the structure to its supports. A background on truss topology optimization, including a literature overview and the motivation behind the problem, is presented. The physical models and the optimization algorithms are explained and afterward, an example problem is solved and analyzed.
引用
收藏
页码:1922 / 1931
页数:10
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