Design optimization of truss structures is a popular topic in aerospace,
mechanical, civil, and structural engineering due to benefits to industry.
Common design problem for the structures is the weight minimization.
Especially in aerospace engineering the minimization of the weight of the total
structure gets the highest importance in the design.
This study focuses on the design optimization of 2D and 3D truss structures.
The objective function is the total mass of the structure which is subjected to
stress and nodal displacement constraints. To optimize the design, Genetic
Algorithm (GA) is preferred due to its efficiency in dealing with problems with
discrete design variables as in the case of truss structures. This technique
yields more realistic results than linear programming methods.
In the thesis, a finite element code is developed for the analysis of planar and
space truss structures. The developed finite element solver is coupled with a
genetic algorithm optimization code which is also developed as a part of the
thesis study. Different truss optimization case studies are performed to
demonstrate the performance of the finite element solver and the genetic
algorithm optimization code that are developed. It is shown that with the use
of adaptive penalty function employing scaled fitnesses, the arbitrariness
issue of the factor multiplying the error term in the augmented fitness
function can be resolved. It is also shown that significant weight reduction can
v
be achieved by employing shape optimization together with size optimization
compared to pure size optimization.
| Identifer | oai:union.ndltd.org:METU/oai:etd.lib.metu.edu.tr:http://etd.lib.metu.edu.tr/upload/12614932/index.pdf |
| Date | 01 October 2012 |
| Creators | Unalmis, Dilek |
| Contributors | Kayran, Altan |
| Publisher | METU |
| Source Sets | Middle East Technical Univ. |
| Language | English |
| Detected Language | English |
| Type | M.S. Thesis |
| Format | text/pdf |
| Rights | To liberate the content for public access |
Page generated in 0.002 seconds