Structural Topology Design Using Compliance Pattern Based Genetic Algorithm

2009 ◽  
Vol 33 (8) ◽  
pp. 786-792 ◽  
Author(s):  
Young-Oh Park ◽  
Seung-Jae Min
1996 ◽  
Vol 118 (1) ◽  
pp. 89-98 ◽  
Author(s):  
C. D. Chapman ◽  
M. J. Jakiela

The genetic algorithm (GA), an optimization technique based on the theory of natural selection, is applied to structural topology design problems. After reviewing the genetic algorithm and previous research in structural topology optimization, we detail the chromosome-to-design representation which enables the genetic algorithm to perform structural topology optimization. Extending our prior investigations, this article first compares our genetic-algorithm-based technique with homogenization methods in the minimization of a structure’s compliance subject to a maximum volume constraint. We then use our technique to generate topologies combining high structural performance with a variety of material connectivity characteristics which arise directly from our discretized design representation. After discussing our findings, we describe potential future work.


Author(s):  
Colin D. Chapman ◽  
Mark J. Jakiela

Abstract The genetic algorithm, a search and optimization technique based on the theory of natural selection, is applied to structural topology design problems with compliance and manufacturability considerations. After describing the genetic algorithm and reviewing previous research in structural topology design, we detail the chromosome-to-design representation which enables the genetic algorithm to perform structural topology optimization. Extending our prior investigations, this article details the use of our genetic algorithm-based technique to minimize a structure’s compliance, subject to a maximum volume constraint. The resulting structure is then directly compared with a solution obtained using a mathematical programming technique and material homogenization methods. We also demonstrate how our technique can generate structures which combine high stiffness-to-weight ratio with high manufacturability. After a brief discussion of our findings, we describe potential future work in genetic algorithm-based structural topology design.


1994 ◽  
Vol 116 (4) ◽  
pp. 1005-1012 ◽  
Author(s):  
C. D. Chapman ◽  
K. Saitou ◽  
M. J. Jakiela

The genetic algorithm, a search and optimization technique based on the theory of natural selection, is applied to problems of structural topology design. An overview of the genetic algorithm will first describe the genetics-based representations and operators used in a typical genetic algorithm search. Then, a review of previous research in structural optimization is provided. A discretized design representation, and methods for mapping genetic algorithm “chromosomes” into this representation, is then detailed. Several examples of genetic algorithm-based structural topology optimization are provided: we address the optimization of cantilevered plate topologies, and we investigate methods for optimizing finely-discretized design domains. The genetic algorithm’s ability to find families of highly-fit designs is also examined. Finally, a description of potential future work in genetic algorithm-based structural topology optimization is offered.


2020 ◽  
Vol 46 ◽  
pp. 101162
Author(s):  
Dennis P.H. Claessens ◽  
Sjonnie Boonstra ◽  
Hèrm Hofmeyer

2000 ◽  
Vol 17 (6) ◽  
pp. 715-734 ◽  
Author(s):  
Qing Li ◽  
Grant P. Steven ◽  
Osvaldo M. Querin ◽  
Y.M. Xie

Author(s):  
Ciro A. Soto

Abstract A new approach to design the topology for structures under crash events is presented. The approach is heuristic in essence, but numerical experiments have shown its uses in real problems. Using an interpolation between porous and solid (non-porous) materials plus a re-design rule to by-pass gradient computations the new approach is able to determine better locations of material and density in a given structural domain for kinetic energy dissipation. An example is presented to illustrate the methodology.


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