Genetic Algorithm-Based Structural Topology Design With Compliance and Manufacturability Considerations

1994 ◽  
Author(s):  
Colin D. Chapman ◽  
Mark J. Jakiela
Keyword(s):  
Genetic Algorithm ◽  
Optimization Technique ◽  
Weight Ratio ◽  
Topology Design ◽  
Structural Topology ◽  
Programming Technique ◽  
Design Representation ◽  
Homogenization Methods ◽  
Future Work ◽  
Structural Topology Design

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.

Genetic Algorithm-Based Structural Topology Design With Compliance and Topology Simplification Considerations

1996 ◽  
Vol 118 (1) ◽  
pp. 89-98 ◽  
Author(s):  
C. D. Chapman ◽  
M. J. Jakiela
Keyword(s):  
Genetic Algorithm ◽  
Topology Optimization ◽  
Optimization Technique ◽  
Topology Design ◽  
Structural Topology Optimization ◽  
Structural Topology ◽  
Design Representation ◽  
Homogenization Methods ◽  
Future Work ◽  
Structural Topology Design

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.

scholarly journals Genetic Algorithms as an Approach to Configuration and Topology Design

1994 ◽  
Vol 116 (4) ◽  
pp. 1005-1012 ◽  
Author(s):  
C. D. Chapman ◽  
K. Saitou ◽  
M. J. Jakiela
Keyword(s):  
Genetic Algorithm ◽  
Topology Optimization ◽  
Optimization Technique ◽  
Topology Design ◽  
Structural Topology Optimization ◽  
Structural Topology ◽  
Design Representation ◽  
Future Work ◽  
Structural Topology Design ◽  
Algorithm Search

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.

scholarly journals Genetic Algorithms As an Approach to Configuration and Topology Design

1993 ◽  
Author(s):  
Colin D. Chapman ◽  
Kazuhiro Saitou ◽  
Mark J. Jakiela
Keyword(s):  
Genetic Algorithm ◽  
Topology Optimization ◽  
Structural Optimization ◽  
Optimization Technique ◽  
Topology Design ◽  
Structural Topology Optimization ◽  
Structural Topology ◽  
Element Analysis ◽  
Structure Topology ◽  
Design Representation

Abstract The Genetic Algorithm, a search and optimization technique based on the theory of natural selection, is applied to problems of structural topology optimization. Given a structure’s boundary conditions and maximum allowable design domain, a discretized design representation is created. Populations of genetic algorithm “chromosomes” are then mapped into the design representation, creating potentially optimal structure topologies. Utilizing genetics-based operators such as crossover and mutation, generations of increasingly-desirable structure topologies are created. In this paper, the use of the genetic algorithm (GA) in structural topology optimization is presented. An overview of the genetic algorithm will describe the genetics-based representations and operators used in a typical genetic algorithm search. After defining topology optimization and its relation to the broader area of structural optimization, a review of previous research in GA-based and non-GA-based structural optimization is provided. The design representations, and methods for mapping genetic algorithm “chromosomes” into structure topology representations, are then detailed. Several examples of genetic algorithm-based structural topology optimization are provided: we address the optimization of beam cross-section topologies and cantilevered plate topologies, and we also investigate efficient techniques for using finite element analysis in a genetic algorithm-based search. Finally, a description of potential future work in genetic algorithm-based structural topology optimization is offered.

scholarly journals Spatial zoning for better structural topology design and performance

2020 ◽  
Vol 46 ◽  
pp. 101162
Author(s):  
Dennis P.H. Claessens ◽  
Sjonnie Boonstra ◽  
Hèrm Hofmeyer
Keyword(s):  
Topology Design ◽  
Structural Topology ◽  
And Performance ◽  
Structural Topology Design

Structural topology design with multiple thermal criteria

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

Optimal Structural Topology Design for Energy Absorption: A Heuristic Approach

2001 ◽  
Author(s):  
Ciro A. Soto
Keyword(s):  
Energy Dissipation ◽  
Kinetic Energy ◽  
Porous Materials ◽  
Numerical Experiments ◽  
Topology Design ◽  
Design Rule ◽  
Structural Domain ◽  
Structural Topology ◽  
New Approach ◽  
Structural Topology Design

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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