Using the sequential linear integer programming method as a post-processor for stress-constrained topology optimization problems

This paper deals with topology optimization of load‐carrying structures defined on discretized continuum design domains. In particular, the minimum compliance problem with stress constraints is considered. The finite element method is used to discretize the design domain into n finite elements and t...

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Veröffentlicht in:International journal for numerical methods in engineering Jg. 76; H. 10; S. 1544 - 1567
1. Verfasser: Werme, M.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Chichester, UK John Wiley & Sons, Ltd 03.12.2008
Wiley
Schlagworte:
0-1 problems
Applied mathematics
Computational techniques
Exact sciences and technology
Fundamental areas of phenomenology (including applications)
MATEMATIK
Mathematical methods in physics
MATHEMATICS
Optimeringslära, systemteori
Optimization, systems theory
Physics
post-processing
Solid mechanics
Static elasticity (thermoelasticity...)
stress constraints
Structural and continuum mechanics
Tillämpad matematik
topology optimization
Lower bound
Geometrical shape
post-processing
Linear programming
0-1 problems
Topology
Modeling
Moving asymptote
Constrained optimization
Continuum
Finite element method
Integer programming
Zero one programming
Sequential method
topology optimization
Non linear effect
stress constraints
ISSN:0029-5981, 1097-0207, 1097-0207
Online-Zugang:Volltext
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Beschreibung
Zusammenfassung:This paper deals with topology optimization of load‐carrying structures defined on discretized continuum design domains. In particular, the minimum compliance problem with stress constraints is considered. The finite element method is used to discretize the design domain into n finite elements and the design of a certain structure is represented by an n‐dimensional binary design variable vector. In order to solve the problems, the binary constraints on the design variables are initially relaxed and the problems are solved with both the method of moving asymptotes and the sparse non‐linear optimizer solvers for continuous optimization in order to compare the two solvers. By solving a sequence of problems with a sequentially lower limit on the amount of grey allowed, designs that are close to ‘black‐and‐white’ are obtained. In order to get locally optimal solutions that are purely {0, 1}n, a sequential linear integer programming method is applied as a post‐processor. Numerical results are presented for some different test problems. Copyright © 2008 John Wiley & Sons, Ltd.
Bibliographie:ark:/67375/WNG-SMQ94R09-0
ArticleID:NME2378
Swedish Research Council - No. 621-2002-5280
istex:611840AAF02C37AC42E06ADC2CDEB1BEE9F7AD9B
ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:0029-5981
1097-0207
1097-0207
DOI:10.1002/nme.2378