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Structural and Multidisciplinary Optimization
Erschienen in: Structural and Multidisciplinary Optimization 1/2013

01.07.2013 | Research Paper

Grammatical evolution of shape and its application to structural shape optimisation

verfasst von: Alkin Nasuf, Atul Bhaskar, Andy J. Keane

Erschienen in: Structural and Multidisciplinary Optimization | Ausgabe 1/2013

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Abstract

We propose an automated shape generative framework, which provides an alternative way of exploring the design space in a structural mechanics context. The framework presented uses “blind” evolutionary intelligence to synthesise shape grammar sentences i.e. Grammatical Evolution (GE), where rules are selected by a Genetic Algorithm (GA). This is a novel approach to automate the Shape Grammar (SG) formalism. We then present an application of a grammar based shape generative framework to solve a 2D design optimisation problem. This involves synthesis of parametric 2D curves where the shape grammar primitives are introduced as arcs represented by rotation and a radius. The efficacy of the proposed shape generative framework is then compared with that of Non-Uniform Rational B-Splines (NURBS) parametrisation for structural optimisation.
Vorheriger Artikel Topology optimization of a cantilevered piezoelectric energy harvester using stress norm constraints
Nächster Artikel Many objective visual analytics: rethinking the design of complex engineered systems

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Metadaten
Titel
Grammatical evolution of shape and its application to structural shape optimisation
verfasst von
Alkin Nasuf
Atul Bhaskar
Andy J. Keane
Publikationsdatum
01.07.2013
Verlag
Springer-Verlag
Erschienen in
Structural and Multidisciplinary Optimization / Ausgabe 1/2013
Print ISSN: 1615-147X
Elektronische ISSN: 1615-1488
DOI
https://doi.org/10.1007/s00158-013-0890-0

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