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Improving machine dynamics via geometry optimization

Improving machine dynamics via geometry optimization
Improving machine dynamics via geometry optimization
The central thesis of this paper is that the dynamic performance of machinery can be improved dramatically in certain cases through a systematic and meticulous evolutionary algorithm search through the space of all structural geometries permitted by manufacturing, cost and functional constraints. This is a cheap and elegant approach in scenarios where employing active control elements is impractical for reasons of cost and complexity. From an optimization perspective the challenge lies in the efficient, yet thorough global exploration of the multi-dimensional and multi-modal design spaces often yielded by such problems. Morevoer, the designs are often defined by a mixture of continuous and discrete variables - a task that evolutionary algorithms appear to be ideally suited for. In this article we discuss the specific case of the optimization of crop spraying machinery for improved uniformity of spray deposition, subject to structural weight and manufacturing constraints. Using a mixed variable evolutionary algorithm allowed us to optimize both shape and topology. Through this process we have managed to reduce the maximum roll angle of the sprayer by an order of magnitude , whilst allowing only relatively inexpensive changes to the baseline design. Further (though less dramatic) improvements were shown to be possible when we relaxed the cost constraint. We applied the same approach to the inverse problem of reducing the mass while maintaining an acceptable roll angle - a 2% improvement proved possible in this case
1615-147X
547-558
Tudose, Lucian
e7e57cc0-b41b-452d-98c0-0c5547923c98
Stanescu, Cristina
1dcfe84e-2f27-42fb-bd97-aca1ad3f05a4
Sobester, Andras
096857b0-cad6-45ae-9ae6-e66b8cc5d81b
Tudose, Lucian
e7e57cc0-b41b-452d-98c0-0c5547923c98
Stanescu, Cristina
1dcfe84e-2f27-42fb-bd97-aca1ad3f05a4
Sobester, Andras
096857b0-cad6-45ae-9ae6-e66b8cc5d81b

Tudose, Lucian, Stanescu, Cristina and Sobester, Andras (2011) Improving machine dynamics via geometry optimization. Structural and Multidisciplinary Optimization, 44 (4), 547-558. (doi:10.1007/s00158-011-0641-z).

Record type: Article

Abstract

The central thesis of this paper is that the dynamic performance of machinery can be improved dramatically in certain cases through a systematic and meticulous evolutionary algorithm search through the space of all structural geometries permitted by manufacturing, cost and functional constraints. This is a cheap and elegant approach in scenarios where employing active control elements is impractical for reasons of cost and complexity. From an optimization perspective the challenge lies in the efficient, yet thorough global exploration of the multi-dimensional and multi-modal design spaces often yielded by such problems. Morevoer, the designs are often defined by a mixture of continuous and discrete variables - a task that evolutionary algorithms appear to be ideally suited for. In this article we discuss the specific case of the optimization of crop spraying machinery for improved uniformity of spray deposition, subject to structural weight and manufacturing constraints. Using a mixed variable evolutionary algorithm allowed us to optimize both shape and topology. Through this process we have managed to reduce the maximum roll angle of the sprayer by an order of magnitude , whilst allowing only relatively inexpensive changes to the baseline design. Further (though less dramatic) improvements were shown to be possible when we relaxed the cost constraint. We applied the same approach to the inverse problem of reducing the mass while maintaining an acceptable roll angle - a 2% improvement proved possible in this case

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Published date: 7 October 2011
Organisations: Faculty of Engineering and the Environment

Identifiers

Local EPrints ID: 180717
URI: http://eprints.soton.ac.uk/id/eprint/180717
ISSN: 1615-147X
PURE UUID: fbf2e2ce-7bae-4f52-a057-507e4a65479b
ORCID for Andras Sobester: ORCID iD orcid.org/0000-0002-8997-4375

Catalogue record

Date deposited: 13 Apr 2011 12:49
Last modified: 20 Jul 2019 01:03

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