Design optimization of space structures with nonperiodic geometries for vibration suppression
Design optimization of space structures with nonperiodic geometries for vibration suppression
This paper presents a computational framework for the design of large flexible space structures with non periodic geometries to achieve vibration suppression. The present system combines the use of an approximation model management framework (AMMF) developed for evolutionary optimization algorithms (EAs) with a reduced basis approximate dynamic reanalysis technique. A coevolutionary genetic search strategy is developed here to ensure that design changes during the optimization iterations lead to low-rank perturbations in the structural system matrices. The k-means algorithm is employed for cluster analysis of the population of designs to determine design points at which exact analysis should be carried out. Results are presented for optimal design of a 2D cantilevered space structure to achieve passive vibration suppression. It is shown that vibration isolation of the order of 30 dB over a 150 Hz bandwidth can be achieved. Further, it is demonstrated that the AMMF can potentially arrive at a better design compared to a conventional approach when optimization is constrained by a limited computational budget.
American Institute of Aeronautics and Astronautics
Nair, P.B.
d4d61705-bc97-478e-9e11-bcef6683afe7
Keane, A.J.
26d7fa33-5415-4910-89d8-fb3620413def
1999
Nair, P.B.
d4d61705-bc97-478e-9e11-bcef6683afe7
Keane, A.J.
26d7fa33-5415-4910-89d8-fb3620413def
Nair, P.B. and Keane, A.J.
(1999)
Design optimization of space structures with nonperiodic geometries for vibration suppression.
In Proceedings of the 40th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference and Exhibition.
American Institute of Aeronautics and Astronautics.
8 pp
.
Record type:
Conference or Workshop Item
(Paper)
Abstract
This paper presents a computational framework for the design of large flexible space structures with non periodic geometries to achieve vibration suppression. The present system combines the use of an approximation model management framework (AMMF) developed for evolutionary optimization algorithms (EAs) with a reduced basis approximate dynamic reanalysis technique. A coevolutionary genetic search strategy is developed here to ensure that design changes during the optimization iterations lead to low-rank perturbations in the structural system matrices. The k-means algorithm is employed for cluster analysis of the population of designs to determine design points at which exact analysis should be carried out. Results are presented for optimal design of a 2D cantilevered space structure to achieve passive vibration suppression. It is shown that vibration isolation of the order of 30 dB over a 150 Hz bandwidth can be achieved. Further, it is demonstrated that the AMMF can potentially arrive at a better design compared to a conventional approach when optimization is constrained by a limited computational budget.
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nair_99.pdf
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Published date: 1999
Additional Information:
AIAA-1999-1260
Venue - Dates:
40th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference and Exhibi, St. Louis, USA, 1999-04-12 - 1999-04-15
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Local EPrints ID: 21889
URI: http://eprints.soton.ac.uk/id/eprint/21889
PURE UUID: efc76b4e-38e8-4e2f-b0f9-96e588472549
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Date deposited: 16 Feb 2007
Last modified: 16 Mar 2024 02:53
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Author:
P.B. Nair
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