An efficient multi-objective optimization framework for thin-walled tubular deployable composite boom
An efficient multi-objective optimization framework for thin-walled tubular deployable composite boom
As a crucial structural component in space applications such as solar sails and solar arrays, the thin-walled tubular deployable composite booms (DCBs) demonstrate extensive utilization by employing stored elastic strain energy to achieve folding and deploying functions. This paper introduces a multi-objective optimization framework that integrates an analytical model with a genetic algorithm. By utilizing a multi-objective evolutionary algorithm based on de-composition (MOEA/D), the optimization objectives of minimizing folding moment and maximizing bending stiffness are pursued. Multiple constraints associated with failure avoidance, laminate stacking sequence design principles, and the folding moment range of actuator in the folding mechanism are considered in the optimization. The multi-objective optimization design of the tubular DCBs is performed to obtain the optimal combinations of cross-sectional radius, central angle, and ply scheme. Experimental validation confirms the efficacy of the optimization results. Additionally, an in-depth analysis on the influence of genetic algorithm types, hyperparameters, and different design variables on the optimization outcomes is thoroughly discussed. The findings of this study offer significantly insights for the practical engineering applications of tubular DCBs.
Deployable composite booms (DCBs), Genetic algorithm, MOEA/D, Multi-objective optimization
Bai, Jiang Bo
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You, Fei Yan
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Wang, Zhen Zhou
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Fantuzzi, Nicholas
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Liu, Qing
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Xi, Hao Tian
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Bu, Guang Yu
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Wang, Yong Bin
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Wu, Shi Qing
b9500dff-7f63-47ca-a098-5626f294ff9c
Feng, Rui
508ac808-496d-4a33-8f3e-f062ef4a03e8
Liu, Tian Wei
45837a5e-880b-4974-b150-556b50c4ca14
1 January 2024
Bai, Jiang Bo
737812f0-24ca-4b03-9b12-ef48dd3da0b6
You, Fei Yan
186d6605-8f83-4b15-9c80-48d971d6cc83
Wang, Zhen Zhou
794c41fe-f5da-4da4-8f1c-c7beb06f87eb
Fantuzzi, Nicholas
b41008d9-9c32-49ef-b71d-cddaa6fe1730
Liu, Qing
71cbdaa7-df90-4a5c-9a3e-d924a8e5c1fb
Xi, Hao Tian
1a373837-6489-4819-a50e-f43a527226d1
Bu, Guang Yu
c16efac6-8a40-4ac8-94d6-585e4baf0fc9
Wang, Yong Bin
1098169c-8302-4958-9c23-84745b7b61db
Wu, Shi Qing
b9500dff-7f63-47ca-a098-5626f294ff9c
Feng, Rui
508ac808-496d-4a33-8f3e-f062ef4a03e8
Liu, Tian Wei
45837a5e-880b-4974-b150-556b50c4ca14
Bai, Jiang Bo, You, Fei Yan, Wang, Zhen Zhou, Fantuzzi, Nicholas, Liu, Qing, Xi, Hao Tian, Bu, Guang Yu, Wang, Yong Bin, Wu, Shi Qing, Feng, Rui and Liu, Tian Wei
(2024)
An efficient multi-objective optimization framework for thin-walled tubular deployable composite boom.
Composite Structures, 327, [117713].
(doi:10.1016/j.compstruct.2023.117713).
Abstract
As a crucial structural component in space applications such as solar sails and solar arrays, the thin-walled tubular deployable composite booms (DCBs) demonstrate extensive utilization by employing stored elastic strain energy to achieve folding and deploying functions. This paper introduces a multi-objective optimization framework that integrates an analytical model with a genetic algorithm. By utilizing a multi-objective evolutionary algorithm based on de-composition (MOEA/D), the optimization objectives of minimizing folding moment and maximizing bending stiffness are pursued. Multiple constraints associated with failure avoidance, laminate stacking sequence design principles, and the folding moment range of actuator in the folding mechanism are considered in the optimization. The multi-objective optimization design of the tubular DCBs is performed to obtain the optimal combinations of cross-sectional radius, central angle, and ply scheme. Experimental validation confirms the efficacy of the optimization results. Additionally, an in-depth analysis on the influence of genetic algorithm types, hyperparameters, and different design variables on the optimization outcomes is thoroughly discussed. The findings of this study offer significantly insights for the practical engineering applications of tubular DCBs.
Text
Deployable composite boom optimisation study - final manuscript
- Accepted Manuscript
Restricted to Repository staff only until 8 November 2025.
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More information
Accepted/In Press date: 7 November 2023
e-pub ahead of print date: 8 November 2023
Published date: 1 January 2024
Additional Information:
Funding Information:
This project was supported by the National Natural Science Foundation of China (Grant No. 52275231 and Grant No. 51875026), the National Key R&D Program of China (Grant No. 2022YFB4301000), Open Fund of Laboratory of Aerospace Entry, Descent and Landing Technology (Grant No. EDL19092204 and Grant No. EDL19092129), the Academic Excellence Foundation of BUAA for PhD Students, and the China Scholarship Council (Grant No. 202106020152).
Keywords:
Deployable composite booms (DCBs), Genetic algorithm, MOEA/D, Multi-objective optimization
Identifiers
Local EPrints ID: 485862
URI: http://eprints.soton.ac.uk/id/eprint/485862
ISSN: 0263-8223
PURE UUID: 4651cf49-ee44-4825-bc97-434302731af9
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Date deposited: 03 Jan 2024 16:17
Last modified: 17 Mar 2024 13:42
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Contributors
Author:
Jiang Bo Bai
Author:
Fei Yan You
Author:
Zhen Zhou Wang
Author:
Nicholas Fantuzzi
Author:
Qing Liu
Author:
Hao Tian Xi
Author:
Guang Yu Bu
Author:
Yong Bin Wang
Author:
Shi Qing Wu
Author:
Rui Feng
Author:
Tian Wei Liu
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