A Surrogate-Model-Based Approach for the Optimization of the Thermal Design Parameters of Space Telescopes

doi:10.3390/app12031633

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	A Surrogate-Model-Based Approach for the Optimization of the Thermal Design Parameters of Space Telescopes
	W. B. Zhu; L. Guo; Z. H. Jia; D. F. Tian and Y. Xiong
	2022
发表期刊	Applied Sciences-Basel
卷号	12 期号:3 页码:15
摘要	The thermal design parameters of space telescopes are mainly optimized through traversal and iterative attempts. These optimization techniques are time consuming, rely heavily on the experience of the engineer, bear a large computational workload, and have difficulty in achieving optimal outcomes. In this paper, we propose a design method (called SMPO) based on an improved back-propagation neural network (called GAALBP) that builds a surrogate model and uses a genetic algorithm to optimize the model parameters. The surrogate model of a space telescope that measures the atmospheric density is established using GAALBP and then compared with surrogate models established using a traditional BP neural network and radial-basis-function neural network. The results show that the regression rate of the surrogate model based on the GAALBP reaches 99.99%, a mean square error of less than 2 x 10(-6), and a maximum absolute error of less than 4 x 10(-3). The thermal design parameters of the surrogate model are optimized using a genetic algorithm, and the optimization results are verified in a finite element simulation. Compared with the design results of the manually determined thermal design parameters, the maximum temperature of the CMOS is reduced by 5.33 degrees C, the minimum temperature is increased by 0.39 degrees C, and the temperature fluctuation is reduced by a factor of 4. Additionally, SMPO displays versatility and can be used in various complex engineering applications to provide guidance for the better selection of appropriate parameters and optimization.
DOI	10.3390/app12031633
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收录类别	sci
语种	英语
引用统计
文献类型	期刊论文
条目标识符	http://ir.ciomp.ac.cn/handle/181722/67139
专题	中国科学院长春光学精密机械与物理研究所
推荐引用方式 GB/T 7714	W. B. Zhu,L. Guo,Z. H. Jia,et al. A Surrogate-Model-Based Approach for the Optimization of the Thermal Design Parameters of Space Telescopes[J]. Applied Sciences-Basel,2022,12(3):15.
APA	W. B. Zhu,L. Guo,Z. H. Jia,&D. F. Tian and Y. Xiong.(2022).A Surrogate-Model-Based Approach for the Optimization of the Thermal Design Parameters of Space Telescopes.Applied Sciences-Basel,12(3),15.
MLA	W. B. Zhu,et al."A Surrogate-Model-Based Approach for the Optimization of the Thermal Design Parameters of Space Telescopes".Applied Sciences-Basel 12.3(2022):15.

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