A practical satellite layout optimization design approach based on enhanced finite-circle method

Chen, Xianqi; Yao, Wen; Zhao, Yong; Chen, Xiaoqian; Zheng, Xiaohu

doi:10.1007/s00158-018-2042-z

Cited by 32 publications

(33 citation statements)

References 44 publications

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“…For 20 heat source items layout positions, SAR 50K could predict out 19 and 20 respectively to two samples. The results of sample (2) are visualized in Figure 10, which validates the general performance of SAR model.…”

Section: • Evaluating the General Test Samplesupporting

confidence: 63%

“…The objective of HSLD is to design the reasonable source layout scheme to offer the expected thermal environment for the whole system. With the increasingly smaller size of components and higher power intensity, HSLD has become a critical problem for the development of many fields such as microelectronic technology or satellite design [2]. However, most existing approaches for solving HSLD are based on optimization techniques, in which a large amount numerical simulation of temperature distribution is integrated into the optimization loop [3]- [5].…”

Section: Introductionmentioning

confidence: 99%

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A Deep Learning-Based Method for Heat Source Layout Inverse Design

Sun

Zhang²,

Zhang³

et al. 2020

IEEE Access

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Heat source layout design is an effective technique to enhance the thermal performance in the whole system, which has become a vital part in many engineering fields, e.g. satellite layout design and integrated circuit design. Traditionally, the optimal design is obtained by searching the design space with the optimization technique which repeatedly runs the thermal simulation to compare the performance of each scheme. Due to the extremely large computational burden with this method, the optimization is greatly limited. To overcome the challenge, heat source layout inverse design (HSLID) is proposed in this paper to directly generate the layout scheme with the given thermal performance requirement. A novel method for heat source layout inverse design, denoted as SAR-HSLID, is proposed based on the recently deep learning technique, Show Attend and Read (SAR) model. Firstly, regarding the mapping from the required temperature field to layout scheme as an image-to-location task, this paper introduces SAR model, which is good at sequence predicting, to generate the layout scheme. The trained SAR is capable of learning the underlying physics of the design problem, thus can efficiently predict the design under given requirement without any physical simulation. Secondly, to ensure that the designed heat source layout exactly satisfies the input temperature field requirement, based on the layout predicted by SAR, we further utilize a simple but efficient optimization process to conduct few post-processing. Finally, a heat source layout inverse design task in a typical two-dimensional heat conduction problem is investigated to demonstrate the feasibility and effectiveness of the proposed method.

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Section: • Evaluating the General Test Samplesupporting

confidence: 63%

Section: Introductionmentioning

confidence: 99%

A Deep Learning-Based Method for Heat Source Layout Inverse Design

Sun

Zhang²,

Zhang³

et al. 2020

IEEE Access

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show abstract

“…Satellite overall design is a typical multidisciplinary design optimization (MDO) problem [1][2][3]. Satellite layout optimization design (SLOD) is considered as a key step in the satellite MDO [4], which studies how to optimize the place position of satellite objects to ensure meeting the requirement of mission and engineering constraints. Previous work usually takes the moment of inertia as the objective [4].…”

Section: Introductionmentioning

confidence: 99%

“…Satellite layout optimization design (SLOD) is considered as a key step in the satellite MDO [4], which studies how to optimize the place position of satellite objects to ensure meeting the requirement of mission and engineering constraints. Previous work usually takes the moment of inertia as the objective [4]. The smaller moment of inertia means less energy that the whole satellite system consumes.…”

Section: Introductionmentioning

confidence: 99%

“…A new energy landscape paving heuristic method, as a kind of Monte-Carlo-based global optimization algorithm, is presented for satellite layout optimization design in [12]. Chen et al [4] proposed a practical satellite layout optimization design approach based on the enhanced finite circle method. These researches could obtain only one global optimal design scheme in one single optimization.…”

Section: Introductionmentioning

confidence: 99%

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A niching cross-entropy method for multimodal satellite layout optimization design

Sun

Chen

Zhang³

et al. 2021

Complex Intell. Syst.

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Satellite layout optimization design (SLOD) relies on solving a high-dimensional and multimodal optimization problem, in which there exist multiple global optimal solutions. Existing algorithms for SLOD focus on seeking only one approximate global optimum. However, finding multiple solutions simultaneously could provide more design diversity for the designers. To alleviate this problem, multimodal optimization method is studied for SLOD in this paper, and an improved niching-based cross-entropy method (INCE) is proposed. INCE consists of an improved niching strategy, cross-entropy method-based offspring generation and a cross operator. CEC2013 benchmarks and satellite layout optimization design problem are investigated to verify the validity and feasibility of the proposed INCE. Compared with several state-of-the-art algorithms, the proposed algorithm performs better.

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Multi-objective layout optimization for an orbital propellant depot

Jiang

Zhong

et al. 2019

Struct Multidisc Optim

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A practical satellite layout optimization design approach based on enhanced finite-circle method

Cited by 32 publications

References 44 publications

A Deep Learning-Based Method for Heat Source Layout Inverse Design

A Deep Learning-Based Method for Heat Source Layout Inverse Design

A niching cross-entropy method for multimodal satellite layout optimization design

Multi-objective layout optimization for an orbital propellant depot

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