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樊冠恒,段宝岩.拓扑优化与仿生设计在空间太阳能电站热设计中的应用[J].计算力学学报,2021,38(4):445~451
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拓扑优化与仿生设计在空间太阳能电站热设计中的应用
Topology and bionic-based thermal design of space solar power station and the application in SSPS-OMEGA
投稿时间:2021-05-15  修订日期:2021-06-04
DOI:10.7511/jslx20210515405
中文关键词:  欧米伽空间太阳能电站  拓扑优化  仿蝴蝶翅膀设计  空间热设计与热控制
英文关键词:SSPS-OMEGA  topology optimization  bionic butterfly wing design  space thermal design and control
基金项目:国家自然科学基金重大项目(51775404;51607131);国家自然科学基金重点项目(U1637207)资助项目.
作者单位E-mail
樊冠恒 西安电子科技大学 机电科技研究所, 西安 710071  
段宝岩 西安电子科技大学 机电科技研究所, 西安 710071 byduan@xidian.edu.cn 
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中文摘要:
      高效热设计与热控制是高功率连续微波无线传能与空间太阳电站(SSPS)领域的研究热点之一,引起了国内外同行专家的高度关注与浓厚兴趣。本文针对欧米伽空间太阳能电站(SSPS-OMEGA)的结构特点及其对热设计与热控提出的巨大挑战,基于拓扑优化与仿生的思想,提出了一种新的热设计策略与方法。首先,联合流体出口边界与流道构型,建立最小化表面平均温度和流道压力损失的优化模型,得到陀螺馈源光伏阵上背板流道最优的出口位置与最佳拓扑构型,使馈源中的热量导出效率明显提高。其次,建立了仿蝴蝶翅膀形状与结构的对自由空间辐射散热的布局与拓扑优化模型,在满足性态前提下显著提升辐射效率。再者,分析推导了非线性目标和约束函数关于设计变量的灵敏度计算公式与迭代格式。最后,将本文模型与方法应用于欧米伽空间太阳能电站热设计,得到了满意的结果。
英文摘要:
      High efficiency thermal design and control is one of the most interested points in the field of high power continuous microwave wireless energy transfer and space solar power station (SSPS), which has attracted great attention and interest from experts all over the world. Based on topology optimization and bionics, a new thermal design methodology is proposed to face the challenge of thermal control in SSPS via orb-shape membrane energy gathering array (SSPS-OMEGA). Firstly, an optimization model is established to minimize the surface average temperature and flow channel pressure loss by combining the fluid flow outlet boundary and flow channel configuration, and the optimal outlet position and topological configuration of the flow channel of gyro photovoltaic back panel are obtained, by which the heat transfer efficiency can be improved obviously. Secondly, the layout and topology optimization model of free-space radiative heat dissipation is developed by analogy with the shape and structure of butterfly wings, and the radiative efficiency could be improved to a certain extend whilst satisfying the nonlinear behavior constraints. Furthermore, the sensitivity of the nonlinear objective and constraint functions with respect to design variables are mathematically deduced. Finally, several numerical experiments are given to demonstrate the strategy, model and method proposed in this manuscript.
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