基于束能推进的微波加热效率仿真

杨浩; 闫二艳

doi:10.11949/j.issn.0438-1157.20181431

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基于束能推进的微波加热效率仿真

流体力学与传递现象 | 更新时间：2020-06-24

- 基于束能推进的微波加热效率仿真
- Simulation research of microwave heating efficiency for beamed energy thruster
- 化工学报 2019年第S1期页码：93-98
- 作者机构：
  
  中国工程物理研究院应用电子学研究所，高功率微波技术重点实验室，四川绵阳621900
- 作者简介：
  
  杨浩（1992—），男，助理研究员，mushui9@qq.com
  闫二艳（1978—），女，博士，副研究员，yaneryan_2002@163.com
- 基金信息：
  
  装备预研基金项目
- DOI：10.11949/j.issn.0438-1157.20181431
  中图分类号： TM 924.76
- 收稿：2018-11-30，
  
  修回：2018-12-10，
- 稿件说明：
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杨浩, 闫二艳. 基于束能推进的微波加热效率仿真[J]. 化工学报, 2019, 70(S1): 93-98

YANG Hao, YAN Eryan. Simulation research of microwave heating efficiency for beamed energy thruster[J]. CIESC Journal, 2019, 70(S1): 93-98
杨浩, 闫二艳. 基于束能推进的微波加热效率仿真[J]. 化工学报, 2019, 70(S1): 93-98 DOI： 10.11949/j.issn.0438-1157.20181431.

YANG Hao, YAN Eryan. Simulation research of microwave heating efficiency for beamed energy thruster[J]. CIESC Journal, 2019, 70(S1): 93-98 DOI： 10.11949/j.issn.0438-1157.20181431.

摘要

微波束能推进是一种新的微波能传输利用方式，使用高强度吸波材料将电磁能转化为热能。针对其热交换器系统构建了简化能量接收模型，对毫米波加热能量转换效率及最高温度进行了初步研究，并设计了三种结构进行模拟仿真，最高效率超过30%，稳定效率在23%左右。使用遗传算法对影响性能的参数进行了优化，结果表明热交换器性能受吸波材料有效损耗因子影响，应保持在一个适中的水平。

Abstract

Microwave beamed energy thruster is a kind of delivery tool using ground microwave beams to provide the energy to launch to the Earth 1st orbit from ground. The energy conversion is different with conventional microwave heating. In order to study the energy efficiency

the report gives a simple energy receiving module of thermal exchange system to simulate conversion process. Millimeter wave heating efficiency as well as maximum temperature have been analysised with the module. Further more

three fabric of exchange system was designed for 2-D simulation to explore the influence of structure. Genetic algorithm was used to optimize the parameters affecting the performance. Simulation results show that thermal exchange system performance follow with material permittivity damping which expected to be moderate. The maximum energy efficiency is over 30%

and the stabilization efficiency is around 23%.

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references

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