Xi Zhipeng, Lu Xiaochi, Shen Tongsheng, Zou Chunrong, Chen Li, Guo Shaojun
National Institute of Defense Technology Innovation, Academy of Military Sciences PLA China, Beijing 100171, China.
Materials (Basel). 2023 Jul 25;16(15):5229. doi: 10.3390/ma16155229.
Metamaterials are usually designed using biomimetic technology based on natural biological characteristics or topology optimization based on prior knowledge. Although satisfactory results can be achieved to a certain extent, there are still many performance limitations. For overcoming the above limitations, this paper proposes a rapid metamaterials design method based on the generation of random topological patterns. This method realizes the combined big data simulation and structure optimization of structure-electromagnetic properties, which makes up for the shortcomings of traditional design methods. The electromagnetic properties of the proposed metamaterials are verified by experiments. The reflection coefficient of the designed absorbing metamaterial unit is all lower than -15 dB over 12-16 GHz. Compared with the metal floor, the radar cross section (RCS) of the designed metamaterial is reduced by a minimum of 14.5 dB and a maximum of 27.6 dB over the operating band. The performance parameters of metamaterial obtained based on the random topology design method are consistent with the simulation design results, which further verifies the reliability of the algorithm in this paper.
超材料通常采用基于自然生物特性的仿生技术或基于先验知识的拓扑优化来设计。虽然在一定程度上可以取得令人满意的结果，但仍存在许多性能限制。为克服上述限制，本文提出了一种基于随机拓扑图案生成的超材料快速设计方法。该方法实现了结构 - 电磁特性的大数据模拟与结构优化相结合，弥补了传统设计方法的不足。所提出的超材料的电磁特性通过实验得到验证。设计的吸收型超材料单元在12 - 16GHz范围内的反射系数均低于 - 15dB。与金属地板相比，所设计的超材料在工作频段内的雷达散射截面（RCS）最小降低了14.5dB，最大降低了27.6dB。基于随机拓扑设计方法获得的超材料性能参数与模拟设计结果一致，进一步验证了本文算法的可靠性。
