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基于拓扑-参数协同优化方法的声学覆盖层设计

Anechoic coating design based on topology-parameter co-optimization approach

  • 摘要: 针对传统拓扑优化方法在声学结构设计中存在设计变量单一的问题,文章提出了一种基于拓扑-参数协同优化的声学覆盖层设计方法。基于精英保留策略的遗传算法,构建了声学覆盖层拓扑-参数协同优化模型,同时将材料分布和基体材料参数作为设计变量,得到了优化后的声学覆盖层结构与材料配置。设计结果表明,在10 kHz全频段吸声性能方面,拓扑-参数协同优化结果的平均吸声系数达到了0.862,相较于单一拓扑优化结果提升了24.39%,吸声性能显著改善。但是在低频段,单一拓扑优化结果的吸声效果较好。此外,文章分析了杨氏模量等材料参数对声学覆盖层吸声系数的影响。该研究为寻找具有宽带高吸声性能的水下声学覆盖层结构及适配的基体材料提供了新的方法。

     

    Abstract: Considering the problem of single design variable in traditional topology optimization methods for acoustic structure design, this paper proposes a design method for acoustic covering layer based on topology-parameter collaborative optimization. By using the genetic algorithm with elite retention strategy, a topology-parameter collaborative optimization model for acoustic covering layer is constructed, and both material distribution and matrix material parameters are taken as design variables. The optimized acoustic covering layer structure and material configuration are obtained. The design results show that in the full frequency band of 10 kHz, the average sound absorption coefficient of the topology-parameter collaborative optimization result reaches 0.862, which is 24.39% higher than that of the single topology optimization result, and the improvement effect of sound absorption performance is significant. However, in the low-frequency band, the sound absorption effect of the single topology optimization result is better. In addition, this paper explores the influence of material parameters such as Young's modulus on the sound absorption coefficient of the acoustic covering layer. This study provides a new method for finding underwater acoustic covering layer structures with broadband high sound absorption performance and suitable matrix materials.

     

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