理论分析,基于神经网络的反向设计和多层薄板声学元材料单元细胞的实验验证
1Hubei Key Laboratory of Modern Manufacturing Quality Engineering, School of Mechanical Engineering, Hubei University of Technology, Wuhan 430068, China.
Materials (Basel, Switzerland)
|January 10, 2026
概括
使用附着质量的薄板进行工程声学元材料,提供卓越的低频隔音. 一个新的神经网络框架使这些复杂的多层结构的有效反向设计成为可能.
科学领域:
- 声学超材料是一种声学超材料.
- 振动力学 振动力学
- 计算材料科学 计算材料科学
背景情况:
- 声学超材料利用亚波长结构来实现先进的隔音.
- 薄板声学元材料是由薄板上的共振质块形成的,在低至中频率中表现出色.
- 多层设计提高性能,但引入显著的设计复杂性.
研究的目的:
- 为多层复合薄板声学元材料开发一个系统的,神经网络辅助的反向设计框架.
- 为了克服复杂的声学超材料的传统设计方法的低效.
- 为低频隔音提供高效的解决方案.
主要方法:
- 建立了使用点匹配和模态叠加的多重附着质量的薄板元材料的分析模型.
- 通过数值模拟构建了多层复合单元细胞,并通过数值模拟生成了大量数据集 (3万个样本).
- 开发和训练前预测和反向设计的神经网络.
主要成果:
- 分析模型通过有限元模拟来验证.
- 未来预测网络的测试误差为1.06%.
- 反向设计网络的误差为2.27%,结构通过实验验证.
结论:
- 成功建立了一个新的理论和计算框架,用于薄板声学元材料的反向设计.
- 神经网络方法有效地解决了设计复杂性和参数非唯一性.
- 拟议的方法为设计高性能低频隔音提供了一个实际的解决方案.
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