Metamaterials are designed by arranging artificial structural elements according to periodic geometries to obtain advantageous and unusual properties when they are hit by waves. Initially designed to interact with electromagnetic waves, their use naturally extended to sound waves, proving to be particularly useful for the construction of containment and soundproofing systems in buildings. In this work, a new metamaterial has been developed with the use of a polyvinyl chloride membrane on which buttons have been glued. Two types of buttons were used, with different weights, placing them on the membrane according to a radial geometry. Each sample of metamaterial was subjected to sound absorption coefficient measurements using the impedance tube. Measurements were made using the samples by setting three configurations, creating a cavity with different thicknesses. The results of the measurements were subsequently used as input for training a simulation model based on artificial neural networks. The model showed an excellent generalization capacity, returning estimates of the acoustic absorption coefficient of the metamaterial very similar to the measured value. Subsequently, the model was used to perform a sensitivity analysis to evaluate the contribution of the various input variables on the returned output.

中文翻译：

---

使用神经网络数据拟合基于重复使用按钮的声学超材料建模

超材料是通过根据周期性几何形状排列人造结构元素来设计的，以便在受到波浪冲击时获得有利和不寻常的特性。最初设计用于与电磁波相互作用，它们的用途自然扩展到声波，事实证明对于建筑物中的密封和隔音系统的构建特别有用。在这项工作中，使用粘有按钮的聚氯乙烯膜开发了一种新的超材料。使用了两种不同重量的按钮，根据径向几何将它们放置在膜上。使用阻抗管对每个超材料样品进行吸声系数测量。通过设置三种配置使用样品进行测量，创建不同厚度的空腔。测量结果随后被用作训练基于人工神经网络的仿真模型的输入。该模型显示出极好的泛化能力，返回的超材料吸声系数的估计值与测量值非常相似。随后，该模型用于执行敏感性分析，以评估各种输入变量对返回输出的贡献。