Numerical Methods for Efficient Acoustic Metamaterial Design

• Applicant: Professor Dr.-Ing. Steffen Marburg
• Subject Area: Acoustics
• Term: since 2024
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 545835419

Noise pollution due to transport or industrial activities is one of largest threats for the environment and may cause severe health problems. Therefore, noise mitigation plays an essential role for engineering design. In the current engineering practice, this is usually achieved by adding damping treatments in a late phase of the design process or even after manufacturing has begun. The resulting increase in mass can be significant and deteriorates the ecological footprint of the product. In recent years, acoustic metamaterials have attracted scientific attention and are considered a promising solution for finding the delicate balance between lightweight design and quietness. The overarching goal of this project is to develop efficient numerical methods for design optimization of elastic and acoustic metamaterials. This goal will be achieved by combining expertise in acoustic engineering and numerical linear algebra. As acoustic metamaterials consist of periodic arrangements of unit cells (so-called metaatoms), the periodicity is also present in the parameter-dependent linear systems of equations arising in the corresponding FEM-BEM models. In this project, efficient structure-exploiting numerical methods for their solution will be developed. This will be a great benefit for model order reduction and also enables computational design optimization. One aim is to optimize the resonance frequencies of the metamaterial by nonlinear eigenvalue optimization. Additionally, we will consider the actual load cases that result in H-infinity optimization problems. The new computational techniques will be tested on relevant industrial benchmark models and then be put into engineering practice.

• DFG Programme: Research Grants
• International Connection: Switzerland
• Partner Organisation: Schweizerischer Nationalfonds (SNF)
• Cooperation Partner: Professor Dr. Matthias Voigt