Novel inverse multi-objective optimization-empowered design of microperforated panels for enhanced low-frequency noise mitigation

TL;DR

This paper introduces an inverse multi-objective optimization framework using a novel MOPSO algorithm and FE modeling to design microperforated panels that effectively mitigate low-frequency noise while reducing costs.

Contribution

It develops a new inverse multi-objective optimization approach with a specialized MOPSO algorithm for designing cost-effective, high-performance MPPs for noise mitigation.

Findings

Designed MPPs significantly improve low-frequency noise absorption.

The optimization method effectively balances noise reduction and fabrication costs.

Validated FE model confirms the reliability of the design process.

Abstract

Microperforated panels (MPPs) display excellent capacity in noise control applications owing to their high strength, simple design, and efficacy in low-frequency sound absorption. Traditionally, the development of MPPs has relied on a trial-and-error design approach. Although simple optimization-based methods have recently begun to be employed, these designs often overlook practical considerations, such as the increased costs associated with adding more MPP layers, which presents a gap to achieve the practical feasibility of MPP deployment. To address this, the study aims to develop an inverse multi-objective optimization-empowered framework for MPP design to enhance low-frequency noise mitigation while minimizing fabrication costs. Specifically, a finite element (FE) model is established to conduct the acoustic analysis of MPPs, followed by thorough experimental validation. A novel multi-objective particle swarm optimization algorithm (MOPSO) is then developed to cope with mixed-type design variables with interrelations inherent to the MPP architecture. Using the high-fidelity FE model as a cornerstone, the MOPSO guides the inverse optimization analysis to yield multiple non-dominant solutions. These solutions not only avoid the trap of local optima, but also allow for continuous screening to ensure the engineering viability based on empirical judgment. The results clearly demonstrate the effectiveness of the proposed methodology. The MPPs designed in this study show great potential for mitigating indoor noise in buildings, addressing noise issues arising from rapid urbanization and transportation development. Furthermore, the novel optimization strategy proposed in this study holds wide applicability for other sound absorption materials.