Optimizing Microperforated Panel Sound Absorbers Using Response Surface Methodology: Measurement, Modeling, and Performance Evaluation



Hashemi Z¹ ; Sheikh Mozafari MJ² ; Putra A³ ; Sadeghian M⁴ ; Asadi N⁵ ; Ahmadi S⁶ ; Alidostie M⁷
Source: Journal of Health and Safety at Work Published:2024

Abstract

Introduction: Microperforated panels (MPPs), often considered as potential replacements for fiber absorbers, have a significant limitation in their absorption bandwidth, particularly around the natural frequency. This study aims to address this challenge by focusing on the optimization and modeling of sound absorption in a manufactured MPP. Material and Methods: The study employed Response Surface Methodology (RSM) with a Central Composite Design (CCD) approach using Design Expert software to determine the average normal absorption coefficient within the frequency range of 125 to 2500 Hz. Numerical simulations using the Finite Element Method (FEM) were conducted to validate the RSM findings. An MPP absorber was then designed, manufactured, and evaluated for its normal absorption coefficient using an impedance tube. Additionally, a theoretical Equivalent Circuit Model (ECM) was utilized to predict the normal absorption coefficient for the manufactured MPP. Results: The optimization process revealed that setting the hole diameter to 0.3 mm, the percentage of perforation to 2.5%, and the air cavity depth behind the panel to 25 mm resulted in maximum absorption within the specified frequency range. Under these optimized conditions, the average absorption coefficient closely aligned with the predictions generated by RSM across numerical, theoretical, and laboratory assessments, demonstrating a 13.8% improvement compared to non-optimized MPPs. Conclusion: This study demonstrates the effectiveness of using RSM to optimize the parameters affecting MPP performance. The substantial correlation between the FEM numerical model, ECM theory model, and impedance tube results positions these models as both cost-effective and reliable alternatives to conventional laboratory methods. The consistency of these models with the experimental outcomes validates their potential for practical applications. © 2024 The Authors.