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VOL. 12, ISSUE 10 (2025)
Optimization of low frequency sound absorption coefficient in micro-perforated panels backed with Kenaf fibre using Response Surface Methodology and Multivariate Regression
Authors
Lim Eng Aik
Abstract
The acoustic performance of micro-perforated panels backed with Kenaf
fibre is highly dependent on the low-frequency sound absorption coefficient,
which is influenced by complex interactions among material and structural
parameters. We propose a systematic approach to optimize this coefficient by
integrating Response Surface Methodology (RSM) and Multivariate Regression
Model (MRM). The RSM captures nonlinear relationships and interactions between
input variables, including linear, quadratic, and cross-term effects, while the
MRM validates the model and identifies statistically significant factors. This
dual-method framework enables a comprehensive analysis of how coefficients
affect sound absorption, thereby facilitating the identification of optimal
design parameters. The study addresses a critical gap in acoustic material
optimization by providing a data-driven methodology that balances computational
efficiency with empirical accuracy. Experimental validation demonstrates the
robustness of the proposed approach, revealing key insights into the interplay
between panel properties and acoustic performance. The results highlight the
potential of Kenaf fibre as a sustainable alternative in noise control
applications, offering practical guidelines for industrial implementation.
Moreover, the methodology is adaptable to other composite materials, broadening
its applicability in acoustic engineering. By bridging theoretical modeling and
practical optimization, this work contributes to advancing the design of
high-performance sound-absorbing materials.
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Pages:199-206
How to cite this article:
Lim Eng Aik "Optimization of low frequency sound absorption coefficient in micro-perforated panels backed with Kenaf fibre using Response Surface Methodology and Multivariate Regression". International Journal of Multidisciplinary Research and Development, Vol 12, Issue 10, 2025, Pages 199-206
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