This content is not included in your SAE MOBILUS subscription, or you are not logged in.

A Hybrid Acoustic Model for Composite Materials Composed of Fibers and High Surface Area Particles

Journal Article
2021-01-1127
ISSN: 2641-9637, e-ISSN: 2641-9645
Published August 31, 2021 by SAE International in United States
A Hybrid Acoustic Model for Composite Materials Composed of Fibers and High Surface Area Particles
Sector:
Citation: Mo, Z., Shi, T., Lee, S., Seo, Y. et al., "A Hybrid Acoustic Model for Composite Materials Composed of Fibers and High Surface Area Particles," SAE Int. J. Adv. & Curr. Prac. in Mobility 4(2):360-367, 2022, https://doi.org/10.4271/2021-01-1127.
Language: English

Abstract:

High surface area particles have drawn attention in the context of noise control due to their good sound absorption performance at low frequencies, which is an advantage compared with more traditional materials. That observation suggests that there is a good potential to use these particles in various scenarios, especially where low frequency noise is the main concern. To facilitate their application, composite materials are formed by dispersing particles within a fiber matrix, thus giving more flexibility in positioning those particles. In this work, a hybrid model that combines a model for limp porous materials and a model of high surface area particles is proposed to describe the acoustic performance of such composites. Two-microphone standing wave tube test results for several types of composites with different thickness, basis weight, and particle concentration are provided. An optimization procedure based on the particle swarm algorithm is introduced to identify the input parameters of the proposed model by minimizing the difference between measured and predicted absorption coefficients. Comparisons between the model predictions made using the optimized parameters and the measurements are shown in this paper, which demonstrates that the proposed model can predict the acoustic performance of the composites with reasonable input parameters.