Seven-Parameter Linear Viscoelastic Model Applied to Acoustical Damping Materials

E Gourdon,K Bilodeau,C Sauzéat,H Di Benedetto

doi:10.1115/1.4030719

Abstract

In this paper, linear viscoelastic rheological properties of acoustical damping materials are predicted. A rheological model, based on a mechanical element approach, is presented. It consists of a combination of two springs, two parabolic elements, and one dashpot (2S2P1D). This model is applied to different acoustical damping materials. Its specificity comes from the fact that elements might be linked to structural and physical features. Parameters might be experimentally determined by tests. Application of the 2S2P1D linear viscoelastic model can adequately predict the behavior of acoustical damping materials with good accuracy. If the material verifies the time–temperature superposition principle (TTSP), the proposed model can predict the behavior on a wide frequency range, even with a small number of available data.

Highlights

Nowadays, acoustical foams [1,2,3,4] and acoustical composite materials [5] are widely used for sound and vibration damping in building or automotive applications
The aim of this paper is to show that the 2S2P1D linear viscoelastic model can be applied to acoustical damping materials with success
Before describing the proposed 2S2P1D linear viscoelastic model, we present other viscoelastic models generally used in acoustical fields

Summary

Introduction

Acoustical foams [1,2,3,4] and acoustical composite materials [5] are widely used for sound and vibration damping in building or automotive applications. Among the existing models for simulating linear viscoelastic behavior of acoustical damping materials, the four-parameter fractional Zener model has been found to be efficient to predict frequency variations with symmetrical loss factor peak. From the results on acoustical damping materials, we will show that this comprehensive model translates correctly the linear viscoelastic behavior in the small strain domain for any range of frequencies and temperatures. If limit values are known by experimental tests or by identification from asymptotic values and from the variation of the complex modulus (it is possible to read off the model parameters directly from the experimental data because the frequency curves are smooth as illustrated in Fig. 4), they constitute the initial values of the parameters to be optimized by the algorithm. We have verified that taking different “acceptable” initial values gives the same solution to be sure of the local convergence

Modeling of Acoustical Damping Materials

Findings

Conclusions