Influence of Porosity, Fiber Radius and Fiber Orientation on the Transport and Acoustic Properties of Random Fiber Structures

Luu, Hoang Tuan; Perrot, Camille; Panneton, Raymond

doi:10.3813/aaa.919134

Cited by 35 publications

(25 citation statements)

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“…A recent approach has been to treat a polydisperse fibrous media as if it was equivalent to a monodisperse fibrous media, i.e. by means of an average diameter of the corresponding distribution [24]. Here, the effective fiber diameter is derived from optical granulomorphometry and is a weighted fiber volume diameter accounting for the relative length and diameter of each fiber.…”

Section: Resultsmentioning

confidence: 99%

“…It is typically hampered, however, by either the need to simplify geometry [16,18] or physics [15,22]. In recent years, however, another approach to the numerical study of diffusion and fluid flow through fibrous media has gained some popularity [17,23,24]. The idea is to numerically solve the asymptotic behaviors of the linearized Navier-Stokes and heat equations in a realistic microscopically disordered geometry, and then study how volume-averaged properties of the diffusion process and the fluid flow depend on the details of the microstructures.…”

Section: Introductionmentioning

confidence: 99%

“…In practice, the selection of the aforementioned average radius yields satisfactory results whenever the wave propagates perpendicularly to the plane to which all fibers belong. This work follows a series of recent contributions by some of the authors [17,23,24], focusing on the determination of the acoustic properties of random fibrous materials from their microstructures. In these papers, numerical simulations of fluid flow through fibrous media were fed with microstructural descriptors of increased complexity, inferred from experiments.…”

Section: Introductionmentioning

confidence: 99%

“…This first approach specifically accounts for the porosity of the material, as well as for fiber diameters and orientations, but does not involve a description of the fiber length. [24] built on the model developed in (1) and focused on numerically characterizing the sensitivity of the transport properties with respect to the microstructural parameters under consideration (namely, the porosity and fiber diameter and orientation).…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Multiscale prediction of acoustic properties for glass wools: Computational study and experimental validation

Perrot

Guilleminot

et al. 2018

The Journal of the Acoustical Society of America

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This work is concerned with the multiscale prediction of the transport and sound absorption properties associated with industrial glass wool samples. In the first step, an experimental characterization is performed on various products using optical granulometry and porosity measurements. A morphological analysis, based on scanning electron imaging, is further conducted to identify the probability density functions associated with the fiber angular orientation. The key morphological characterization parameters of the microstructure, which serve as input parameters of the model, include the porosity, the weighted volume diameter accounting for both lengths and diameters of the analyzed fibers (and therefore the specific surface area of the random fibrous material), and the preferred out-of-plane fiber orientation generated by the manufacturing process. A computational framework is subsequently proposed and allows for the reconstruction of an equivalent fibrous network. A fully stochastic microstructural model, parameterized by the probability laws inferred from the database, is also proposed herein. Multiscale simulations are carried out to estimate transport properties and sound absorption. With no adjustable parameter, the results accounting for ten different samples obtained with various processing parameters are finally compared with the experimental data and used to assess the relevance of the reconstruction procedures and the multiscale computations.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Multiscale prediction of acoustic properties for glass wools: Computational study and experimental validation

Perrot

Guilleminot

et al. 2018

The Journal of the Acoustical Society of America

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“…Recently, multi-component polyester materials have started to become more popular replacing single component polyester materials. However, there is limited amount of data on the acoustical and related non-acoustical properties of multi-component polyester materials [3]. Therefore, the major objective of this study is to measure the airflow resistivity for a representative range of fibrous media and use data to understand better the effect of fiber diameter distribution on the accuracy of model predictions.…”

Section: Introductionmentioning

confidence: 99%

A study of some airflow resistivity models for multi-component polyester fiber assembly

et al. 2018

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The airflow resistivity is a key parameter to predict accurately the acoustical properties of fibrous media. There is a large number of theoretical and empirical models which can be used to predict the airflow resistivity of this type of porous media. However, there is a lack of experimental data on the accuracy of these models in the case of multi-component fibrous media. This paper presents a detailed analysis of the accuracy of several existing models to predict airflow resistivity which make use of the bulk density and mean fibre diameter information. Three types of polyester (PET) materials made using regular PET, hollow PET and bi-component PET with a range of densities are chosen for this study. It is shown that some existing models largely under-or overestimate the airflow resistivity when compared with the measured values. A novel feature of this work is that it studies the relative performance of airflow resistivity prediction models that are based on the capillary channel theory and drag force theory. These two groups of models are then compared to some purely empirical models. It is found that the prediction error by some models is unacceptably high (e.g. >20-30%). The results suggest that there are existing models which can predict the airflow resistivity of multicomponent fibrous media with 8-10% accuracy.

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On Experimental Evaluation of Tortuosity for Cellulose-Based Highly Porous Composites Used Within Noise Insulation Applications

Seciureanu,

Guiman,

Nastac

et al. 2024

Acoustics and Vibration of Mechanical Structures—AVMS-2023

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Influence of Porosity, Fiber Radius and Fiber Orientation on the Transport and Acoustic Properties of Random Fiber Structures

Cited by 35 publications

References 0 publications

Multiscale prediction of acoustic properties for glass wools: Computational study and experimental validation

Multiscale prediction of acoustic properties for glass wools: Computational study and experimental validation

A study of some airflow resistivity models for multi-component polyester fiber assembly

On Experimental Evaluation of Tortuosity for Cellulose-Based Highly Porous Composites Used Within Noise Insulation Applications

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