Sound absorption of porous materials – Accuracy of prediction methods

Oliva, David; Hongisto, Valtteri

doi:10.1016/j.apacoust.2013.06.004

Cited by 94 publications

(54 citation statements)

References 9 publications

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“…The average error for all data was 4.85%. These error values are common for this type of empirical method, and the results are in agreement with the observations made recently by authors using empirical prediction methods to study typical mineral wools (Oliva and Hongisto 2013). Therefore, the calculated regression coefficients can be applied with sufficient confidence in the model to predict the acoustic behavior of this cellulose material.…”

Section: Resultssupporting

confidence: 75%

“…Although at first sight the sound absorption values of the cellulose material appear similar to those obtained for mineral wools of the same thickness, the values of the regression coefficients in the model are very different for both materials, as shown in Table 1. To quantitatively describe how much the empirical model either overestimated or underestimated the measured sound absorption coefficients, the relative prediction error was calculated using the following equation (Oliva and Hongisto 2013),…”

Section: Resultsmentioning

confidence: 99%

“…Some authors have determined the regression coefficients by directly measuring the characteristic wave impedance and propagation constants and subsequently applying curve-fitting (Delany and Bazley 1970;Dunn and Davern 1986;Oliva and Hongisto 2013). Because measuring these constants can be a difficult and lengthy process, an alternative may include determining the regression coefficients, Ci, from the measured data for the normal-incidence sound absorption coefficient in the frequency domain for a known airflow resistivity of the material sample.…”

Section: Numerical Modelmentioning

confidence: 99%

“…In fact, the European standard on building acoustics (EN 12354 2003) recommends using the regression coefficients of Delany and Bazley (1970) for the prediction of the sound absorption of materials composed of fibers and the results of Dunn and Davern (1986) for foam materials. Oliva and Hongisto (2013) presented a comprehensive study on the accuracy of several empirical approaches for predicting the impedance of mineral wool configurations. However, there is no information about the corresponding regression coefficients for cellulose in the technical literature.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Sound Absorption Properties of Unbleached Cellulose Loose-Fill Insulation Material

Arenas¹,

Rebolledo²,

Tormos³

et al. 2014

BioResources

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Recyclable cellulose loose-fill insulation has been commonly used in heavy timber construction for treating attic areas, under floors, and wall cavities. Through the kraft process, the unbleached cellulose adopts a texture characterized by small crumbs, forming a porous medium. In this work, different samples of a single layer of loose-fill cellulose insulation with different thicknesses were tested to measure their sound absorption properties, the airflow resistivity, and porosity for both dry and moist samples. The regression coefficients for an empirical model were calculated using a numerical optimization method. It is concluded that the model predicts the acoustical performance of this material well and that the sound absorption properties of the material are similar to those of mineral fiber-based materials.

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Section: Resultssupporting

confidence: 75%

Section: Resultsmentioning

confidence: 99%

Section: Numerical Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Sound Absorption Properties of Unbleached Cellulose Loose-Fill Insulation Material

Arenas¹,

Rebolledo²,

Tormos³

et al. 2014

BioResources

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show abstract

“…23 When simulating a complex system, like the one used in this study, there are a lot of other influences on acoustic attenuation, such as impedance of the wall, termination of the pipe, etc. Therefore, in this study, anechoic termination was modeled using the sound absorption of porous material, 24 obtained with the Delany-Bazley model. Pipe walls were modeled with impedance boundary condition.…”

Section: Numerical Simulationsmentioning

confidence: 99%

Adaptive muffler based on controlled flow valves

Šteblaj

Čudina

Lipar

et al. 2015

The Journal of the Acoustical Society of America

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An adaptive muffler with a flexible internal structure is considered. Flexibility is achieved using controlled flow valves. The proposed adaptive muffler is able to adapt to changes in engine operating conditions. It consists of a Helmholtz resonator, expansion chamber, and quarter wavelength resonator. Different combinations of the control valves' states at different operating conditions define the main working principle. To control the valve's position, an active noise control approach was used. With the proposed muffler, the transmission loss can be increased by more than 10 dB in the selected frequency range.

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Acoustic Metamaterial Composite Structures Based on Multistage Fano Resonance for Noise Attenuation

Zhang,

Geng,

Zhao

et al. 2024

Annalen der Physik

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An acoustic metamaterial composite structure (AMCS) for Noise attenuation is proposed based on the principle of multilevel Fano resonance. The AMCS is composed of a type I labyrinthine metamaterial in the outer ring, a six‐channel spiral metamaterial in the middle ring, a type II labyrinthine metamaterial in the inner ring, and a porous acoustic‐absorbing metamaterial in the inner inlay. The simulation results show that the average sound attenuation reaches 17 dB in the range of 0–5000 Hz due to the multilevel Fano resonance effect during the sound wave propagation process. Meanwhile, the sound field distribution law and the flow diagram also verify that the multilevel Fano resonance mechanism is the key factor causing broadband sound absorption. Then, the AMCS is fabricated by 3D printing, and the simulation results are verified by the acoustic experiment for AMCS cell. Additionally, to further enhance the overall sound attenuation in the railroad noise field, a simulation model of the combined train‐track‐AMCS sound barrier coupling is developed, and it is found that the AMCS type sound barrier can effectively block the propagation of wheel‐rail noise from different angles, and it possesses a noise reduction of 20 dB in all frequency bands.

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Sound absorption of porous materials – Accuracy of prediction methods

Cited by 94 publications

References 9 publications

Sound Absorption Properties of Unbleached Cellulose Loose-Fill Insulation Material

Sound Absorption Properties of Unbleached Cellulose Loose-Fill Insulation Material

Adaptive muffler based on controlled flow valves

Acoustic Metamaterial Composite Structures Based on Multistage Fano Resonance for Noise Attenuation

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