A semi-phenomenological model to predict the acoustic behavior of fully and partially reticulated polyurethane foams

Doutres, Olivier; Atalla, Noureddine; Dong, Kevin

doi:10.1063/1.4789595

Cited by 64 publications

(48 citation statements)

References 25 publications

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“…A slight but monotonic decrease in measured tortuosity with decreasing permeability accounted for most of the standard deviation as opposed to random scatter. For comparison, analogous data from Álvarez-Arenas et al (2006), Kino et al (2012), and references in Melon and Castagnede (1995) and Doutres and Atalla (2012) note that reticulated foam commonly has a narrow range of tortuosity from 1.03 to 1.06. Tortuosity of the FXI-reticulated foam is not independently measured but shares other specifications with these other sources and likely has tortuosity in the same range.…”

Section: Results For the Em Methodsmentioning

confidence: 99%

A low-cost acoustic permeameter

Drake

Selker

Higgins

2017

Geosci. Instrum. Method. Data Syst.

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Abstract. Intrinsic permeability is an important parameter that regulates air exchange through porous media such as snow. Standard methods of measuring snow permeability are inconvenient to perform outdoors, are fraught with sampling errors, and require specialized equipment, while bringing intact samples back to the laboratory is also challenging. To address these issues, we designed, built, and tested a low-cost acoustic permeameter that allows computation of volumeaveraged intrinsic permeability for a homogenous medium. In this paper, we validate acoustically derived permeability of homogenous, reticulated foam samples by comparison with results derived using a standard flow-through permeameter. Acoustic permeameter elements were designed for use in snow, but the measurement methods are not snow-specific. The electronic components -consisting of a signal generator, amplifier, speaker, microphone, and oscilloscope -are inexpensive and easily obtainable. The system is suitable for outdoor use when it is not precipitating, but the electrical components require protection from the elements in inclement weather. The permeameter can be operated with a microphone either internally mounted or buried a known depth in the medium. The calibration method depends on choice of microphone positioning. For an externally located microphone, calibration was based on a low-frequency approximation applied at 500 Hz that provided an estimate of both intrinsic permeability and tortuosity. The low-frequency approximation that we used is valid up to 2 kHz, but we chose 500 Hz because data reproducibility was maximized at this frequency. For an internally mounted microphone, calibration was based on attenuation at 50 Hz and returned only intrinsic permeability. We found that 50 Hz corresponded to a wavelength that minimized resonance frequencies in the acoustic tube and was also within the response limitations of the microphone. We used reticulated foam of known permeability (ranging from 2 × 10 −7 to 3 × 10 −9 m 2 ) and estimated tortuosity of 1.05 to validate both methods. For the externally mounted microphone the mean normalized standard deviation was 6 % for permeability and 2 % for tortuosity. The mean relative error from known measurements was 17 % for permeability and 2 % for tortuosity. For the internally mounted microphone the mean normalized standard deviation for permeability was 10 % and the relative error was also 10 %. Permeability determination for an externally mounted microphone is less sensitive to environmental noise than is the internally mounted microphone and is therefore the recommended method. The approximation using the internally mounted microphone was developed as an alternative for circumstances in which placing the microphone in the medium was not feasible. Environmental noise degrades precision of both methods and is recognizable as increased scatter for replicate data points.

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Section: Results For the Em Methodsmentioning

confidence: 99%

A low-cost acoustic permeameter

Drake

Selker

Higgins

2017

Geosci. Instrum. Method. Data Syst.

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“…The macroscopic non-acoustical parameters involved in this model (i.e., static airflow resistivity V, tortuosity D∞, viscous /, and thermal /′ characteristic lengths) were estimated by the semi-phenomenological model of Dourtes et al [17] where the foam cell is considered as a tetrakaidecahedron made of 14-sided polyhedron, with six squares faces and eight hexagonal faces (Fig. 1).…”

Section: Acoustic Properties Of Pu Foammentioning

confidence: 99%

Prediction of acoustic foam properties by numerical simulation of polyurethane foaming process

Abdessalam

Abbès

et al. 2016

MATEC Web Conf.

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Abstract. This work aims to model and to simulate the polyurethane foaming process. Models taking into account the two main chemical reactions of the formation of polyurethane, the exothermic effect of these reactions as well as the thermo-rheo-kinetic coupling characterizing this process are proposed and implemented in the software NOGRIDpoints based on a meshless method (Finite Pointset Method). A prediction of some acoustic foam characteristics is also proposed based on the results of the numerical simulation of the foaming process and semi-phenomenological models.

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“…In what follows, the sensitivity analysis is applied to two semi-empirical models recently developed by the authors 7,8 to link the main microstructure properties of fully and partially reticulated polyurethane (PU) foams to the macroscopic non-acoustic parameters involved in the JCA model. In both models, the PUC shape is an isotropic tetrakaidecahedron having struts of triangular concave cross-section shape.…”

Section: Introductionmentioning

confidence: 99%

“…4 : pages 58, 68, 81 and 104], (ii) empirical 6 and semi-empirical 7,8 , and (iii) numerical [9][10][11] .…”

Section: Introductionmentioning

confidence: 99%

“…In the first model 7 , called the 3-parameter model, the PUC is characterized by the strut length l, the strut thickness t and the reticulation rate R w (i.e., open pore content). In the second model 8 , called the 2-parameter model, the PUC is characterized by the cell size C s and reticulation rate R w assuming that the geometric ratio between strut length l and strut thickness t is known. It is a simplification of the 3-parameter model as the cell size is easier to characterize compared to strut's dimensions and it is also a parameter commonly used by chemists.…”

Section: Introductionmentioning

confidence: 99%

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Impact of the irregular microgeometry of polyurethane foam on the macroscopic acoustic behavior predicted by a unit-cell model

Doutres

Ouisse

Atalla

et al. 2014

The Journal of the Acoustical Society of America

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This paper deals with the prediction of the macroscopic sound absorption behavior of highly porous polyurethane foams using two unit-cell microstructure-based models recently developed by the authors [J. Appl. Phys. 110, 064901 (2011) and J. Appl. Phys. 113, 054901 (2013)]. In these models, the porous material is idealized as a packing of a tetrakaidecahedra unit-cell representative of the disordered network that constitutes the porous frame. The non-acoustic parameters involved in the classical Johnson-Champoux-Allard model (i.e., porosity, airflow resistivity, tortuosity...) are derived from characteristic properties of the unit-cell and semi-empirical relationships. A global sensitivity analysis is performed on these two models in order to investigate how the variability associated with the measured unit-cell characteristics affects the models outputs. This allows identification of the possible limitations of a unit-cell micro-macro approach due to microstructure irregularity. The sensitivity analysis mainly shows that for moderately and highly reticulated polyurethane foams, the strut length parameter is the key parameter since it greatly impacts three important non-acoustic parameters and causes large uncertainty on the sound absorption coefficient even if its measurement variability is moderate. For foams with a slight inhomogeneity and anisotropy, a micro-macro model associated to cell size measurements should be preferred.

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A semi-phenomenological model to predict the acoustic behavior of fully and partially reticulated polyurethane foams

Cited by 64 publications

References 25 publications

A low-cost acoustic permeameter

A low-cost acoustic permeameter

Prediction of acoustic foam properties by numerical simulation of polyurethane foaming process

Impact of the irregular microgeometry of polyurethane foam on the macroscopic acoustic behavior predicted by a unit-cell model

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