**4. Experimental results and discussion**

#### **4.1. Air permeability**

(15) [17]. The measurements were done on five different samples from each material by apply-

Sound absorption coefficients of multilayer nonwovens were measured according to ISO 10534-2 [18]. Nonwoven samples were cut into 100 and 29 mm diameters for the measurement of large and small tubes. Sound absorption coefficients of three samples (two replications from each material) were obtained by using a Brüel and Kjær impedance tube kit

The capillary flow porometer (Porous Materials Inc., USA) has been successfully used to evaluate pore structures of multilayer nonwovens. Determination of porosity of samples according to ISO 15901-1 standard, 5 samples were prepared at 0.03 cm and determined by

In statistical analysis, Design Expert Analysis of Variance (ANOVA) software (Stat-Ease, Inc., USA) was achieved. The effect of independent parameters, basis weight (A) and fiber type (B) on the dependent parameters of air permeability, mean pore diameter, and sound absorption has been examined with the analysis of variance at significance level of p value

**Figure 4.** Impedance tubes for the two microphone transfer function methods: (a) large tube for 0.5–6.4 kHz and (b) small

test area. The reported results are the averages of the

ing 200 Pa pressure through a 20 cm<sup>2</sup>

taking the average of the measurement values [19].

five measurements.

(**Figure 4**).

48 Engineered Fabrics

less than 0.05.

tube for 0.5–1.6 kHz.

Air permeabilities of nonwoven samples are presented in **Figure 5**, respectively, for increasing basis weights of multilayer nonwovens. As seen in **Figure 5**, the air permeabilities of the nonwoven samples with bicomponent fibers are lower than the air permeabilities of the nonwoven samples with homocomponent fibers. For each range of basis weight, BC samples are more resistant to air flow than the HC samples.

Air permeability is expressed as the ratio of air flow between the two surfaces of the fabric. The speed of the air flow passing vertically from a given area is measured by the pressure difference within the measuring area of the fabric. The degree of air permeability is one of the major affecting parameters of thermal and acoustic insulation capabilities of nonwoven fabrics. Higher air permeability results in higher sound absorption [21–23].

Co-PET polymer with low melting temperature in nonwoven samples containing bicomponent fibers melts during the thermal bonding and provides the binding by spreading to the fibers around the web. This attribute limits the cross sectional and connection between fibers, and when considering that it affects the fiber roughness, the decrease in pore diameters is determined by the pore size measurements. When the relationship between air permeability and pore structure is evaluated, it is thought that this will increase air flow resistance and create a decrease in air permeability values. This indicates that bicomponent structures restricted the size of air passages, so that air permeability decreased. At higher basis weights of the fabrics, the increase in the number of fibers creates more spaces and a longer tortuous path through which the air must flow. Thus fabric structure becomes more resistant to air flow resulted with lower air permeabilities.

**Figure 5.** Air permeability of nonwoven samples.

In the statistical data analysis, the effect of independent parameters, basis weight (A) and fiber type (B), on the dependent parameter, air permeability, has been examined with the analysis of variance at significance level of p value less than 0.05. The model summary statistics and ANOVA results for the data obtained in the study are shown in **Table 2**.

As presented in **Table 2**, R-Squared (R2 ) equals 0.9938, and predicted R-Squared (Rpre 2 ) equals 0.9865 for the model. It means that dependent parameters have been affected by independent parameters 99.38%, and this model predicts air permeability successfully at very high proportion of 98.65%. In the ANOVA results of BC and HC samples, both A and B are significant model terms. Contribution to model of significant terms according to F values, it has been determined that A-basis weight is more significant factor with higher F value for air permeability than B-fiber type. It can be specified that fiber type (bicomponent and homocomponent), is less effective parameter than basis weight to control air permeability of multilayer nonwovens statistically. Regression equation for air permeability of BC and HC samples obtained from the model is presented below in Eq. (1) according to codded factors. The high levels of the factors are coded as +1, and the low levels of the factors are coded as −1.

$$\text{Air permeability} = +121.00 - 124.34^{\circ} \text{ A} - 14.93^{\circ} \text{ B} + 97.23^{\circ} \text{ A}^{2} - 40.50^{\circ} \text{ A}^{3} \tag{1}$$

Porosity, thickness, and fiber diameter are the factors that affect tortuosity of the structure [24]. Co-PET polymer with low melting point in the bicomponent nonwoven samples melted earlier and smeared the adjacent fibers during the bonding. The reason may be the variation of intersection of fibers, roughness, and tortuosity resulted with the change of the pore struc-

The statistical analysis of mean pore diameter of BC and HC samples exhibited in **Table 3** indicates the significant effect of fiber type with higher F values. Mean pore diameters have been affected by basis weight and fiber type 98.97%, and the model predicts the actual values of air permeability 97.60%. It can be specified that fiber type (bicomponent and homocomponent)

Model 29.47 4 7.37 216.22 <0.0001 A-Basis weight 1.92 1 1.92 56.46 <0.0001 B-Fiber type 2.91 1 2.91 85.34 <0.0001

Model Std. deviation 0.18 R-Squared 0.9897

C.V.% 1.06 Adjusted R-Squared 0.9851 PRESS 0.71 Predicted R-Squared 0.9760

**square**

**F Significance**

Acoustic Insulation Behavior of Composite Nonwoven http://dx.doi.org/10.5772/intechopen.80463 51

ture as smaller pore diameters for bicomponent nonwovens.

**Source Sum of squares Degree of freedom (df) Mean** 

Residual 0.31 9 0.034

1.28 2

Cor total 29.78 13

**Table 3.** ANOVA for mean pore diameter of samples.

**Figure 6.** Mean pore diameter of nonwoven samples.

Factors within group

#### **4.2. Mean pore diameter**

The porosity of the fabrics is a complex feature characterized by parameters such as pore diameter, pore distribution, pore volume, while the porosity of the fabrics is associated with the total fabric volume area of the empty volume. Fabric porosity directly affects permeability properties, and the shape, layout, and size distribution of the media spaces are important considering the flow from porous structure [22].

In **Figure 6**, it is presented the mean pore diameter of nonwoven samples with the change of basis weight. As seen in **Figure 6**, nonwoven samples with bicomponent fibers had lower mean pore diameters than nonwoven samples with homocomponent fibers.


**Table 2.** ANOVA for air permeability of samples.

**Figure 6.** Mean pore diameter of nonwoven samples.

In the statistical data analysis, the effect of independent parameters, basis weight (A) and fiber type (B), on the dependent parameter, air permeability, has been examined with the analysis of variance at significance level of p value less than 0.05. The model summary statistics and

0.9865 for the model. It means that dependent parameters have been affected by independent parameters 99.38%, and this model predicts air permeability successfully at very high proportion of 98.65%. In the ANOVA results of BC and HC samples, both A and B are significant model terms. Contribution to model of significant terms according to F values, it has been determined that A-basis weight is more significant factor with higher F value for air permeability than B-fiber type. It can be specified that fiber type (bicomponent and homocomponent), is less effective parameter than basis weight to control air permeability of multilayer nonwovens statistically. Regression equation for air permeability of BC and HC samples obtained from the model is presented below in Eq. (1) according to codded factors. The high

levels of the factors are coded as +1, and the low levels of the factors are coded as −1.

Air permeability = +121.00 − 124.34<sup>∗</sup> A − 14.93<sup>∗</sup> B + 97.23<sup>∗</sup> A2 − 40.50<sup>∗</sup> A3 (1)

The porosity of the fabrics is a complex feature characterized by parameters such as pore diameter, pore distribution, pore volume, while the porosity of the fabrics is associated with the total fabric volume area of the empty volume. Fabric porosity directly affects permeability properties, and the shape, layout, and size distribution of the media spaces are important

In **Figure 6**, it is presented the mean pore diameter of nonwoven samples with the change of basis weight. As seen in **Figure 6**, nonwoven samples with bicomponent fibers had lower

**Source Sum of squares Degree of freedom (df) Mean square F Significance** Model 1.748E + 005 4 43703.18 362.97 <0.0001 A-Basis weight 13084.75 1 13084.75 108.67 <0.0001 B-Fiber type 3120.07 1 3120.07 25.91 0.0007

Model Std. deviation 10.97 R-Squared 0.9938

C.V.% 6.68 Adjusted R-Squared 0.9911 PRESS 2380.21 Predicted R-Squared 0.9865

mean pore diameters than nonwoven samples with homocomponent fibers.

) equals 0.9938, and predicted R-Squared (Rpre

2 ) equals

ANOVA results for the data obtained in the study are shown in **Table 2**.

As presented in **Table 2**, R-Squared (R2

50 Engineered Fabrics

**4.2. Mean pore diameter**

Factors within group

considering the flow from porous structure [22].

20580.48 2

Cor total 1.759E + 005 13

**Table 2.** ANOVA for air permeability of samples.

Residual 1083.64 9 120.40

Porosity, thickness, and fiber diameter are the factors that affect tortuosity of the structure [24]. Co-PET polymer with low melting point in the bicomponent nonwoven samples melted earlier and smeared the adjacent fibers during the bonding. The reason may be the variation of intersection of fibers, roughness, and tortuosity resulted with the change of the pore structure as smaller pore diameters for bicomponent nonwovens.

The statistical analysis of mean pore diameter of BC and HC samples exhibited in **Table 3** indicates the significant effect of fiber type with higher F values. Mean pore diameters have been affected by basis weight and fiber type 98.97%, and the model predicts the actual values of air permeability 97.60%. It can be specified that fiber type (bicomponent and homocomponent)


**Table 3.** ANOVA for mean pore diameter of samples.

is more effective parameter than basis weight to control mean pore diameters of multilayer nonwovens statistically.

Regression equation for air permeability of BC and HC samples obtained from the model is presented below in Eq. (2) according to codded factors. The high levels of the factors are coded as +1, and the low levels of the factors are coded as −1.

$$\text{Mean pore diameter} = +17.09 - 1.51^{\circ} \text{A} + 0.46^{\circ} \text{B} + 0.70^{\circ} \text{A}^{2} - 0.65^{\circ} \text{A}^{3} \tag{2}$$

The effectiveness of a material in sound absorption depends mainly on the frequency of the sound wave subjected to the material, basis weight, air permeability, fiber geometry, and fiber arrangement [25–27]. Sound absorption occurs due to the impact of sound waves on material, friction losses while moving in the pores and channels of the structure, and the decrease in sound energy. As a result of increasing basis weight, fiber density, and porosity of random fibers, the sound wave will contact more fibers, and friction losses will increase [23]. As a result, the sound energy will be reduced, and higher sound absorption coefficients will be obtained. The results obtained from this research are evi-

Acoustic Insulation Behavior of Composite Nonwoven http://dx.doi.org/10.5772/intechopen.80463 53

In bicomponent fibers with core/sheath type round cross section, melting Co-PET smeared to adjacent fibers to bind the nonwoven structure. It can be concluded that melting part of bicomponent fibers affects the cross-section area and fiber surface roughness, resulted with the variation of tortuous passages performed as higher sound absorption. As the result of restricted flow of sound waves, the sound absorption coefficients became higher [28, 29].

The statistical analysis of sound absorption of BC and HC samples presented in **Table 4** indicates the significant effect of fiber type with higher F values. Sound absorption has been affected by basis weight and fiber type 98.98%. It can be specified that fiber type (bicomponent and homocomponent) is more effective parameter than basis weight to control sound absorp-

Regression equation for air permeability of BC and HC samples obtained from the model is presented below in Eq. (3) according to codded factors. The high levels of the factors are

A2 B + 0.24<sup>∗</sup> A3 + 0.41<sup>∗</sup> A3 B + 0.23<sup>∗</sup> A4 + 0.25<sup>∗</sup> A4 B − 0.25<sup>∗</sup> A5 − 0.44<sup>∗</sup> A5 B (3)

**Source Sum of squares Degree of freedom (df) Mean square F Significance** Model 0.53 11 0.048 900.08 0.0011 A-Basis weight 0.012 1 0.012 230.51 0.0043 B-Fiber type 0.036 1 0.036 685.34 0.0015

Model Std. deviation 7.282E-003 R-Squared 0.9998

C.V. % 1.18 Adjusted R-Squared 0.9987 PRESS 0.20 Predicted R-Squared 0.6143

Sound absorption = +0.65 + 0.25<sup>∗</sup> A + 0.10<sup>∗</sup> B + 0.01 2<sup>∗</sup> AB − 0.25<sup>∗</sup> A2 − 0.30<sup>∗</sup>

dence of this situation.

Factors within group

tion of multilayer nonwovens statistically.

coded as +1, and the low levels of the factors are coded as −1.

0.005 9

Cor total 0.53 13

**Table 4.** ANOVA for sound absorption of samples.

Residual 1.061E-004 2 5.303E-005

#### **4.3. Sound absorption**

The performance of sound absorbing materials is generally explained by the sound absorption coefficient (α). It is defined as the ratio of acoustic energy that is trapped in the material by the material and ranges between 0 and 1. "α = 0" means 0% sound absorption so the reflection of all the sound waves, and "α = 1" means 100% sound absorption of all the sound waves.

The sound absorption results of nonwoven samples are observed in **Figure 7**. It is certain that as many researchers reported, the increase in basis weight influences the sound absorption positively. So also in this research, the higher sound absorption coefficients were proved for the higher weights. But it should be noted that BC samples have better sound insulation for each range of fabric weight. More effective sound absorption with bicomponent fibers is obvious.

**Figure 7.** Sound absorption coefficients of nonwoven samples.

The effectiveness of a material in sound absorption depends mainly on the frequency of the sound wave subjected to the material, basis weight, air permeability, fiber geometry, and fiber arrangement [25–27]. Sound absorption occurs due to the impact of sound waves on material, friction losses while moving in the pores and channels of the structure, and the decrease in sound energy. As a result of increasing basis weight, fiber density, and porosity of random fibers, the sound wave will contact more fibers, and friction losses will increase [23]. As a result, the sound energy will be reduced, and higher sound absorption coefficients will be obtained. The results obtained from this research are evidence of this situation.

In bicomponent fibers with core/sheath type round cross section, melting Co-PET smeared to adjacent fibers to bind the nonwoven structure. It can be concluded that melting part of bicomponent fibers affects the cross-section area and fiber surface roughness, resulted with the variation of tortuous passages performed as higher sound absorption. As the result of restricted flow of sound waves, the sound absorption coefficients became higher [28, 29].

The statistical analysis of sound absorption of BC and HC samples presented in **Table 4** indicates the significant effect of fiber type with higher F values. Sound absorption has been affected by basis weight and fiber type 98.98%. It can be specified that fiber type (bicomponent and homocomponent) is more effective parameter than basis weight to control sound absorption of multilayer nonwovens statistically.

Regression equation for air permeability of BC and HC samples obtained from the model is presented below in Eq. (3) according to codded factors. The high levels of the factors are coded as +1, and the low levels of the factors are coded as −1.



**Table 4.** ANOVA for sound absorption of samples.

is more effective parameter than basis weight to control mean pore diameters of multilayer

Regression equation for air permeability of BC and HC samples obtained from the model is presented below in Eq. (2) according to codded factors. The high levels of the factors are

Mean pore diameter = +17.09 − 1.51<sup>∗</sup> A + 0.46<sup>∗</sup> B + 0.70<sup>∗</sup> A2 − 0.65<sup>∗</sup> A3 (2)

The performance of sound absorbing materials is generally explained by the sound absorption coefficient (α). It is defined as the ratio of acoustic energy that is trapped in the material by the material and ranges between 0 and 1. "α = 0" means 0% sound absorption so the reflection of all the sound waves, and "α = 1" means 100% sound absorption of all the sound waves.

The sound absorption results of nonwoven samples are observed in **Figure 7**. It is certain that as many researchers reported, the increase in basis weight influences the sound absorption positively. So also in this research, the higher sound absorption coefficients were proved for the higher weights. But it should be noted that BC samples have better sound insulation for each range of fabric weight. More effective sound absorption with bicomponent fibers is obvious.

coded as +1, and the low levels of the factors are coded as −1.

**Figure 7.** Sound absorption coefficients of nonwoven samples.

nonwovens statistically.

52 Engineered Fabrics

**4.3. Sound absorption**


the pore diameters and air permeability values of the samples containing bicomponent fibers decrease, friction of the sound wave by changing direction with the fiber surfaces can be said

Acoustic Insulation Behavior of Composite Nonwoven http://dx.doi.org/10.5772/intechopen.80463 55

When sound absorption and effecting factors are evaluated on nonwovens, the basis weight, thickness, fiber fineness, air flow resistance, pore structure, and tortuosity can be listed. Sound absorption performances of surfaces with high resistance to air flow up to a certain point will also be high. However, according to the studies in the literature, this situation may vary at various levels depending on the conditions of use and the frequency of the sound wave. The air permeability is mainly effective in determining the sound absorption, and the structural parameters that control the air permeability will also affect the sound absorption. The results obtained in this study show that the air permeability values of samples with smaller pore diameters are also lower, supporting the high sound absorption of these samples. In addition, it has been determined that this effect has become more pronounced with the increase of basis weight. As fabric basis weights ranged from 130 to 280 gsm for each sample group, as the increase in the number of fiber per unit area, the higher sound absorption coefficients were obtained. Increasing intersection of fibers in heavier nonwovens creates a tortuous path for

Additionally, all samples had low sound absorption coefficient range between 0.0 and 0.3 up

At the high frequencies, as the wavelengths becomes smaller, the thinner fabrics control the sound absorption efficiently. Therefore, the thinner spunmelt nonwovens compared to

The results show that sound insulation at high frequencies can be improved by using spunmelt multilayer nonwovens. Spunmelt multilayer nonwovens offer opportunities to tailor

This research has been supported by Scientific Research Project Department of Cukurova University. The authors would like to thank also Mogul Nonwoven Company/Gaziantep/

fabrics to desired applications through variations in fiber type and basis weight.

to cause loss of acoustic energy and increase of sound absorption coefficients.

sound wave to flow caused to acoustic energy loss and sound absorption.

needle-punched ones are good sound absorbers at high frequencies.

\* and Osman Babaarslan2

1 Gaziantep University, Technical Sciences Vocational School, Gaziantep, Turkey

2 Çukurova University, Department of Textile Engineering, Adana, Turkey

\*Address all correspondence to: celikel@gantep.edu.tr

to the frequency of 3000 Hz.

**Acknowledgements**

**Author details**

Dilan Canan Çelikel<sup>1</sup>

Turkey for supplying nonwoven samples.

**Table 5.** Correlation between variables and responses.

#### **4.4. Correlations**

The correlations between the independent parameters, basis weight (A) and fiber type (B), and the dependent parameters, air permeability (C), mean pore diameter (D), and sound absorption (E), has been examined and the results for the data obtained in the study are shown in **Table 5**. The statistical results have showed that air permeability, mean pore diameter, and sound absorption have significant correlation. Correlations between each of variables proved that sound absorption has an inverse relation with air permeability and pore sizes.

## **5. Conclusion**

In this research, acoustic insulation behavior of SMS type composite nonwovens has been investigated. The results show that sound absorption has been affected by fiber type of homocomponent or bicomponent, and more effective sound absorption with bicomponent fibers is obvious. Higher sound absorption coefficients were provided with multilayer nonwoven samples containing bicomponent fibers.

The reason for these results may be because the different porosity, tortuosity, and roughness of bicomponent and homocomponent structures. Higher value of tortuosity would therefore indicate longer, more complicated, and sinuous path, thus resulting in greater resistance to sound wave flow. Tortuosity also directly influences propagation of acoustic waves and absorbance efficiency in fibrous porous media. It has also been said that the degree of tortuosity determines the high frequency behavior of sound absorbing porous materials.

Additionally, sound absorbent materials must be porous in order to allow sound waves to enter, spread, and decrease sound energy through friction. However, closed pores in the structure have little effect on the absorption of sound, while open pores directly affect the sound insulation properties of the material as they allow sound waves to penetrate into the material [21, 30].

It can be stated that this effect increases with the contribution of bicomponent fibers in the formation of nonwoven surface with filament laying methods, which constitute the basic character of the process of random fiber orientation and intersection [31–34]. As a result, while the pore diameters and air permeability values of the samples containing bicomponent fibers decrease, friction of the sound wave by changing direction with the fiber surfaces can be said to cause loss of acoustic energy and increase of sound absorption coefficients.

When sound absorption and effecting factors are evaluated on nonwovens, the basis weight, thickness, fiber fineness, air flow resistance, pore structure, and tortuosity can be listed. Sound absorption performances of surfaces with high resistance to air flow up to a certain point will also be high. However, according to the studies in the literature, this situation may vary at various levels depending on the conditions of use and the frequency of the sound wave. The air permeability is mainly effective in determining the sound absorption, and the structural parameters that control the air permeability will also affect the sound absorption. The results obtained in this study show that the air permeability values of samples with smaller pore diameters are also lower, supporting the high sound absorption of these samples. In addition, it has been determined that this effect has become more pronounced with the increase of basis weight. As fabric basis weights ranged from 130 to 280 gsm for each sample group, as the increase in the number of fiber per unit area, the higher sound absorption coefficients were obtained. Increasing intersection of fibers in heavier nonwovens creates a tortuous path for sound wave to flow caused to acoustic energy loss and sound absorption.

Additionally, all samples had low sound absorption coefficient range between 0.0 and 0.3 up to the frequency of 3000 Hz.

At the high frequencies, as the wavelengths becomes smaller, the thinner fabrics control the sound absorption efficiently. Therefore, the thinner spunmelt nonwovens compared to needle-punched ones are good sound absorbers at high frequencies.

The results show that sound insulation at high frequencies can be improved by using spunmelt multilayer nonwovens. Spunmelt multilayer nonwovens offer opportunities to tailor fabrics to desired applications through variations in fiber type and basis weight.
