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Nonwoven fabrics are widely used for thermal insulation and sound absorption purpose in construction and automobile fields. It is essential to investigate their thermal conductivity and sound absorption coefficient. Five cross-laid nonwoven fabrics are measured on the Alambeta device and Brüel & Kjær impedance tube. Bogaty and Bhattacharyya models are selected to predict the thermal conductivity, and Voronina and Miki models are used to predict the sound absorption coefficient. The predicted thermal conductivity shows a significant difference compared with the measured values. It is concluded that Bogaty and Bhattacharyya models are not suitable for high porous nonwoven fabric. In addition, the results of Voronina and Miki models for sound absorption prediction are acceptable, but Voronina model shows lower mean prediction error compared with Miki model. The results indicate that Voronina model can be used to predict the sound absorption of cross-laid nonwoven fabric.

Nonwoven fabrics are widely used for thermal insulation and sound absorption purpose in construction and automobile fields. It is essential to investigate their thermal conductivity and sound absorption coefficient. Five cross-laid nonwoven fabrics are measured on the Alambeta device and Brüel & Kjær impedance tube. Bogaty and Bhattacharyya models are selected to predict the thermal conductivity, and Voronina and Miki models are used to predict the sound absorption coefficient. The predicted thermal conductivity shows a significant difference compared with the measured values. It is concluded that Bogaty and Bhattacharyya models are not suitable for high porous nonwoven fabric. In addition, the results of Voronina and Miki models for sound absorption prediction are acceptable, but Voronina model shows lower mean prediction error compared with Miki model. The results indicate that Voronina model can be used to predict the sound absorption of cross-laid nonwoven fabric. [ABSTRACT FROM AUTHOR]

This study presents an investigation of the acoustical properties of multi-component polyester nonwovens with experimental and numerical methods. Fifteen types of nonwoven samples made with staple, hollow and bi-component polyester fibers were chosen to carry out this study. The AFD300 AcoustiFlow device was employed to measure airflow resistivity. Several models were grouped in theoretical and empirical model categories and used to predict the airflow resistivity. A simple empirical model based on fiber diameter and fabric bulk density was obtained through the power-fitting method. The difference between measured and predicted airflow resistivity was analyzed. The surface impedance and sound absorption coefficient were determined by using a 45 mm Materiacustica impedance tube. Some widely used impedance models were used to predict the acoustical properties. A comparison between measured and predicted values was carried out to determine the most accurate model for multi-component polyester nonwovens. The results show that one of the Tarnow model provides the closest prediction to the measured value, with an error of 12%. The proposed power-fitted empirical model exhibits a very small error of 6.8%. It is shown that the Delany–Bazley and Miki models can accurately predict surface impedance of multi-component polyester nonwovens, but the Komatsu model is less accurate, especially at the low-frequency range. The results indicate that the Miki model is the most accurate method to predict the sound absorption coefficient, with a mean error of 8.39%. [ABSTRACT FROM AUTHOR]

Polyester nonwoven fibrous material is widely used in construction and automobile industries for thermal insulation purposes. It is worthy and meaningful to understand the effect of structural parameters on the thermal property. Fiber orientation, as one of the most vital parameters, has a significant effect on thermal property. However, there has been little quantitative analysis focusing on this aspect. This paper theoretically and experimentally analyzes the thermal conductivity of samples with varying fiber orientation. Existing models were selected to predict the thermal conductivity of polyester nonwoven samples. Two different apparatus were applied to carry out the experimental measurements. The relative differences between the predicted and measured results were compared. One commonly used model was modified for accurate prediction. It was shown that some existing models under- or overestimate the thermal conductivity compared to the measured values. The results indicate that the modified model can accurately predict the thermal conductivity of polyester nonwoven materials within a 0.2% relative difference. [ABSTRACT FROM AUTHOR]

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 porosity, 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 multi-component fibrous media with 8–10% accuracy. [ABSTRACT FROM AUTHOR]