Development of an acoustic material property database and universal airflow resistivity model

The importance of accurate airflow resistivity predictive models and a subsequent comprehensive database of acoustic material properties for designers cannot be underestimated. With the advances in Finite Element Analysis software, the development of physical prototypes for preliminary testing is becoming obsolete. This is due to the limited resources available and pressure on designers by industry to accomplish tasks in shorter time frames. Therefore, the primary purpose of this research was to develop a comprehensive database of acoustic material properties such as airflow resistivity, bulk density, fibre density and fibre diameter, for designers to draw from, since there is no comprehensive database currently in the literature. Secondly, this research attempts to provide a comprehensive list of available airflow resistivity predictive models, for the designer's convenience. Furthermore, this research attempts to evaluate the accuracy of the available models by benchmarking each model against experimental data, this will allow for the correct implementation of the model. Finally, this research proposes a universal airflow resistivity predictive empirical model, this is necessary since the current available models are limited in their predictive range. Based on this model, it was found that the predicted percentage error of the airflow resistivity had no visible correlation with the bulk density and fibre diameter. Thus, the range (i.e. the bulk density and fibre diameter range) did not influence the percentage error between the measured and predicted airflow resistivity. Interestingly, it was found that the majority of high percentage errors that occurred came from inaccuracies in the data presented in the available literature. Finally, it was determined that further research to improve the body of knowledge is required. (C) 2020 Elsevier Ltd. All rights reserved.

Automated summary

The research aims to provide designers with a comprehensive database of acoustic material properties and a list of airflow resistivity predictive models, evaluate the accuracy of the models, and propose a universal predictive model.