Development of an empirical model for the prediction of the noise reduction coefficient for thin and low-density fibrous materials

This paper presents the development of an empirical noise reduction coefficient model for the prediction of low-density, less than 50 kg/m3, thin, less than 20 mm thick, fibrous materials using multiple linear regression. The purpose of this empirical model is to assist design engineers, working with thin and low-density materials, efficiently and effectively select the most appropriate material for the design. Therefore, several models were developed using software such as Statistical Analysis System. Thereafter, the models were compared using an internal and external data set. A selection metric was developed to assist in the objective selection of the best model. It was found that the log model performed the best overall and thus was selected as the model of choice.