OPTIMIZATION OF THE CALCULATION APPARATUS FOR DESIGNING POROUS SOUND-ABSORBING MATERIALS

Abstract

The main drawback of existing models of sound propagation through sound-absorbing porous materials is the complexity of their practical application. All calculations are presented in an imaginary form, which increases the volume of calculations and complicates the process of automating the design of sound-absorbing materials of the required efficiency. Therefore, it is advisable to convert all calculations into a real form, which will simplify the process of automating the design of soundabsorbing materials and structures. It has been shown that the use of empirical and semi-phenomenological models for preliminary assessment of the sound-absorbing properties of porous materials is difficult due to their dependence on numerous parameters that cannot be measured directly. It is proposed to optimise the calculation apparatus based on the Johnson-Champ-Allard-LaFarge (JCAL) model. It is shown that the JCAL model can be reduced to two non-acoustic parameters – porosity and airflow resistance, which can be determined quite accurately experimentally, taking into account their correlation with the four remaining parameters. The porosity of the material is easily determined by weighing test samples, and the air flow resistance can be measured in a standard impedance tube or on a laboratory setup for determining air flow resistance using air flow and a pressure sensor. Reducing the number of model parameters speeds up the prediction of sound absorption characteristics and makes the model more applicable to optimisation strategies and automated design of protective porous materials. The creation of application software for the automation of sound insulation design with high calculation speed will allow the optimisation of the selection of the required material parameters by trial and error. The proposed changes significantly reduce the computational complexity, increasing the suitability of the calculation apparatus for real-time applications and large-scale modelling.