Numerical simulation for porous hemp plastic composites sound absorption properties

Abstract

Hemp is an environmentally friendly porous fiber, and has good sound absorption properties, which can be used to reduce noise. In recent years, hemp-based composites have been widely studied, but most of them study the preparation methods of materials, Therefore, this paper studies the topic. Firstly, the material and specimens with different thickness and diameter were prepared, then, the standing wave tube method experiment was carried out, and the values of sound absorption coefficient of the specimens were measured and analyzed, while a novel model using genetic algorithm and artificial neural network is proposed. Secondly, the artificial neural network structure was designed, and the training data, verification data, test data are divided and the data is preprocessed. Thirdly, improved genetic algorithm is proposed to design to determine an optimal solution. Fourthly, the optimal solution was as the initial weight and threshold, and were input into the artificial neural network together with training data and verification data. Levenberg Marquardt algorithm were used to train the network. Finally, input the test data into the trained network to test the model. The results showed that there is only a minor deviation between the model output values and the measured values, the values of sound absorption coefficient of specimens with 10 mm thickness are between 0.9 and 1. It was also found that compared with artificial neural network model without genetic algorithm, the proposed model has the lower root mean squared error (RMSE) value, the larger coefficient of determination (R2) value.