부산대학교 도서관

This paper proposes an algorithm to perform the inverse design of a low-frequency acoustic absorber using a deep convolutional autoencoder network. A hybrid sound-absorber configuration based on Helmholtz resonators with inserted curvy neck and microperforated panel is suggested and its geometrical properties are inversely forecasted from the targeted signal. A mathematical model is put forwarded to evaluate the absorption characteristics of the introduced geometry by employing the effective medium theory and the electro-acoustic analogy. The large dataset required to train, validate and test the deep neural network is extracted through this analytical procedure. Initially, the proposed inverse technique is successfully applied on a standard Helmholtz resonator based absorber setup with great accuracy. This prediction approach is further extended to suit the inverse design of a hybrid sound absorber with complex geometrical attributes. The encoder maps the input acoustic absorption spectrum to geometrical features of the absorber, and the subsequent decoder recreates the absorption characteristics using convolutional layers. Once the training and testing of the neural network are over, the deep autoencoder inversely predicts the geometrical parameters. In comparison with earlier inverse models which employed deep neural networks, the accuracy of the current scheme is very high and no pre-design information on absorber geometry is required as well. Since the relevant learnable parameters involved are very low, the computational load is also very less for this autoencoder based method. Later, using the new inverse scheme, four representative absorber designs with specific acoustic functionality are deduced. Most importantly, these four compact absorber models produce quasi-perfect absorption in the frequency bands 200–315 Hz, 255–400 Hz, 300–530 Hz, and 350–650 Hz. Notably, the developed absorber versions have great potential in noise reduction applications owing to their deep sub-wavelength thickness (λ/23 at 200 Hz) and wide absorption spectra.