A Comparison between Numerical Simulation Models for the Prediction of Acoustic Behavior of Giant Reeds Shredded

Abstract

Giant reeds represent a natural fiber widely available in some areas of the world. Its use can be particularly useful as the uncontrolled growth of giant reeds can be a problem because large areas are invaded by them and the crops are damaged. In this study, two models of numerical simulation of the acoustic behavior of giant reeds were put in comparison: the Hamet model and a model based on artificial neural networks. First, the characteristics of the reeds were examined and the procedures for the preparation of the samples to be analyzed were described. Then air flow resistance, porosity and sound absorption coefficient were measured and analyzed in detail. Finally, the results of the numerical modeling of the acoustic coefficient were compared. The neural network-based model showed high Pearson correlation coefficient value, indicating a large number of correct predictions.

Green Sound-Absorbing Composite Materials of Various Structure and Profiling

“…However, profiling a concave in the plate and directing it with its front face to the sound wave causes an increase in sound absorption, Figure 11. Taking into account the published results of previous studies [21], which indicated the validity of the use of convexity on the back of the composite plate, which was confirmed in Figure 12, the absorption of the plate with concavity was measured comparatively. The results showed that convexity on the plate is more advantageous than concavity, Figures 11 and 12.…”

“…The microscopic structure and surface morphology of natural fibers such as flax, bamboo, kenaf, kapok, coir, cotton, broom, giant reeds, cane, coconut, hemp, etc. are conducive to sound absorption [18][19][20][21][22]. Natural fibers, due to their unique hollow and multi scale structures, show better sound absorption compared to high-modulus fibers such as glass or carbon, especially at frequencies above 1000 Hz.…”

Numerical Simulation for the Sound Absorption Properties of Ceramic Resonators

“…This work reports the results of experimental measurements of the sound absorption coefficient of ceramic materials using the principle of acoustic resonators. Subsequently, the values obtained from the measurements were used to train a simulation model of the acoustic behavior of the analyzed material based on artificial neural networks [45][46][47][48][49]. The normal incidence absorption coefficient was measured with the Kundt tube, and as expected, with increasing sample thickness, the peak of the bell curve shifts to lower frequencies.…”

Machine Learning-Based Algorithms to Knowledge Extraction from Time Series Data: A Review

“…In the images, the low-level features are, for example, the edges or the blobs that are reworked to form high-level features, which, once passed to the last layers of the network, will be able to create, for example, the outlines of houses, dogs, cats, or whatever was present in the original image [151,152]. CNNs process maps of traits where each element corresponds to pixels in the original image.…”