Characterization and Simulation of Acoustic Properties of Sugarcane Bagasse-Based Composite Using Artificial Neural Network Model

Abstract

Environmental sustainability and environmental protection represent essential challenges for the well-being of the community. The use of eco-sustainable materials in architecture is necessary for the transformation of urban centers into modern sustainable cities, to reduce air pollution and protect natural ecosystems, decrease greenhouse gas emissions and improve the energy efficiency of buildings. In this study, sugar cane processing waste was used as an alternative and ecological acoustic material, combining it with natural binders used in construction, such as plaster and clay. To make the composite, the fibers were separated from the bark, then the fibers were assembled with the binder in the frames, and finally the frame with the composite was subjected to a drying process. Specimens of various thicknesses were prepared and the sound absorption coefficient (SAC) at normal incidence was calculated. Subsequently, to compare the acoustic performances of the samples, a simulation model for the prediction of the SAC based on the artificial neural network (ANN) was created. The results suggest the adoption of the simulation model to review the acoustic properties of the material.