Prediction of The Behavior of Bio-Loaded Flexible PVC by Chicken Feathers with Artificial Neural Networks

Abstract

The infinite needs of humanity in several fields give birth to several innovations, in materials sciences, these needs are summed up in the creation of new composite materials. Obtaining a composite material from recycled material and a bio-load first of all makes it possible to recover the recycled material and to have new composite material. PVC is one of the most used plastics in recent years, the addition, after recycling, of a bio-load in the form of chicken feathers which are just lost in nature or incinerated, allows the birth of new composite material. In this article, we use neural networks which appear to be among the essential methods to solve and model complex systems, and in particular when it comes to non-linear problems. This method will be used in comparison with the finite element method to find the most adequate method which makes it possible to better model the behaviors of PVC bio-loaded by chicken feathers, and then predict the behaviors with different percentages of the bio-load. We took the results of the experiments carried out, with those of the study of finite elements, and with the results obtained by the neural networks which will be presented in this article, to find the model which makes it possible to better present and predict the behavior of the recycled PVC bio-loaded with an adequate percentage which improves the mechanical characteristics of this type of composite material. The error between the experimental results and those obtained by the neural networks is very small compared to the differences between the two experimental results and those obtained by the finite elements. Which proves that the neural network model is an important computer tool for modeling and predicting the results of mechanical experiments