Towards the Prediction of the Mechanical Properties of a Green Polymer Bioloaded with Alfa Fibers Using a Deep Neural Network Model

The investigation of micromechanical properties of bio composites has emerged as a focus of current scientific inquiry. The use of this type of research is due to the ecological, environmental, and long-term development benefits that these bio composites provide. In addition to their economic benefits in meeting industrial constraints. The matrix used in this intelligent study is green epoxy, which is one of the most commonly used polymers in the current industry due to its low cost, availability, and interesting thermomechanical properties, and which has applications in transportation, infrastructure, packaging, home applications, and the automotive industry, among others. The bio load used is Alpfa fibers, which have been largely overlooked by researchers in the field of bio composites. Bio loading with Alfa fibers enhance the mechanical properties of the green epoxy matrix, according to the findings. When compared to the experimental results, the neural network model predicted the Young modulus of the bio composite with high accuracy. The best results obtained in the test phase demonstrate that NNs are capable of generalizing the complicated link between the input and output set of data learned during the training phase, allowing us to create an efficient predictive model for elasiycity of biocomposite.