Prediction of the Mechanical Properties of Carbon Fiber Reinforced Polymer Composites Using Machine Learning

Abstract

Machine learning (ML), which includes deep learning, has been applied to structural design and in understanding the behavior of materials. ML has self-learning capabilities, reduces the computer processing time with large datasets, and can obtain highly accurate results. However, because ML is a data-driven method, the quantity and quality of data significantly affect the accuracy of ML, and therefore properly designed AI algorithms and virtual reality models are necessary. Continued research efforts in this area are thus required. This article presents the latest applications of ML for composite materials.