Machine Learning Applied to Composite Materials

The book "Machine Learning Applied to Composite Materials" offers a comprehensive introduction to the use of Machine Learning (ML) for developing predictive models in the design of composite materials. It demonstrates how ML can learn from existing experimental data obtained from a limited number of experiments. These models are capable of capturing complex, nonlinear, and multidimensional functional relationships without requiring prior assumptions about their nature. The book addresses various aspects, including the design of composite materials based on the properties of matrix materials and reinforcements, material processing during manufacturing, and the relationships between properties. By applying ML methods, the experimental effort in developing new composite materials is significantly reduced, opening up new possibilities in the field of material design. It is aimed at students, academics, and researchers interested in the modeling and design of composite materials.