Classical inverse and metamodel approach in identification of nanomaterials properties

System of nanocoatings deposited by using physical vapour deposition is planned to be applied in the artificial heart prosthesis. Material models of these coatings are necessary for numerical design of these products and are crucial for accuracy of simulations. The objective of the present work is identification of parameters of material model of nanocoatings using two methods based on the nanoindentation test data: the classical inverse analysis and the artificial neural network metamodel. The inverse analysis is preceded by the development of FEM model dedicated to the nanoindentation test for the system of nanocoatings. The parameters of individual coating of the system are evaluated. In the second approach to decrease the computation cost, the metamodel is suggested. The metamodelling method is based on the artificial neural network technique. The achieved results confirm the usefulness of the presented solution in the identification of the material properties for the system of nanocoatings.