Evolutionary identification of laminates' granular parameters

The paper deals with the identification of material constants in simple and hybrid laminates. It is assumed that identified constants are non-deterministic and can be described by means of different forms of the information granularity represented by interval numbers, fuzzy numbers or random variables. The TwoStage Granular Strategy combining global (Evolutionary Algorithm) and local (gradient method supported by an Artificial Neural Network) optimization techniques is used to solve the identification problems. Finite Element Method in the granular form is used to solve the direct problem for laminates. Modal analysis methods are employed to collect measurement data for the identification process. Numerical examples presenting effectiveness of the strategy are enclosed.