Composite materials in automotive: Improving safety by refining FEA correlation

In the last few years, the restrictive safety standards and the need for weight reduction have brought the crashworthiness research to focus on composite materials because of their high energy absortion-to-mass ratio. On the other hand, the possibility of obtaining predictive dynamic FEA models for these new materials is still an open issue: The present work aims at developing a methodology for the characterization of composite materials with particular interest for the head impact simulation. Composite materials behavior, defined through the mathematical models implemented in FEA codes, is very complex and requires a large amount of physical and numerical setting parameters. The majority of these parameters can be obtained by an experimental campaign that involves several kind of different tests. The presented methodology allows to obtain a good numerical-experimental correlation simply performing few tests which emulate the behavior of the component during the head impact event. A software tool based on a genetic optimization technique has been developed in order to determinate automatically the material properties values that guarantee the best numericalexperimental correlation. Copyright copy; 2013 by ASME.