MATERIAL MODEL CALIBRATION AND VALIDATION FOR LAMINATED COMPOSITES USING KRIGING SURROGATE MODELS

The aim of this paper is to present a methodological approach to speed up the numerical calibration of a composite material in the automotive industry. Extended experimental/numerical activity can be very expensive both in terms of economic and computer resources, since the material parameters required by material models have to be assessed by investigating several loading conditions. From a numerical point of view, this implies running many simulations in which material model parameters are tweaked to achieve the correlation between numerical and experimental results. The methodology presented in this study is used to tune the LS-DYNA material card *mat rate sensitive composite fabric (MAT 158) for the numerical characterization of a laminate composite. The workflow follows the Building Block Approach (BBA) by first exploiting several experimental tests at coupon level to perform a preliminary material model tuning. Thereafter, the paper suggests, and demonstrates, how to implement a surrogate-based optimization technique to avoid trial-and-error attempts and complete the MAT 158 final calibration, thus increasing the speed of the calibration process. Eventually, the correlation between numerical and experimental results of a three-point bending test of a beam is evaluated to assess the calibrated set of material parameters.