Model reduction and clustering techniques for crash simulations
Abstract
Model reduction in car crash simulations is a fairly new research field. In this paper, a possible workflow is presented: Since nonlinear behavior can occur, parts with linear and nonlinear behavior need to be separated with clustering methods such as k-means or spectral clustering. For the latter, a nonlinear reduction technique such as POD-DEIM needs to be applied. A longitudinal chassis beam of a 2001 Ford Taurus is used to examine the different clustering methods. (© 2015 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)