Nonlinear metamodeling of bulky data and applications in automotive design

We describe and discuss methods for nonlinear metamodeling of simulation databases featuring continuous exploration of simulation results, tolerance prediction, sensitivity analysis, and rapid interpolation of bulky FEMdata. Themethods have been implemented in the design-parameter optimization tool DesParO. Reallife applications from the automotive industry show their efficiency.