Today the numerical simulation is an inherent process of the development of the passive safety of vehicles. Robust and predictable computational models are the base of successful application of numerical simulations. The evaluation of the level of correlation of those models to the real world needs objective and reliable rating methods. In the past this rating was either done by engineering judgment or by analysing single peaks or zero-crossings of response curves in comparision with test data. Nowadays, it is common agreement that for an objective rating the complete curve data have to be taken into account.
In this paper, a new method is presented that provides an objective evaluation of whole response curves coming from test and simulation. The method combines two independent sub-methods, a corridor rating and a cross-correlation rating. The corridor rating evaluates the fitting of a response curve into user-defined or automatically calculated corridors. The cross-correlation method evaluates phase shift, shape and area below curves. It was found that the use of both of these two sub-methods is essential because the disadvantages of each sub-method are compensated by the other method. Both methods were implemented into a tool called CORA – correlation and analysis. The philosophy of this tool is to separate engineer’s knowledge from the algorithms. External parameters to adjust the algorithms are representing this knowledge. So it is possible to tune the evaluation to the specific needs of the application.
The rating method was successfully used in a project on the improvement of Hybrid III 50th dummy models. It was possible to distinguish qualitatively and quantitatively between different releases of the model. In summary, the development of this rating method is a step forward to get an objective quality criterion of computational models.
In a next step the robustness of the rating will be analysed by varying the external parameters. Furthermore, the tool will also be used to analyse and evaluate results of physical tests.