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Objective evaluation of the quality of the FAT ES-2 dummy model

The numerical simulation is an essential part of the development of the passive safety of vehicles. Robust and predictable computational models are the base of the successful application of those simulations. Crash test dummies and their virtual counterparts are measuring tools to evaluate the injury risks to occupants in car crashes. The progress of those dummy models was remarkable over the past years. By increasing the quality, the potential of further significant improvements declines. Hence, the assessment of im- provements and their impact on the overall quality of simulations is getting more complex. Major improvements of sub-parts do not necessarily improve the overall performance of a model. Therefore, a standardised objective evaluation of models could ease the definition of priorities of model updates. Objective rating tools could help to solve this problem. These tools are calculating the level of correlation between two signals, usually coming from test and simulation. All signal ratings can be merged to global ratings. However, the analysis of only one loading case is not sufficient to calcu- late a reliable and a robust quality score of a dummy model. A more comprehensive approach is required to provide a valid rating for all relevant loading conditions. Furthermore, it must distin- guish between good and poor models and should correlate with user experiences. This paper presents results of a study to assess the quality of the LS-DYNA FAT ES-2. The data set comprises results of dummy certification tests as well as results of various component and sled tests. The extraction of the most relevant dummy responses was an essential part of the evaluation too. Finally, all scenarios were applied to different releases of the FAT ES-2. The cal- culated quality scores were verified with the experiences of users of the model. The findings of this study are limited to the FAT ES-2 model but can be transferred to another dummy model. However, the selection of loading cases and signals must be adjusted to each dummy.