Model update and variability assessment for automotive crash simulations
conference paper
In order to develop confidence in numerical models which are used for automotive crash simulations, results are often compared with test data, and in some cases the numerical models are adjusted in order to improve the correlation. Comparisons between the time history of acceleration responses from test and simulations are the most challenging. Computing accelerations correctly is more difficult compared to computing displacements, velocities, or intrusion levels due to the second order differentiation with time. In this paper an approach for updating the simulation model for improved correlation is presented. Fast running models are developed for the time histories of the acceleration at the measurement locations based on principal component decomposition and metamodeling. A large number of iterations is required during the model update process in order to guide the changes in the numerical model for improved correlation. The fast running models are utilized during this process instead of the actual solver for computing the time histories of the accelerations. Once the model update is completed, the fast running models are further employed for enabling probabilistic analyses and for establishing a statistical correlation metric between the numerical solution and the test data.
TNO Identifier
460807
ISSN
21915644
ISBN
9781604237597
Source title
25th Conference and Exposition on Structural Dynamics 2007, IMAC-XXV, 19 February 2007 through 22 February 2007, Orlando, FL
Files
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