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In order to develop confidence in numerical models which are used for automotive crash simulations, results are compared with test data. Modeling assumptions are made when constructing a simulation model for a complex system, such as a vehicle. Through a thorough understanding of the modeling assumptions an appropriate set of variables can be selected and adjusted in order to improve correlation with test data. Such a process can lead to better modeling practices when constructing a simulation model. 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 a methodology for enabling the update of a simulation model for improved correlation is presented.

One of the main threats to military vehicles originates from landmine blasts. In order to improve the survivability of the occupants it is important to design a military vehicle for increased occupant safety. Simulation technology that combines modeling of the blast loads from the landmine explosion, the response of the vehicle to the blast load, and the loads developed on the members of an occupant are important factors in this effort. Uncertainties from the soil properties can influence the blast loads and thus the occupants' safety. In this paper, principal component analysis along with metamodel theory are employed for developing fast running models for the response functions of interest. The response functions of interest are the time domain loads which are developed on an occupant's members due to the blast. The fast running models allow assessing the probability level associated with injury for an occupant.