In the event of a crash involving a car, its seats, together with their backrests and head supports, ensure the safety of the passengers. The filling material used for such a car seat is normally made of polyurethane foam. To simulate the behaviour of the seat assembly during a crash, the material characteristics of the seat-filling foam should be appropriately modelled. The purpose of this paper is to present a method, with which the proper parameter values of the selected material model for the seat-filling foam can be easily determined.
In the study, an experiment with the specimen from seat-filling foam was carried out. The results from this experiment were the basis for the determination of the parameter values of the low-density-foam material model, which is often used in crash-test simulations. Two different numerical optimisation algorithms – a genetic algorithm and a gradient-descent algorithm – were coupled with LS-DYNA explicit simulations to identify the material parameters.
The paper provides comparison of two optimisation algorithms and discusses the engineering applicability of the results.
This paper presents an approach for the identification of the missing parameter values of the highly non-linear material model, if these cannot be easily determined directly from experimental data.
Škrlec, A., Klemenc, J. and Fajdiga, M. (2014), "Parameter identification for a low-density-foam material model using numerical optimisation procedures", Engineering Computations, Vol. 31 No. 7, pp. 1532-1549. https://doi.org/10.1108/EC-03-2013-0100Download as .RIS
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