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Soft-computing-based car body deformation and EES determination for car crash analysis systems

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Abstract(s)

Car body deformation modeling plays a very important role in crash accident analyses, as well as in safe car body design. The determination of the energy absorbed by the deformation and the corresponding energy equivalent speed can be of key importance; however, their precise determination is a very difficult task. Starting from the results of crash tests, intelligent and soft methods offer a way to model the crash process itself, as well as to determine the absorbed energy, the before-crash speed of the car, etc. In this paper, a modeling technique and an intelligent expert system are introduced, which, together, are able to follow the deformation process of car bodies in car crashes and analyze the strength of the different parts, which can significantly contribute to the improvement of the safety of car bodies.
Car body deformation modeling plays a very important role in crash accident analyses, as well as in safe car body design. The determination of the energy absorbed by the deformation and the corresponding energy equivalent speed can be of key importance; however, their precise determination is a very difficult task. Starting from the results of crash tests, intelligent and soft methods offer a way to model the crash process itself, as well as to determine the absorbed energy, the before-crash speed of the car, etc. In this paper, a modeling technique and an intelligent expert system are introduced, which, together, are able to follow the deformation process of car bodies in car crashes and analyze the strength of the different parts, which can significantly contribute to the improvement of the safety of car bodies.

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Keywords

Car body deformation Crash analysis Energy equivalent speed (ees) determination Fuzzy and neural network (nn)-based modeling Fuzzy corner detection Fuzzy edge detection Intelligent systems Three-dimensional (3-d) modeling

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Institute of Electrical and Electronics Engineers (IEEE)

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