Combined strength analysis of deformation capability of a body under frontal force impact

The use of numerical strength analysis at the current stage of development of computer technology and application software is a common practice in design activities with respect to vehicle parts and units. With the combined use of full-scale experiments and numerical research methods, the issues of results coordination, their qualitative and quantitative interpretation become relevant. The objective of the presented work is to consider and study particular issues of data correlation obtained during full-scale tests (a car collision with a crumpled obstacle) with the results of a numerical strength experiment. As part of the study of the deformation response of the structure to the frontal force impact, the results of bench tests for compliance with safety regulations were considered, which showed insufficient deformation compliance of the body elements, which led to significant damage to the passenger compartment. The obtained data, namely, the depth of displacement of the front end of the side member, were included in the working parameters during the subsequent numerical strength study. It is shown that the assignment of reasonable initial and boundary conditions of the problem, as well as the introduction of a number of assumptions, allows us to significantly limit the size of the calculation problem. The virtual picture of deformations, in general, turned out to be visually similar to the results of full-scale bench tests. Computer analysis revealed in detail the dynamics and nature of destruction, revealed design flaws: the presence of a massive, non-crushable central region in the spar, transmitting the main energy of the impact to the cabin part. As a result, it can be summarized that the results of full-scale tests and the numerical experiment showed a visually similar picture. At the same time, the data of the numerical experiment are more detailed, which provided grounds for continuing studies of modified design options using numerical methods, significantly reducing the number of full-scale experiments.