Beam element modelling of vehicle body-in-white applying artificial neural network

In this study a large knowledge base is first established through numerous designs of experiments on beam elements, based on a validated finite element model of a reference vehicle body-in-white. Then a recurrent artificial neural network is applied to extract the input/output relationship between the crash dynamic characteristics and beam element features. With such established relationship, beam element features are predicted according to expected crash dynamic characteristics. Our analyses show that the predicted beam element model enables generating essential crash dynamic characteristics for concept BIW design evaluation at a reasonable level of accuracy. Last, a data assurance criterion is developed to quantitatively validate the beam element modelling.