Reliability analysis of a crashed thin-walled s-rail accounting for random spot weld failures

Abstract

Possibly the most common application of spot welding is in the automobile manufacturing industry, where it is almost universally used to weld the sheet metal car components.However, due to manufacturing inaccuracies and fatigue failures an important number of spot welds may be missing in an operational vehicle. It seems that in order to properly analyze reliability of such structures, in particular crashworthiness reliability, the spot weld failures must be considered. Representing properties of each spot weld in a stochastic model by corresponding random variables is extremely inefficient. Therefore, in the current paper an approach is proposed for handling spot weld defects in the reliability analysis by accounting for their averaged influence on a failure criterion. The approach consists in appropriate treatment of a random noise component of the limit state function. The noise results from strategy of deleting a certain number of randomly selected spot weld elements from the finite element model each time the limit state function value is computed.Dealing with noisy limit state functions in structural reliability analysis is a challenging task. The only method that seems to be insensitive to this phenomenon is Monte Carlo sampling, which for most of the applications of practical interest is prohibitively expensive. Having this in mind, in the paper a method based on the algorithm proposed by Zou et al. in [23] is investigated. The method combines the best features of the first order reliability method, the response surface technique and the importance sampling method to achieve both accuracy and efficiency. A detailed study on the reliability of thin-walled s-rail subjected to crash is performed. Some suggestions concerning modification of the original algorithm are proposed.

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