Effect of tensile pre-strain on bending and unloading of automotive steels

In recent years, advanced high strength steels (AHSS) have been used in a wide range of automotive applications; they may have property variations through the thickness and the properties may also be dependent of prior processing including pre-straining. In order to model forming processes precisely using, for example, finite element analysis, it is important that material input data should adequately reflect these effects. It is known that shape defects in roll forming are related to small strains in material that has undergone prior deformation in a different strain path. Much research has already been performed on the change in the Young’s Modulus once a steel sheet has been plastically deformed,however many of these tests have only been conducted using tensile testing, and therefore may not take into account differences in compressive and tensile unloading. This research investigates the effect of tensile pre-straining on bending behaviour for various types of material;in bending, one half of the sheet will load and unload in compression and hence experience deformation under a reversed stress. Four different materials were pre-strained in tension with 1%, 3%, 7%, 11% and 25% elongation. Using a free bending test, moment curvature diagrams were obtained for bending and unloading. The results showed that the characteristics of the moment curvature diagram depended on the degree of pre-straining; more highly strained samples showed an earlier elastic-plastic transformation and a decreased Young's Modulus during unloading. This was compared to previous literature results using only tensile tests. Our results could influence the modeling of springback in low tension sheet operations, such as roll forming.

Finite element model updating using estimation of distribution algorithm

Finite Element (FE) model updating has been attracting research attentions in structural engineering fields for over 20 years. Its immense importance to the design, construction and maintenance of civil and mechanical structures has been highly recognised. However, many sources of uncertainties may affect the updating results. These uncertainties may be caused by FE modelling errors, measurement noises, signal processing techniques, and so on. Therefore, research efforts on model updating have been focusing on tackling with uncertainties for a long time. Recently, a new type of evolutionary algorithms has been developed to address uncertainty problems, known as Estimation of Distribution Algorithms (EDAs). EDAs are evolutionary algorithms based on estimation and sampling from probabilistic models and able to overcome some of the drawbacks exhibited by traditional genetic algorithms (GAs). In this paper, a numerical steel simple beam is constructed in commercial software ANSYS. The various damage scenarios are simulated and EDAs are employed to identify damages via FE model updating process. The results show that the performances of EDAs for model updating are efficient and reliable.