Study on the influence of work-hardening modeling in springback prediction

Abstract

The main goal of this study is to evaluate the influence of work-hardening modeling in springback prediction in the first phase of the Numisheet'05 ''Benchmark 3'': the U-shape ''Channel Draw''. Several work-hardening constitutive models are used in order to allow the different materials' mechanical behavior to be better described: the Swift law (a power law) or a Voce type saturation law to describe the classical isotropic work-hardening; a Lemaître and Chaboche type law to model the non-linear kinematic hardening, which can be combined with the previous two; and Teodosiu's microstructural work-hardening model. This analysis was carried out using two steels currently used in the automotive industry: mild (DC06) and dual phase (DP600). Haddadi et al. [Haddadi, H., Bouvier, S., Banu, M., Maier, C., Teodosiu, C., 2006. Towards an accurate description of the anisotropic behaviour of sheet metals under large plastic deformations: Modelling, numerical analysis and identification. Int. J. Plasticity 22 (12), 2226-2271] performed the mechanical characterization of these steels, as well as the identification of the constitutive parameters of each work-hardening model, based on an appropriate set of experimental data such as uniaxial tensile tests, monotonic and Bauschinger simple shear tests and orthogonal strain-path change tests, all at various orientations with respect to the rolling direction of the sheet. All the simulations were carried out with the inhouse FE code DD3IMP. The selected sheet metal formed component induces high levels of equivalent plastic strain. However, for the several work-hardening models tested, the differences in springback prediction are not significantly higher than those previously reported for components with lower equivalent plastic strain levels. It is shown that these differences can be related to the predicted through-thickness stress gradients. The comparative significance of both equivalent plastic strain levels and strain-path changes in the through-thickness stress gradients is discussed.

Identification of nonlinear kinematic hardening constitutive model parameters using the virtual fields method for advanced high strength steels

“…Currently, AHSS are widely utilized for automotive applications. As is well known, springback is a short-coming for materials that have low strength-to-modulus ratio, which results in undesired shape after the release of load (Lee et al, 2005a;Lee et al, 2005b;Narasimhan and Lovell, 1999), commonly seen for AHSS (Chongthairungruang et al, 2012;Oliveira et al, 2007;Zang et al, 2014). In order to predict the springback behavior, an effective way is to develop finite element (FE) simulation with proper material constitutive model.…”

Prediction of wrinkling and springback in sheet metal forming

“…Several advanced yield criteria and work hardening laws (constitutive models) have been implemented in DD3IMP to allow a better description of the different material mechanical behaviour [13,18]. In each load step, an explicit approach is used to calculate the trial solution, which is adjusted using a generalization of the rmin strategy [19].…”

“…Since the prediction of wrinkling phenomena in sheet metal forming simulation requires a fine mesh [6], a regular mesh is adopted in the Oxy plane (element size of 1.0 mm in the central region), as shown in Figure 5. The discretization of the blank comprises two layers of finite elements through the thickness, which enable an accurate prediction of the forming forces and the springback [13]. Hence, the modelling of the full blank comprises 130,000 finite elements, while 1/4 of the blank requires 32,500 finite elements (see Figure 5).…”

“…For instance, it is known that wrinkling prediction is strongly affected by the finite element discretization [6]. Also, springback prediction is influenced by the model selected to describe the material kinematic hardening behaviour [13].…”

Case study on the influence of kinematic hardening within a parameter-free and non-invasive form finding approach

“…Oliveira et al [21] further utilized the parameter set for analyzing the springback prediction of sheets, in which the modelling of the Bauschinger effect has a major impact. As a feature, the parameter sets are thereby separately identified in [19] on the one hand for a pure isotropic hardening ( = ) with the Voce law, see Eq.…”