为了进一步提高板料成形中的回弹预测精度,分别建立了基于Ziegler线性随动强化模型、Lemaitre-Chaboche非线性随动强化以及非线性混合强化模型的Gurson-Tvergaard-Needleman(GTN)细观损伤本构模型,并给出有限元数值积分方法。通过用户自定义材料子程序VUMAT将损伤模型嵌入到有限元软件ABAQUS中,以NUMISHEET’93板料U型弯曲考题为例,应用显隐相结合的方法模拟分析了不同材料强化模型和损伤对板料回弹量的影响。结果表明:在相同GTN损伤模型情况下,线性随动和非线性随动强化模型预测得到的板料回弹量较小,等向强化预测的板料回弹量偏大,非线性混合强化预测的板料回弹量介于它们之间。材料模型在考虑损伤因素后,预测的回弹严重程度比无损伤情况时略小,与实验值更相近。
To improve the accuracy of springback prediction in sheet metal forming, a Gurson-Tvergaard- Needleman (GTN) meso-damage model and its finite element constitutive integration algorithm are developed, based on Ziegler linear kinematic hardening, Lemaitre-Chaboche nonlinear kinematic and nonlinear combined hardening rules. The GTN damage models are implemented in the commercial finite element software ABAQUS by using the user material subroutine VUMAT. The NUMISHEET'93 U-bending benchmark problem is employed to investigate the effect of different hardening rules and damage on springback prediction by using the coupled explicit to implicit the finite element procedure. The results show that the springback predicted by the linear kinematic hardening and nonlinear kinematic rules is small, then is that predicted by the nonlinear combined hardening rule. The springback predicted by the isotropic hardening rule is the largest. After considering the damage, the GTN model predicts lower springback, which is closer to the experiment data.