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A strain-space nonlinear elasto-plastic model improving springback prediction accuracy and efficiency
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DOI：10.1016/j.jcsr.2024.109210.png)
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Abstract
En 中文
During the forming process of X80 grade high-strength pipeline steel, nonlinear elastic unloading-reloading behaviors and strain hardening followed by softening were observed, closely related to springback prediction. To address this, the most classic model Quasi-Plastic-Elastic (QPE) model, which describes the material's nonlinear elastic behavior, was mapped into a strain space that can describe strain softening behaviors. Considering the hysteresis loop phenomenon during the unloading phase of the pipeline steel, a strain space nonlinear elasto-plastic mixed hardening constitutive model incorporating the aforementioned behaviors was developed. A UMAT subroutine was written in Fortran and implemented in the ABAQUS Standard finite element analysis software for numerical realization of the model. Model parameters were calibrated and the model's accuracy was verified through uniaxial tension and cyclic loading-unloading experiments. Finally, the model was applied to three-point bending forming simulations. The results showed that compared to models not considering both mechanical behaviors simultaneously, the strain space nonlinear elasto-plastic constitutive model predicted the springback angle error within 6 %, with an average error of approximately 4 %, demonstrating good prediction accuracy. As the punch displacement increased, the model gradually surpassed the QPE-Damage model in springback prediction accuracy at larger displacements, highlighting the importance of considering strain softening behavior in model design. Additionally, comparing the computational time required by this model with the QPE-Damage model, this model was 30.32 % more efficient, proving the new model's advantages in both springback prediction accuracy and computational efficiency.
Keywords:
Springback
Nonlinear elastic
Strain space
High-strength steels
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