Breaking through the plasticity modeling limit in plane strain and shear loadings of sheet metals by a novel additive-coupled analytical yield criterion

The automotive industry increasingly relies on numerical simulations to predict the geometry and forming processes of complex curved parts. Accurate yield stress functions that cover a wide range of stress states, such as uniaxial tension, equi-biaxial tension, near-plane strain tension, and simple shear, are essential for implementing virtual manufacturing technologies. In this work, a new additive-coupled analytical yield stress function, CPN2025, is proposed to accurately describe plastic anisotropy under various loading conditions. CPN2025 integrates the Poly4 anisotropic yield criterion with the Hosford isotropic yield criterion under a non-associated flow rule. A non-fixed-exponent calibration strategy is introduced, overcoming the limitations of existing yield criteria that typically offer curvature adjustment with only positive or negative correlations. CPN2025 is compared with other non-associated yield functions, including SY2009, CQN2017, and NAFR-Poly4, to evaluate its performance in predicting the plastic anisotropy of DP490, QP1180, AA5754-O, and AA6016-T4. Results show that, while meeting convexity requirements, the additive-coupled approach not only provides greater flexibility than the multiplicative-coupled but also simplifies the acquisition of partial derivative information. CPN2025 delivers the highest accuracy in characterizing anisotropic yield behavior, particularly for near-plane strain tension and simple shear loadings. Additionally, incorporating more uniaxial tensile yield stress-calibrated material parameters significantly improves the prediction capacity of in-plane anisotropic behavior. The use of anisotropic hardening concepts enhances the model's capability to capture the subsequent yield behavior across the entire plastic strain range. (c) 2025 Published by Elsevier Ltd on behalf of The editorial office of Journal of Materials Science & Technology. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)