An inverse strategy to determine constitutive parameters of tubular materials for hydroforming processes

This paper is to determine the flow stress curve of 5049-O aluminium alloy by a tube hydraulic bulging test with fixed end-conditions. During this test, several tubular specimens are bulged under different internal pressures before their bursting, and the corresponding bulging height and wall thickness at the pole are measured. An inverse strategy is developed to determine the constitutive parameters of tubular materials based on experimental data, which combines the finite element method with gradient-based optimization techniques. In this scheme, the objective function is formulated with the sum of least squares of the error between numerical and experimental data, and finite difference approximation is used to calculate the gradient. The tubular material behavior is assumed to meet the von Mises yield criterion and Hollomon exponential hardening law. Then, constitutive parameters identification is performed by minimization of the objective function. In order to validate the performance of this framework, identified parameters are compared with those obtained by two types of theoretical models, and tensile tests are performed on specimens cut from the same tubes. The comparison shows that this inverse framework is robust and can achieve a more accurate parameter identification by eliminating mechanical and geometrical assumptions in classical theoretical analysis. (c) 2021 Chinese Society of Aeronautics and Astronautics. Production and hosting by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Automated summary

This paper determines the flow stress curve of 5049-O aluminium alloy using a tube hydraulic bulging test. It introduces an inverse strategy that combines the finite element method with gradient-based optimization techniques to determine the constitutive parameters of the material. The results show that this framework can achieve more accurate parameter identification by eliminating assumptions made in classical theoretical analysis.