Abstract

The flow stress is significantly affected in the precision machining process by the factors of strain path, strain rate history, temperature history and even microstructures. The physics-based Bammann–Chiesa–Johnson viscoplastic model is capable of capturing the flow stress evolution as well as the rate and temperature dependence. However, it is extremely challenging to identify all 18 constants in the model. In this paper, a novel method was proposed to identify the material constants by decoupling the parameters of internal state variables. A comprehensive experimental plan was conducted to obtain the true stress–strain curves of aluminum 1060 at elevated temperatures from 25 to 500 °C and strain rates from 10−6 to 16400 s−1 using creeping, quasi-static and SHPB methods. The particle swarm optimization algorithm was adapted to find the optimal solutions of the model parameters. The results showed that the prediction on the established model matched well with the experimental data. The quantitative error analysis confirmed the reliability of the method across a large range of strain rate and temperature variations.

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