Abstract: The Bammann-Chiesa-Johnson (BCJ) viscoplasticity constitutive model is advanced to predict mechanical behavior of metals. And the capability of prediction relies on the determination of the model parameters. Normally, the parameters would be identified by using the back-analysis method. However, the method is very complicated because there are quite a number of parameters in the BCJ model and it is not easy to obtain the optimal values. These parameters are involved to describe the coupling effects of strain, strain rate, temperature, as well as the load path and temperature history. This paper proposed a method to identify the 18 papameters, in which comprehensive experiments, based on the physics of the parameters, had been conducted, including quasi-static tests, creep tests and the split Hopkinson pressure bar (SHPB) tests, furthermore parameters decoupling and the Particle Swarm Optimization (PSO) algorithm had been applied. The dynamic mechanical response of Al 1060 was taken to validate the method and the prediction on flow stressesis in good agreement with the test data. The quantitative error analysis showed that the method was effective for a large range of strain rate and temperature variation with high accuracy.
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2017, Vol. 31 
