Estimation of constitutive parameters for shape memory polymer thermo-mechanical cycle by an integrated simulation and inverse optimization method

In this work, a method for inverse optimization of shape memory polymer material parameters is proposed to determine the intrinsic model parameters more quickly and accurately for simulated experimental test analysis. First, the basic mechanical properties of the material are characterized experimentally and the parameters of the generalized Maxwell model based on SMP material are fitted. Then, a joint simulation inversion optimization method is built in the ISIGHT-MATLAB-ABAQUS integrated environment to optimize the time domain Prony series parameters using downhill simplex optimization algorithm. The results show that the average errors of the stress curves before and after the optimization of the cooling solid phase and the experimental results are 0.31 MPA and 0.23 MPA, respectively, and the average errors of the strain curves in the warming recovery phase are 1.70% and 0.40%, respectively. After the inversion optimization, the average errors of the stress curves are optimized by 25.8% and the average errors of the strain curves are optimized by 76.5%. This method makes the simulation results more stable with the experimental results, which can effectively reduce the experimental cost and promote the shape memory property of SMP to be widely used in engineering.