Artificial neural network modelling of PET constitutive behavior in stretch blow molding

This characterization is the base of creating a big enough training database to train the ANN models.<br><br>By comparing the performance of the pure ANN based constitutive model under both displacement-controlled deformation and load-controlled deformation, the drawbacks of applying the pure ANN model as a constitutive model in load-controlled simulations were pointed out. In order to figure out this problem, some physical equations were embedded with ANN models to enlarge its stabilization under load-controlled scenario and a Hybrid ANN based material model was developed based on a part of the original Buckley and two ANN models.<br><br>The results of the single element finite element (FE) analysis using the Hybrid ANN based material model showed a good prediction on the constitutive behaviour of aPET during conventional biaxial stretching.

In predicting the deformation behaviour of aPET during the blowing process, the material model demonstrated its capability of capturing the stress response of aPET under arbitrary deformation. <br><br>A finite element model which included the validated process parameters and the Hybrid ANN based material model was created to mimic the free stretch-blow process and SBM process with large delay time. The results showed a good prediction of preform shape evolution, no matter whether the deformation tends towards a sequential biaxial stretch or a simultaneous biaxial deformation.<br><br><i>Thesis is embargoed until 31 July 2029.</i>