Development of a DIC-instrumented Bubble Inflation Test: Characterization of ABS Thermoforming

This study addresses the mechanical characterization of ABS material under test conditions relevant to the vacuum-forming process. In order to determine the linear viscoelasticity of the material, a shear oscillatory rheometer was employed to extract the relaxation spectra which is directly used to...

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Hauptverfasser: Varedi, rasoul, Buffel, bart, Mergan, Sander, Scheuer, Adrien, Coppieters, Sam, Desplentere, Frederik
Format: Tagungsbericht
Sprache:eng
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Zusammenfassung:This study addresses the mechanical characterization of ABS material under test conditions relevant to the vacuum-forming process. In order to determine the linear viscoelasticity of the material, a shear oscillatory rheometer was employed to extract the relaxation spectra which is directly used to satisfy the linear portion of the constitutive equation. To examine the nonlinear response of the material, a custom-made bubble inflation test setup was linked to a stereo Digital Image Correlation (DIC) system to measure the large deformation behavior during fast inflation in the range of forming temperature (140 to 180°C). The main goal here was to calculate the thickness of the material at the pole region by measuring the principal strains. A direct thickness measurement using an ultrasonic thickness gauge performed on the pole of the bubble in the final deformed state shows an excellent correspondence to the calculated thickness using DIC. To calibrate the nonlinear part of the viscoelastic model, an inverse approach was adopted based on Finite Element Model Updating (FEMU). The thickness variation at the pole was defined as an objective feed function to optimize the nonlinear parameters iteratively. To examine the robustness of the method, the simulated thickness values are compared with the experimental data across the arc length of the bubble at different times and temperatures. The calibrated constitutive model is afterward implemented into the simulation tool to predict the real industrial vacuum-forming process by knowing the temperature distribution using a thermal camera during forming step.
ISSN:0094-243X