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<p>Modeling the thermoforming of amorphous thermoplastics under industrially relevant, complex mould shape remains a significant challenge due to the interplay of temperature gradients, large multiaxial strains, and mould-sheet contact. This work presents a single-test, multi-mode material calibration method within a digital twin framework, capturing equi-biaxial, non-equi-biaxial, and off-axis biaxial deformation simultaneously in a stereo DIC-instrumented bubble inflation setup. The calibrated visco-hyperelastic model is applied to simulate forming over a custom cutlery mould with multiple cavity depths, sharp transitions, and localized strain concentrations. Experimental and simulated strain fields and thickness profiles show strong agreement, demonstrating predictive capability under highly non-uniform industrial conditions. The approach reduces experimental effort, improves model robustness, and enables transferable, industry-ready digital twin workflows for process optimization and virtual prototyping in thermoforming.</p>

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Unified multi-mode material characterization and digital twin simulation for complex thermoforming

  • 期刊论文

  • 发表日期：

    2026年7月3日

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  • Rasoul Varedi,
  • Bart Buffel,
  • Frederik Desplentere

摘要

Modeling the thermoforming of amorphous thermoplastics under industrially relevant, complex mould shape remains a significant challenge due to the interplay of temperature gradients, large multiaxial strains, and mould-sheet contact. This work presents a single-test, multi-mode material calibration method within a digital twin framework, capturing equi-biaxial, non-equi-biaxial, and off-axis biaxial deformation simultaneously in a stereo DIC-instrumented bubble inflation setup. The calibrated visco-hyperelastic model is applied to simulate forming over a custom cutlery mould with multiple cavity depths, sharp transitions, and localized strain concentrations. Experimental and simulated strain fields and thickness profiles show strong agreement, demonstrating predictive capability under highly non-uniform industrial conditions. The approach reduces experimental effort, improves model robustness, and enables transferable, industry-ready digital twin workflows for process optimization and virtual prototyping in thermoforming.