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Naji, M. |
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Motta, Antonella |
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Aletan, Dirar |
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Mohamed, Tarek |
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Ertürk, Emre |
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Taccardi, Nicola |
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Kononenko, Denys |
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Petrov, R. H. | Madrid |
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Alshaaer, Mazen | Brussels |
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Bih, L. |
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Casati, R. |
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Muller, Hermance |
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Kočí, Jan | Prague |
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Šuljagić, Marija |
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Kalteremidou, Kalliopi-Artemi | Brussels |
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Azam, Siraj |
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Ospanova, Alyiya |
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Blanpain, Bart |
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Ali, M. A. |
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Popa, V. |
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Rančić, M. |
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Ollier, Nadège |
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Azevedo, Nuno Monteiro |
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Landes, Michael |
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Rignanese, Gian-Marco |
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Zulueta, Kepa
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Topics
Publications (4/4 displayed)
- 2023Composites Part A: Applied Science and Manufacturing / A macroscopic model of the compaction process during compression molding of carbon fiber sheet molding compoundscitations
- 2023Advancing on viscosity characterization and modeling of SMC for compression molding simulationcitations
- 2023Determination of fiber orientation model parameters for injection molding simulations via automated metamodel optimizationcitations
- 2023Finite-strain Thermomechanics of Viscoelastic-Viscoplastic Model for Thermoplastic Polymers
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article
Advancing on viscosity characterization and modeling of SMC for compression molding simulation
Abstract
<jats:title>Abstract</jats:title><jats:p>Sheet molding compounds are thermoset‐based and glass or carbon fiber reinforced composites. SMCs are transformed through compression molding and for optimizing this process, virtual compression molding tools are employed. These tools require material model calibrations based on raw material data obtained by different characterization techniques. In this research, temperature and shear rate dependent viscosity of two SMCs has been experimentally characterized by oscillatory rheometer (RPA) and extensional rheometry. The obtained results were fitted to the modified Cross‐Castro‐Macosko viscosity model. Finally, the compression molding of two validation plates was performed virtually and experimentally. The obtained results demonstrate that, testing by RPA is preferable for industrial partners because tests are run with standard equipment and no manual post‐processing of the experimental data is required. Besides, the comparison of the virtual clamping force estimation with the experimental clamping force, shows that material models calibrated with RPA‐generated data foresee a lower clamping force overestimation.</jats:p>