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A Novel Multi-Region, Multi-Phase, Multi-Component-Mixture Modeling Approach to Predicting the Thermodynamic Behaviour of Thermoplastic Composites during the Consolidation Process

In the processing of thermoplastic composites, great importance is attributed to the consolidation step, as it can significantly reduce the porosity of the semi-finished product and thus influence considerably the quality of the final component. This work presents an approach to modeling the thermod...

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Detalles Bibliográficos
Autores principales: Kobler, Eva, Birtha, Janos, Marschik, Christian, Straka, Klaus, Steinbichler, Georg, Zwicklhuber, Paul, Schlecht, Sven
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9658174/
https://www.ncbi.nlm.nih.gov/pubmed/36365774
http://dx.doi.org/10.3390/polym14214785
Descripción
Sumario:In the processing of thermoplastic composites, great importance is attributed to the consolidation step, as it can significantly reduce the porosity of the semi-finished product and thus influence considerably the quality of the final component. This work presents an approach to modeling the thermodynamic behavior of composite materials during hot-press consolidation. For this purpose a multi-region, multi-phase and multi-component-mixture model was developed using the simulation toolbox OpenFOAM(®). The sensitivity of the model was tested by varying the thermal parameters and mesh resolution, confirming its robustness. Validity of the model was confirmed by comparing simulation results to experimental data for (i) polycarbonate with 44% carbon fiber by volume and (ii) polypropylene with 45.3% glass fiber by volume. The simulation allows very precise estimation of when a particular temperature, such as the glass transition temperature or melting point, will be reached at the core of a composite. In relation to the total process time, maximum deviation of the simulation from the experimental data amounted to 2.84%. Therefore, the model is well suited for process optimization, it offers a basis for further model implementations and the creation of a digital twin.