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Estimation of state and material properties during heat-curing molding of composite materials using data assimilation: A numerical study

Accurate simulations of carbon fiber-reinforced plastic (CFRP) molding are vital for the development of high-quality products. However, such simulations are challenging and previous attempts to improve the accuracy of simulations by incorporating the data acquired from mold monitoring have not been...

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Detalles Bibliográficos
Autores principales: Matsuzaki, Ryosuke, Tachikawa, Takeshi, Ishizuka, Junya
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5857893/
https://www.ncbi.nlm.nih.gov/pubmed/29560466
http://dx.doi.org/10.1016/j.heliyon.2018.e00554
Descripción
Sumario:Accurate simulations of carbon fiber-reinforced plastic (CFRP) molding are vital for the development of high-quality products. However, such simulations are challenging and previous attempts to improve the accuracy of simulations by incorporating the data acquired from mold monitoring have not been completely successful. Therefore, in the present study, we developed a method to accurately predict various CFRP thermoset molding characteristics based on data assimilation, a process that combines theoretical and experimental values. The degree of cure as well as temperature and thermal conductivity distributions during the molding process were estimated using both temperature data and numerical simulations. An initial numerical experiment demonstrated that the internal mold state could be determined solely from the surface temperature values. A subsequent numerical experiment to validate this method showed that estimations based on surface temperatures were highly accurate in the case of degree of cure and internal temperature, although predictions of thermal conductivity were more difficult.