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A Semi-Analytical Model to Predict Infusion Time and Reinforcement Thickness in VARTM and SCRIMP Processes
In liquid composite molding processes, such as resin transfer molding (RTM) and vacuum assisted resin transfer molding (VARTM), the resin is drawn through fiber preforms in a closed mold by an induced pressure gradient. Unlike the RTM, where a rigid mold is employed, in VARTM, a flexible bag is comm...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6401964/ https://www.ncbi.nlm.nih.gov/pubmed/30960004 http://dx.doi.org/10.3390/polym11010020 |
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author | Rubino, Felice Carlone, Pierpaolo |
author_facet | Rubino, Felice Carlone, Pierpaolo |
author_sort | Rubino, Felice |
collection | PubMed |
description | In liquid composite molding processes, such as resin transfer molding (RTM) and vacuum assisted resin transfer molding (VARTM), the resin is drawn through fiber preforms in a closed mold by an induced pressure gradient. Unlike the RTM, where a rigid mold is employed, in VARTM, a flexible bag is commonly used as the upper-half mold. In this case, fabric deformation can take place during the impregnation process as the resin pressure inside the preform changes, resulting in continuous variations of reinforcement thickness, porosity, and permeability. The proper approach to simulate the resin flow, therefore, requires coupling deformation and pressure field making the process modeling more complex and computationally demanding. The present work proposes an efficient methodology to add the effects of the preform compaction on the resin flow when a deformable porous media is considered. The developed methodology was also applied in the case of Seeman’s Composite Resin Infusion Molding Process (SCRIMP). Numerical outcomes highlighted that preform compaction significantly affects the resin flow and the filling time. In particular, the more compliant the preform, the more time is required to complete the impregnation. On the other hand, in the case of SCRIMP, the results pointed out that the resin flow is mainly ruled by the high permeability network. |
format | Online Article Text |
id | pubmed-6401964 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-64019642019-04-02 A Semi-Analytical Model to Predict Infusion Time and Reinforcement Thickness in VARTM and SCRIMP Processes Rubino, Felice Carlone, Pierpaolo Polymers (Basel) Article In liquid composite molding processes, such as resin transfer molding (RTM) and vacuum assisted resin transfer molding (VARTM), the resin is drawn through fiber preforms in a closed mold by an induced pressure gradient. Unlike the RTM, where a rigid mold is employed, in VARTM, a flexible bag is commonly used as the upper-half mold. In this case, fabric deformation can take place during the impregnation process as the resin pressure inside the preform changes, resulting in continuous variations of reinforcement thickness, porosity, and permeability. The proper approach to simulate the resin flow, therefore, requires coupling deformation and pressure field making the process modeling more complex and computationally demanding. The present work proposes an efficient methodology to add the effects of the preform compaction on the resin flow when a deformable porous media is considered. The developed methodology was also applied in the case of Seeman’s Composite Resin Infusion Molding Process (SCRIMP). Numerical outcomes highlighted that preform compaction significantly affects the resin flow and the filling time. In particular, the more compliant the preform, the more time is required to complete the impregnation. On the other hand, in the case of SCRIMP, the results pointed out that the resin flow is mainly ruled by the high permeability network. MDPI 2018-12-24 /pmc/articles/PMC6401964/ /pubmed/30960004 http://dx.doi.org/10.3390/polym11010020 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Rubino, Felice Carlone, Pierpaolo A Semi-Analytical Model to Predict Infusion Time and Reinforcement Thickness in VARTM and SCRIMP Processes |
title | A Semi-Analytical Model to Predict Infusion Time and Reinforcement Thickness in VARTM and SCRIMP Processes |
title_full | A Semi-Analytical Model to Predict Infusion Time and Reinforcement Thickness in VARTM and SCRIMP Processes |
title_fullStr | A Semi-Analytical Model to Predict Infusion Time and Reinforcement Thickness in VARTM and SCRIMP Processes |
title_full_unstemmed | A Semi-Analytical Model to Predict Infusion Time and Reinforcement Thickness in VARTM and SCRIMP Processes |
title_short | A Semi-Analytical Model to Predict Infusion Time and Reinforcement Thickness in VARTM and SCRIMP Processes |
title_sort | semi-analytical model to predict infusion time and reinforcement thickness in vartm and scrimp processes |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6401964/ https://www.ncbi.nlm.nih.gov/pubmed/30960004 http://dx.doi.org/10.3390/polym11010020 |
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