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Improving Composite Tensile Properties during Resin Infusion Based on a Computer Vision Flow-Control Approach
Liquid composite manufacturing techniques, mainly applied in the transport industry, have been studied and optimized for decades while defect analysis and its minimization have been a goal to increase reliability and mechanical performance. Researchers have found that many process parameters have a...
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/PMC6317164/ https://www.ncbi.nlm.nih.gov/pubmed/30563074 http://dx.doi.org/10.3390/ma11122469 |
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author | Almazán-Lázaro, Juan-Antonio López-Alba, Elías Díaz-Garrido, Francisco-Alberto |
author_facet | Almazán-Lázaro, Juan-Antonio López-Alba, Elías Díaz-Garrido, Francisco-Alberto |
author_sort | Almazán-Lázaro, Juan-Antonio |
collection | PubMed |
description | Liquid composite manufacturing techniques, mainly applied in the transport industry, have been studied and optimized for decades while defect analysis and its minimization have been a goal to increase reliability and mechanical performance. Researchers have found that many process parameters have a strong influence on the mechanical behavior of composite structures where the flow front velocity, closely related to voids, plays a considerable role. In this work, the optimal flow front velocity was evaluated and controlled using a computer vision system for different laminates improving the mechanical tensile properties and void content. Enhanced mechanical tensile properties were found using a feedback flow-controller vision system which was able to keep the optimal flow front velocity constant to reduce the air traps among tows and fibers. Tensile strength was enhanced up to 18% for fiber orientation at 0° and 3.3% at 90°, whereas tensile modulus was increased up to 18.4% for fibers at 0° and 8.7% at 90°. A novel methodology is presented through this work, aiming to improve the robustness of resin film infusion (RFI) processes while ensuring the quality of the composite material. |
format | Online Article Text |
id | pubmed-6317164 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-63171642019-01-08 Improving Composite Tensile Properties during Resin Infusion Based on a Computer Vision Flow-Control Approach Almazán-Lázaro, Juan-Antonio López-Alba, Elías Díaz-Garrido, Francisco-Alberto Materials (Basel) Article Liquid composite manufacturing techniques, mainly applied in the transport industry, have been studied and optimized for decades while defect analysis and its minimization have been a goal to increase reliability and mechanical performance. Researchers have found that many process parameters have a strong influence on the mechanical behavior of composite structures where the flow front velocity, closely related to voids, plays a considerable role. In this work, the optimal flow front velocity was evaluated and controlled using a computer vision system for different laminates improving the mechanical tensile properties and void content. Enhanced mechanical tensile properties were found using a feedback flow-controller vision system which was able to keep the optimal flow front velocity constant to reduce the air traps among tows and fibers. Tensile strength was enhanced up to 18% for fiber orientation at 0° and 3.3% at 90°, whereas tensile modulus was increased up to 18.4% for fibers at 0° and 8.7% at 90°. A novel methodology is presented through this work, aiming to improve the robustness of resin film infusion (RFI) processes while ensuring the quality of the composite material. MDPI 2018-12-05 /pmc/articles/PMC6317164/ /pubmed/30563074 http://dx.doi.org/10.3390/ma11122469 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 Almazán-Lázaro, Juan-Antonio López-Alba, Elías Díaz-Garrido, Francisco-Alberto Improving Composite Tensile Properties during Resin Infusion Based on a Computer Vision Flow-Control Approach |
title | Improving Composite Tensile Properties during Resin Infusion Based on a Computer Vision Flow-Control Approach |
title_full | Improving Composite Tensile Properties during Resin Infusion Based on a Computer Vision Flow-Control Approach |
title_fullStr | Improving Composite Tensile Properties during Resin Infusion Based on a Computer Vision Flow-Control Approach |
title_full_unstemmed | Improving Composite Tensile Properties during Resin Infusion Based on a Computer Vision Flow-Control Approach |
title_short | Improving Composite Tensile Properties during Resin Infusion Based on a Computer Vision Flow-Control Approach |
title_sort | improving composite tensile properties during resin infusion based on a computer vision flow-control approach |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6317164/ https://www.ncbi.nlm.nih.gov/pubmed/30563074 http://dx.doi.org/10.3390/ma11122469 |
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