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Sensor Fusion for Simultaneous Estimation of In-Plane Permeability and Porosity of Fiber Reinforcement in Resin Transfer Molding
To meet the expectation of the industry, resin transfer molding (RTM) has become one of the most promising polymer processing methods to manufacture fiber-reinforced plastics (FRPs) with light weight, high strength, and multifunctional features. The permeability and porosity of fiber reinforcements...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9269317/ https://www.ncbi.nlm.nih.gov/pubmed/35808697 http://dx.doi.org/10.3390/polym14132652 |
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author | Qi, Wei Chiu, Tzu-Heng Kao, Yi-Kai Yao, Yuan Chen, Yu-Ho Yang, Hsun Wang, Chen-Chieh Hsu, Chia-Hsiang Chang, Rong-Yeu |
author_facet | Qi, Wei Chiu, Tzu-Heng Kao, Yi-Kai Yao, Yuan Chen, Yu-Ho Yang, Hsun Wang, Chen-Chieh Hsu, Chia-Hsiang Chang, Rong-Yeu |
author_sort | Qi, Wei |
collection | PubMed |
description | To meet the expectation of the industry, resin transfer molding (RTM) has become one of the most promising polymer processing methods to manufacture fiber-reinforced plastics (FRPs) with light weight, high strength, and multifunctional features. The permeability and porosity of fiber reinforcements are two of the primary properties that control the flow of resin in fibers and are critical to numerical simulations of RTM. In the past, various permeability measurement methods have been developed in the literature. However, limitations still exist. Furthermore, porosity is often measured independently of permeability. As a result, the two measurements do not necessarily relate to the same entity, which may increase the time and labor costs associated with experiments and affect result interpretation. In this work, a measurement system was developed by fusing the signals from capacitive sensing and flow visualization, based on which a novel algorithm was developed. Without complicated sensor design or expensive instrumentation, both in-plane permeability and porosity can be simultaneously estimated. The feasibility of the proposed method was illustrated by experiments and verified with numerical simulations. |
format | Online Article Text |
id | pubmed-9269317 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-92693172022-07-09 Sensor Fusion for Simultaneous Estimation of In-Plane Permeability and Porosity of Fiber Reinforcement in Resin Transfer Molding Qi, Wei Chiu, Tzu-Heng Kao, Yi-Kai Yao, Yuan Chen, Yu-Ho Yang, Hsun Wang, Chen-Chieh Hsu, Chia-Hsiang Chang, Rong-Yeu Polymers (Basel) Article To meet the expectation of the industry, resin transfer molding (RTM) has become one of the most promising polymer processing methods to manufacture fiber-reinforced plastics (FRPs) with light weight, high strength, and multifunctional features. The permeability and porosity of fiber reinforcements are two of the primary properties that control the flow of resin in fibers and are critical to numerical simulations of RTM. In the past, various permeability measurement methods have been developed in the literature. However, limitations still exist. Furthermore, porosity is often measured independently of permeability. As a result, the two measurements do not necessarily relate to the same entity, which may increase the time and labor costs associated with experiments and affect result interpretation. In this work, a measurement system was developed by fusing the signals from capacitive sensing and flow visualization, based on which a novel algorithm was developed. Without complicated sensor design or expensive instrumentation, both in-plane permeability and porosity can be simultaneously estimated. The feasibility of the proposed method was illustrated by experiments and verified with numerical simulations. MDPI 2022-06-29 /pmc/articles/PMC9269317/ /pubmed/35808697 http://dx.doi.org/10.3390/polym14132652 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Qi, Wei Chiu, Tzu-Heng Kao, Yi-Kai Yao, Yuan Chen, Yu-Ho Yang, Hsun Wang, Chen-Chieh Hsu, Chia-Hsiang Chang, Rong-Yeu Sensor Fusion for Simultaneous Estimation of In-Plane Permeability and Porosity of Fiber Reinforcement in Resin Transfer Molding |
title | Sensor Fusion for Simultaneous Estimation of In-Plane Permeability and Porosity of Fiber Reinforcement in Resin Transfer Molding |
title_full | Sensor Fusion for Simultaneous Estimation of In-Plane Permeability and Porosity of Fiber Reinforcement in Resin Transfer Molding |
title_fullStr | Sensor Fusion for Simultaneous Estimation of In-Plane Permeability and Porosity of Fiber Reinforcement in Resin Transfer Molding |
title_full_unstemmed | Sensor Fusion for Simultaneous Estimation of In-Plane Permeability and Porosity of Fiber Reinforcement in Resin Transfer Molding |
title_short | Sensor Fusion for Simultaneous Estimation of In-Plane Permeability and Porosity of Fiber Reinforcement in Resin Transfer Molding |
title_sort | sensor fusion for simultaneous estimation of in-plane permeability and porosity of fiber reinforcement in resin transfer molding |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9269317/ https://www.ncbi.nlm.nih.gov/pubmed/35808697 http://dx.doi.org/10.3390/polym14132652 |
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