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Icing Condition Predictions Using FBGS
Icing is a hazard which is important for the aerospace industry and which has grown over the last few years. Developing sensors that can detect the existence not only of standard icing conditions with typically small droplet size, but also of Supercooled Large Droplet (SLD) conditions is one of the...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8473373/ https://www.ncbi.nlm.nih.gov/pubmed/34577259 http://dx.doi.org/10.3390/s21186053 |
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author | González del Val, Miguel Mora Nogués, Julio García Gallego, Paloma Frövel, Malte |
author_facet | González del Val, Miguel Mora Nogués, Julio García Gallego, Paloma Frövel, Malte |
author_sort | González del Val, Miguel |
collection | PubMed |
description | Icing is a hazard which is important for the aerospace industry and which has grown over the last few years. Developing sensors that can detect the existence not only of standard icing conditions with typically small droplet size, but also of Supercooled Large Droplet (SLD) conditions is one of the most important aims in order to minimize icing hazards in the near future. In the present paper a study of the Fiber Bragg Grating Sensors’ (FBGSs) performance as a flight icing detection system that predicts the conditions of an icing cloud is carried out. The test matrix was performed in the INTA Icing Wind Tunnel (IWT) with several icing conditions including SLD. Two optic fibers with 16 FBGS in total were integrated in the lower and upper surface of an airfoil to measure the temperature all over the chord. The results are compared with a Messinger heat and mass balance model and the measurements of the FBGS are used to predict the Liquid Water Content (LWC) and Ice Accretion Rate (IAR). Finally, the results are evaluated and a sensor assessment is made. A good correlation was observed between theoretical calculations and test results obtained with the FBGS in the IWT tests. FBGS proved to detect the beginning and end of ice accretion, LWC and IAR quickly and with good precision. |
format | Online Article Text |
id | pubmed-8473373 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-84733732021-09-28 Icing Condition Predictions Using FBGS González del Val, Miguel Mora Nogués, Julio García Gallego, Paloma Frövel, Malte Sensors (Basel) Article Icing is a hazard which is important for the aerospace industry and which has grown over the last few years. Developing sensors that can detect the existence not only of standard icing conditions with typically small droplet size, but also of Supercooled Large Droplet (SLD) conditions is one of the most important aims in order to minimize icing hazards in the near future. In the present paper a study of the Fiber Bragg Grating Sensors’ (FBGSs) performance as a flight icing detection system that predicts the conditions of an icing cloud is carried out. The test matrix was performed in the INTA Icing Wind Tunnel (IWT) with several icing conditions including SLD. Two optic fibers with 16 FBGS in total were integrated in the lower and upper surface of an airfoil to measure the temperature all over the chord. The results are compared with a Messinger heat and mass balance model and the measurements of the FBGS are used to predict the Liquid Water Content (LWC) and Ice Accretion Rate (IAR). Finally, the results are evaluated and a sensor assessment is made. A good correlation was observed between theoretical calculations and test results obtained with the FBGS in the IWT tests. FBGS proved to detect the beginning and end of ice accretion, LWC and IAR quickly and with good precision. MDPI 2021-09-09 /pmc/articles/PMC8473373/ /pubmed/34577259 http://dx.doi.org/10.3390/s21186053 Text en © 2021 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 González del Val, Miguel Mora Nogués, Julio García Gallego, Paloma Frövel, Malte Icing Condition Predictions Using FBGS |
title | Icing Condition Predictions Using FBGS |
title_full | Icing Condition Predictions Using FBGS |
title_fullStr | Icing Condition Predictions Using FBGS |
title_full_unstemmed | Icing Condition Predictions Using FBGS |
title_short | Icing Condition Predictions Using FBGS |
title_sort | icing condition predictions using fbgs |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8473373/ https://www.ncbi.nlm.nih.gov/pubmed/34577259 http://dx.doi.org/10.3390/s21186053 |
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