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Icing Condition Predictions Using FBGS.
González Del Val, Miguel; Mora Nogués, Julio; García Gallego, Paloma; Frövel, Malte.
Afiliação
  • González Del Val M; Instituto Nacional de Técnica Aeroespacial (INTA), Crta. de Ajalvir km 4, 28850 Torrejón de Ardoz, Spain.
  • Mora Nogués J; Ingeniería de Sistemas para la Defensa de España S.A. (ISDEFE), C. de Beatriz de Bobadilla, 3, 28040 Madrid, Spain.
  • García Gallego P; Instituto Nacional de Técnica Aeroespacial (INTA), Crta. de Ajalvir km 4, 28850 Torrejón de Ardoz, Spain.
  • Frövel M; Escuela Internacional de Doctorado, Universidad Nacional de Educación a Distancia (UNED), Calle de Bravo Murillo, 38, 28015 Madrid, Spain.
Sensors (Basel) ; 21(18)2021 Sep 09.
Article em En | MEDLINE | ID: mdl-34577259
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.
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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article