Assessment methodology for wet runway surface conditions

Autor: Bouteldja, Mohamed, GERTHOFFERT, Jonathan, CEREZO, Veronique, GARNIER DE BOISGROLLIER, Jérôme, BELON, Sébastien
Přispěvatelé: Centre d'Etudes et d'Expertise sur les Risques, l'Environnement, la Mobilité et l'Aménagement - Direction Centre-Est (Cerema Direction Centre-Est), Centre d'Etudes et d'Expertise sur les Risques, l'Environnement, la Mobilité et l'Aménagement (Cerema), Environnement, Aménagement, Sécurité et Eco-conception (IFSTTAR/AME/EASE), PRES Université Nantes Angers Le Mans (UNAM)-Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR), ADL, parent, Cadic, Ifsttar
Jazyk: angličtina
Rok vydání: 2018
Předmět:
Zdroj: 8th Symposium on Pavement Surface Characteristics: SURF 2018-Vehicle to Road Connectivity
8th Symposium on Pavement Surface Characteristics: SURF 2018-Vehicle to Road Connectivity, May 2018, BRISBANE, Australia
Popis: 8th Symposium on Pavement Surface Characteristics: SURF 2018 - Vehicle to Road Connectivity, BRISBANE, AUSTRALIE, 02-/05/2018 - 04/05/2018; The presence of water on runway significantly affects aircraft safety on ground and runway friction. Under such conditions, pilots have to be informed of runway surface conditions to assess required landing distances. This assessment is based on runway surface characteristics (design, construction and maintenance), water depth and water-covered surface (operational conditions). However, estimation of water depth and water-covered surface may be tricky due to the lack of tools and methods, and to the rapid changing conditions during rainfall. This paper presents a method and its related tool, called OPHELIA for runway condition monitoring. A road model has been adapted to model water flows on a runway from its geometrical and surface characteristics, and to predict water depth during rainy events. An experimentation held on one of the two runways of Lyon airport is performed to validate OPHELIA tool and the water depth estimation. It is concluded that the model provides good results of the water depth estimation, compared to those measured by Vaisala sensor and it allows in the meanwhile the detection of water accumulation area on the runway.
Databáze: OpenAIRE
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