Assessing the impact of the slopes on runway drainage capacity based on wheel/path surface adhesion conditions
Aircraft braking distance is dependent on the friction between the main gear tires and runway pavement surface.Pavement texture, which is divided into macrotexture and micro-texture, has a noticeable effect upon friction, especially when the surface is wet. A risk analysis framework is developed to study the effects of longitudinal and transverse slopes on the aircraft braking distance in wet runway conditions and their influences on the probability of landing overrun accidents.This framework is operating under various water-film thicknesses, Maximum Landing Weights (MLW), and touchdown speed probability distributions for an acceptable range of longitudinal/transverse slopes and pavement texture depths.A simulator code is developed that initially computes the existing water-film thickness, as the result of intense precipitation,under aircraft main gear (depend on aircraft category) and then applies this variable as one of the main inputs to the aircraft braking distance computation. According to the obtained results, longitudinal gradient does not have a significant effect on the existing water depth on the surface although it affects the flow path length. Furthermore, 1% to 1.5% transverse slope causes rapid drainage of water from the runway surface and considerably decreases the probability of runway excursion accidents.
This work is licensed under a Creative Commons Attribution 4.0 International License.
American Association of State Highway and Transportation Officials (AASHTO). (1990). A policy on geometric design of highways and streets. AASHTO.
American Meteorological Society. (2000). Rain. In Glossary of Meteorology. https://glossary.ametsoc.org/wiki/Rain
Barnes, T., DeFiore, T., & Micklos, R. (1998). Video landing parameter survey – Washington National Airport. Publication DOT/FAA/AR-97/106. FAA, U.S. Department of Transportation.
Chesterton, J., Nancekivell, N., & Tunnicliffe, N. (2006). The use of Gallaway equation for aquaplaning evaluation in New Zealand [Conference presentation]. NZIHT/Transit NZ 8th Annual Conference, New Zealand.
Eshel, A. A. (1967). Study of tires on a wet runway. Report No. RR67-24, Ampex Corporation, Redwood City, California.
European Aviation Safety Agency. (2017). CS-ADR-DSN. Certification Specifications and Guidance Material for Aerodromes Design. EASA.
FAA. (2012). AC 150/5300-13A. Airport design. United States Department of Transportation.
Gallaway, B. M., Ivey, D. L., Hayes, G., Ledbetter, W. B., Olson, R. M., Woods, D. L., & Schiller Jr, R. F. (1979). Pavement and geometric design criteria for minimizing hydroplaning. A technical summary, Final Report. Texas A&M University, College Station.
Grogger, H., & Weiss, M. (1996). Calculation of the three-dimensional free surface flow around an automobile tire. Tire Science Technology, 24(1), 39–49. https://doi.org/10.2346/1.2137511
Guven, O., & Melville, G. (1999). Pavement cross slope design – a technical review. Auburn university – Highway research center.
Hosang, V. A. (1975). Field survey and analysis of aircraft distribution on airport pavements. Report FAA-RD-74-36. FAA, U.S. Department of Transportation.
International Civil Aviation Organization (ICAO). (2002). ICAO Doc 9137-AN/898, Aircraft service manual, Part 2: Pavement Surface Conditions. ICAO Secretary General.
International Civil Aviation Organization (ICAO). (2013). Annex 14 to the Convention on International Civil Aviation: Aerodromes, volume I: Aerodrome Design and Operations. ICAO, Volume 1 (6th ed.). Quebec, Canada H3C 5H7.
Jayasooriya, W., & Gunaratne, M. (2014). Evaluation of widely used hydroplaning risk prediction methods using Florida’s past crash data. Transportation Research Record, 2457(1), 140–150. https://doi.org/10.3141/2457-15
Ketabdari, M., Giustozzi, F., & Crispino, M. (2018). Sensitivity analysis of influencing factors in probabilistic risk assessment for airports, Safety Science, 107, 173–187. https://doi.org/10.1016/j.ssci.2017.07.005
Ketabdari, M., Crispino, M., & Giustozzi, F. (2019). Probability contour map of landing overrun based on aircraft braking distance computation. In Pavement and Asset Management (pp. 731–740). CRC Press. https://doi.org/10.1201/9780429264702
Ketabdari, M., Toraldo, E., Crispino, M., & Lunkar, V. (2020a). Evaluating the interaction between engineered materials and aircraft tyres as arresting systems in landing overrun events. Case Studies in Construction Materials, 13(December 2020), e00446. https://doi.org/10.1016/j.cscm.2020.e00446
Ketabdari, M., Toraldo, E., & Crispino, M. (2020b). Numerical risk analyses of the impact of meteorological conditions on probability of airport runway excursion accidents. In International Conference on Computational Science and its Applications (pp. 177–190). Springer, Cham. https://doi.org/10.1007/978-3-030-58799-4_13
Li, S., Zhu, K. Q., Noureldin, S., & Kim, D. (2004). Pavement surface friction test using standard smooth tire: The Indiana experience. In Transportation Research Board 83rd Annual Meeting Compendium of Papers (CD-ROM). Transportation Research Board, Washington, D.C.
Luo, W., Wang, K. C., & Li, L. (2019). Field test validation of water film depth (WFD) prediction models for pavement surface drainage. International Journal of Pavement Engineering, 20(10), 1170–1181. https://doi.org/10.1080/10298436.2017.1394099
Monjo, R. (2016). Measure of rainfall time structure using the dimensionless n-index. Climate Research, 67(1), 71–86. https://doi.org/10.3354/cr01359
Okano, T., & Koishi, M. (2001). A new computational procedure to predict transient hydroplaning performance of a tire. Tire Science and Technology, 29(1), 2–22. https://doi.org/10.2346/1.2135228
Ong, G. P., & Fwa, T. F. (2007). Wet-pavement hydroplaning risk and skid resistance: modeling. Journal of Transportation Engineering, 133(10), 590–598. https://doi.org/10.1061/(ASCE)0733-947X(2007)133:10(590)
Pasindu, H. R., Fwa, T. F., & Ping Ong, G. (2011). Computation of aircraft braking distances. Transportation Research Record: Journal of the Transportation Research Board, 2214(1), 126–135. https://doi.org/10.3141/2214-16