Abstract
In the effort to increase economic and environmental sustainability of the airport system; longitudinal spacing of aircraft approaching a runway has been identified as a major obstacle for runway efficiency. As demand approaches capacity at main hub airports, research efforts have focused on safely reducing current aircraft separations, which are considered a bottleneck in the effort to increase the utilization of existing airport facilities. This research uses modelling and computational algorithms to demonstrate the potential for aircraft separation reductions based on discrete scenarios comprising environmental conditions, aircraft-dependent parameters, and aircraft operational capabilities. Results from this research show that separation reductions can be obtained for aircraft such as the A320 and E170, corresponding to groups D and E in RECAT I. This results in single runway airport efficiency increase and gains are further translated into reductions of emission and fossil fuel.
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Acknowledgments
This research has been made possible thanks to the research contributions of the Federal Aviation Administration Wake Program, National Aeronautics and Space Administration (NASA) wake program, EUROCONTROL, Japan Aerospace Exploration Agency, WakeNet meeting members, MIT Lincoln Laboratory, and private industry research labs such as the MITRE Corporation.
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The contents of this material reflect the views of the author only. Neither the Federal Aviation Administration nor the United States Department of Transportation nor National Aeronautics and Space Administration nor Virginia Tech. Virginia Tech does not make any warranty or guarantee, or promise, expressed or implied, concerning the content or accuracy of the views expressed herein.
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Roa, J., Hu, J. (2019). Modelling of Runway Infrastructure Operations in an Effort to Increase Economic and Environmental Sustainable Development. In: Charytonowicz, J., Falcão, C. (eds) Advances in Human Factors, Sustainable Urban Planning and Infrastructure. AHFE 2018. Advances in Intelligent Systems and Computing, vol 788. Springer, Cham. https://doi.org/10.1007/978-3-319-94199-8_9
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DOI: https://doi.org/10.1007/978-3-319-94199-8_9
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