Optimisation of changi airport's future air traffic contingency management in extreme haze condition
As world air traffic grows exponentially, Singapore Changi Airport has planned ahead and geared up for challenges in years to come. Despite being well equipped with all the sophisticated technologies, air traffic movements are still affected yearly by haze from the region. Such haze reduces...
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Format: | Final Year Project |
Language: | English |
Published: |
2014
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Online Access: | http://hdl.handle.net/10356/60041 |
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Institution: | Nanyang Technological University |
Language: | English |
Summary: | As world air traffic grows exponentially, Singapore Changi Airport has planned ahead and
geared up for challenges in years to come. Despite being well equipped with all the
sophisticated technologies, air traffic movements are still affected yearly by haze from the
region. Such haze reduces visibility and forces air traffic movements to slow down as part of
precautionary measures to ensure the best safety policies are practiced. Such slow air traffic
movements can easily cause congestion to the high volume of air traffic in the future.
This final year project explores various methods to optimise future flight movements that fly
in and out of Changi Airport during haze by using Microsoft Excel simulations. Two
optimisation models are created to reduce all departure and arrival aircrafts’ waiting time.
The first optimisation model addresses the problem by separating the flights by time evenly.
The second optimisation model tackles the problem by having an alternate land and take off
or a vice versa of the pattern.
In addition to support the optimisation models, Chapter 2 reviews the necessary literatures
such as flight statistics and wake turbulence in order to understand the various perimeters
needed in the study. To understand the future flight movements, a forecast is done in
Chapter 3 before using these figures in the optimisation model simulations. At the
conclusion, the pros and cons of both optimisation models are examined. |
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