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Title: Estimation of runway capacity at Changi Airport using AirTOp and Monte Carlo analysis
Authors: Dhir Varun
Keywords: DRNTU::Engineering::Aeronautical engineering
Issue Date: 2015
Source: Dhir Varun. (2015). Estimation of runway capacity at Changi Airport using AirTOp and Monte Carlo analysis. Master's thesis, Nanyang Technological University, Singapore.
Abstract: The issue of future capacity of Changi airport in Singapore is currently the subject of much debate. Runway occupancy time is an important control parameter in enhancing the use of current infrastructure to increase capacity of existing runways. Due to land availability constraints in Singapore the construction of new runways is also limited. The realistic estimates of the effects of capacity enhancement are desirable, but these estimates are difficult. This research estimates the runway occupancy time and maximum runway capacity at Changi airport using AirTOp simulation software and Monte Carlo analysis. A model of Changi airport was simulated using AirTOp simulator software. The evaluation of runway occupancy time and runway capacity was done based on the flight arrival/departure data captured for 6600 movements from the Changi airport group website. The study analyzes runway occupancy times and runway capacity under different traffic mix scenarios. It also takes into account the increase in capacity that can be achieved after construction of the third runway is over. The results of this study indicate that runway occupancy time is not only dependant on size of the aircraft but also the sequencing of traffic mix on the runway at any given point of time. Larger separation interval times are required by aircraft pairs with small aircraft in lead compared to other aircraft pairs. The research also illustrates that by scheduling and sequencing flights in a certain sequence an increase of up' to 27% in existing runway capacity may be achieved.
DOI: 10.32657/10356/65675
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:MAE Theses

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