| Autor: |
Guruprasad, Shreyas M., Greco, Gil Felix, Ring, Tobias P., Langer, Sabine C. |
| Předmět: |
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| Zdroj: |
INTER-NOISE & NOISE-CON Congress & Conference Proceedings; 2023, Vol. 265 Issue 2, p44-55, 12p |
| Abstrakt: |
The increased availability of air traffic data has enabled the application of data-driven approaches to support the simulation of noise contours around airports. Aiming at efficient aircraft noise simulations, this contribution proposes a framework for the probabilistic description of the air traffic around an airport. The methodology is based on flight trajectory clustering using the density-based algorithm OPTICS. The clustered trajectories serve as a basis for the creation of backbone and dispersion tracks, which, together with a prescribed number of flight operations per aircraft type, provide a probabilistic description of the air traffic to the noise simulations. A major focus is given to quantitatively assess the sensitivity of the OPTICS algorithm to different hyper-parameters to reduce the dimensionality of the problem. This framework is demonstrated utilizing a dataset of ADS-B flight trajectories associated with flights approaching the Hannover airport. Noise simulations based on the ECAC Doc. 29 best-practice method are conducted using the software SoundPLAN. A good agreement between noise contours is obtained when comparing simulations performed using the proposed framework and the full dataset while the computational time required is decreased. Furthermore, this approach identifies most of the trajectory patterns with the least amount of outliers. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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