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SITRAER Proceedings · XX SITRAER 2023

SITRAER Proceedings – XX SITRAER (2023)

Paper award · Best Paper – 1st Place

Obtenção da orientação de pista de pouso e decolagem por modelagem de anemograma em linguagem Python

  • Antônio Carlos Hanig
  • John Heberty de Freitas
  • Michelle Carvalho Galvão da Silva Pinto Bandeira
  • João Paulo Silva Lima

Universidade Federal de Goiás, Faculdade de Ciências e Tecnologia, Curso de Engenharia de · Transportes

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Event
XX SITRAER – Joinville, SC, Brasil, October 18–20, 2023
Volume
Proceedings of XX SITRAER – Air Transportation Symposium · ISSN 2448-1912
Pages
431–442
Publisher
Universidade Federal de Santa Catarina (UFSC)
Editors
Renata Cavion, Rafael Gigena Cuenca

Abstract

This paper seeks to present a methodology that can contribute to the effectiveness of the operation of new airport projects, focusing on the analysis and studies of winds on the runway and airport takeoff. A methodological proposal is presented, which consists of collecting wind data in existing airports, which historically have a high crosswind index, in order to present non-conformities in the standard models applied and/ or estimated a priori. To validate the study, three Brazilian airports are evaluated: Guarulhos International Airport - São Paulo/SP, Guararapes International Airport - Recife/PE and Barreiras/Bahia Regional Airport. Through the modeling of Anemogram using the Python language, it is possible to analyze the orientation of runway landing and takeoff. We used the analysis of four probability distribution curves for the winds at the proposed sites, the distribution GEV - Generalized Extreme Value Distribution, Log-normal, Weibull and Gumbel, to identify which or which would be the best choice of probability distribution that can more assertively describe the behavior of the winds in that place, and serve to assist in predicting future undesirable events in landing and takeoff operations, Seeking to improve operational and safety in air transport. The results show that the Weibull distribution is the one that best fits the wind data at Guarulhos Airport. The Lognormal distribution is the most suitable for wind data at Recife Airport; and the Gumbel distribution is the one that best fits the wind data at Barreiras Airport. These results are important because they allow more accurate wind forecasts to be made at each airport, which can help improve the operability and safety of aeronautical operations. In addition, choosing the correct probability distribution can help prevent future undesirable events such as aviation accidents and incidents. However, it is important to emphasize that the choice of the correct probability distribution depends on the particularities of each location and the data collected. Therefore, it is necessary to perform a careful analysis of wind data at each airport before choosing the most appropriate probability distribution.

Keywords: Airport; Wind; Anemogram; Runway Orientation; Python

How to cite

ABNT

HANIG, Antônio Carlos; FREITAS, John Heberty de; BANDEIRA, Michelle Carvalho Galvão da Silva Pinto; LIMA, João Paulo Silva. Obtenção da orientação de pista de pouso e decolagem por modelagem de anemograma em linguagem Python. In: SIMPÓSIO DE TRANSPORTE AÉREO, 20., 2023, Joinville. Anais [...]. Joinville: UFSC, 2023. p. 431-442. ISSN 2448-1912. Disponível em: https://sitraer-sbta.org/anais-2023-sit2327.html.

APA

Hanig, A. C., Freitas, J. H., Bandeira, M. C. G. S. P., & Lima, J. P. S. (2023). Obtenção da orientação de pista de pouso e decolagem por modelagem de anemograma em linguagem Python. In R. Cavion, & R. G. Cuenca (Eds.), Proceedings of XX SITRAER – Air Transportation Symposium (pp. 431–442). UFSC. https://sitraer-sbta.org/anais-2023-sit2327.html

BibTeX
@inproceedings{hanig2023obtencao,
  author = {Hanig, Antônio Carlos and Freitas, John Heberty de and Bandeira, Michelle Carvalho Galvão da Silva Pinto and Lima, João Paulo Silva},
  title = {{Obtenção da orientação de pista de pouso e decolagem por modelagem de anemograma em linguagem Python}},
  booktitle = {Proceedings of XX SITRAER – Air Transportation Symposium},
  editor = {Cavion, Renata and Cuenca, Rafael Gigena},
  pages = {431--442},
  year = {2023},
  address = {Joinville, SC, Brasil},
  publisher = {Universidade Federal de Santa Catarina (UFSC)},
  issn = {2448-1912},
  url = {https://sitraer-sbta.org/anais-2023-sit2327.html}
}