Low-level turbulence risk assessment and visualization using temporal rate of change of headwind of an aircraft


연구 분야: Verification



학회: Journal of Big Data


초록

In this study, we focused on the temporal rate of change of headwind, which is one of the recorded parameters in the aircraft’s in-flight quick access recorder data. We selected the Laplace distribution and utilized the scaling parameter to construct a low-level turbulence risk assessment model. Using this model, we calculated the risk of low-level turbulence occurrence at five airports in Japan based on the month, time of day, and wind speed. We visualized how the geographical conditions at each airport influenced risk in relation to airport wind speeds. We developed a low-level turbulence visualization site linked to weather conditions using these results to enable pilots to easily verify low-level turbulence risk and incorporate this information into their flight routines. These findings are anticipated to significantly enhance aircraft safety.


Author Profile
Koji Ito

College of Aviation Management J. F. Oberlin University 2-31-1 Ochiai Tama Tokyo 206-0033 Japan

Japan
Author Profile
Haruka Ohba

Faculty of Health Data Science Juntendo University 6-8-1 Hinode Urayasu Chiba 279-0013 Japan

Japan
Author Profile
Shinya Mizuno

Faculty of Health Data Science Juntendo University 6-8-1 Hinode Urayasu Chiba 279-0013 Japan

Japan

📄 논문 정보

발행 연도 2024년
인용수 0
출판 국가 Japan
사이트 Springer
좋아요 수 0

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