Low-level turbulence risk assessment and visualization using temporal rate of change of headwind of an aircraft
Year: 2024
Type: article
Abstract: 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 visualization 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.
Source: Journal Of Big Data
Authors: Koji Ito, Haruka Ohba, Shinya Mizuno
Institutions: J. F. Oberlin University, Juntendo University
Language: English
Subfield: Aerospace Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,090
OpenAlex ID: W4404147569