scholarly journals Recognition of Aircraft Wake Vortex Based on Random Forest

IEEE Access ◽  
2022 ◽  
pp. 1-1
Author(s):  
Weijun Pan ◽  
Haoran Yin ◽  
Yuanfei Leng ◽  
Xiaolei Zhang
Keyword(s):  
Random Forest ◽  
Wake Vortex ◽  
Aircraft Wake

Study on the influence of linear and nonlinear distribution of crosswind on the motion of aircraft wake vortex

2021 ◽  
pp. 095441002098743
Author(s):  
Dong Li ◽  
Ziming Xu ◽  
Ke Zhang ◽  
Zeyu Zhang ◽  
Jinxin Zhou ◽  
...  
Keyword(s):  
Numerical Simulations ◽  
Dissipation Rate ◽  
Vortex Pair ◽  
Vertical Shear ◽  
Wake Vortex ◽  
Analysis Method ◽  
Velocity Magnitude ◽  
Aircraft Wake ◽  
Linear And Nonlinear ◽  
Nonlinear Distribution

Environmental crosswind can greatly affect the development of aircraft wake vortex pair. Previous numerical simulations and experiments have shown that the nonlinear vertical shear of the crosswind velocity can affect the dissipation rate of the aircraft wake vortex, causing each vortex of the vortex pair descent with different velocity magnitude, which will lead to the asymmetrical settlement and tilt of the wake vortex pair. Through numerical simulations, this article finds that uniform crosswind convection and linear vertical shear crosswind convection can also have an effect on the strength of the vortex. This effect is inversely proportional to the cube of the vortex spacing, so it is more intense on small separation vortex pair. In addition, the superposition of crosswind and vortex-induced velocities will lead to the asymmetrical pressure distribution around the vortex pair, which will also cause the tilt of the vortex pair. Furthermore, a new analysis method for wake vortex is proposed, which can be used to predict the vortex trajectory.

Analysis of Predicted Aircraft Wake Vortex Transport and Comparison with Experiment

1975 ◽  
Vol 12 (7) ◽  
pp. 619-620
Author(s):  
M. R. Brashears ◽  
James N. Hallock
Keyword(s):  
Wake Vortex ◽  
Comparison With Experiment ◽  
Aircraft Wake

Modeling the Radar Signature of Raindrops in Aircraft Wake Vortices

2013 ◽  
Vol 30 (3) ◽  
pp. 470-484 ◽  
Author(s):  
Zhongxun Liu ◽  
Nicolas Jeannin ◽  
Francois Vincent ◽  
Xuesong Wang
Keyword(s):  
Traffic Control ◽  
Vortex Flow ◽  
Doppler Radar ◽  
Elevation Angle ◽  
Wake Vortex ◽  
Wake Vortices ◽  
Radar Signature ◽  
Radar Echo ◽  
Aircraft Wake ◽  
Resolution Cell

Abstract The present work is dedicated to the modeling and simulation of the radar signature of raindrops within wake vortices. This is achieved through the computation of the equation of raindrop motion within the wake vortex flow. Based on the inhomogeneous distribution of raindrops within wake vortices, the radar echo model is computed for raindrops in a given resolution cell. Simulated Doppler radar signatures of raindrops within wake vortices are shown to be a potential criterion for identifying wake vortex hazards in air traffic control. The dependence of the radar signature on various parameters, including the radial resolution and antenna elevation angle, is also analyzed.

scholarly journals Identification of Aircraft Wake Vortex Based on SVM

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Weijun Pan ◽  
Zhengyuan Wu ◽  
Xiaolei Zhang
Keyword(s):  
Environmental Parameters ◽  
Classification Model ◽  
Support Vector ◽  
Wake Vortex ◽  
Doppler Lidar ◽  
Pulsed Doppler ◽  
Wind Fields ◽  
Wake Turbulence ◽  
Aircraft Wake ◽  
Separation Standards

The aircraft wake vortex has important influence on the operation of the airspace utilization ratio. Particularly, the identification of aircraft wake vortex using the pulsed Doppler lidar characteristics provides a new knowledge of wake turbulence separation standards. This paper develops an efficient pattern recognition-based method for identifying the aircraft wake vortex measured with the pulsed Doppler lidar. The proposed method is outlined in two stages. (i) First, a classification model based on support vector machine (SVM) is introduced to extract the radial velocity features in the wind fields by combining the environmental parameters. (ii) Then, grid search and cross-validation based on soft margin SVM with kernel tricks are employed to identify the aircraft wake vortex, using the test dataset. The dataset includes wake vortices of various aircrafts collected at the Chengdu Shuangliu International Airport from Aug 16, 2018, to Oct 10, 2018. The experimental results on dataset show that the proposed method can identify the aircraft wake vortex with only a small loss, which ensures the satisfactory robustness in detection performance.

scholarly journals Deep Learning for Aircraft Wake Vortex Identification

2019 ◽  
Vol 685 ◽  
pp. 012015
Author(s):  
Pan Weijun ◽  
Duan Yingjie ◽  
Zhang Qiang ◽  
Tang Jiahao ◽  
Zhou Jun
Keyword(s):  
Deep Learning ◽  
Wake Vortex ◽  
Vortex Identification ◽  
Aircraft Wake

scholarly journals Ultrasonic Method for Aircraft Wake Vortex Detection

2007 ◽  
Vol 44 (3) ◽  
pp. 726-732 ◽  
Author(s):  
Rebecca J. Rodenhiser ◽  
William W. Durgin ◽  
Hamid Johari
Keyword(s):  
Ultrasonic Method ◽  
Wake Vortex ◽  
Aircraft Wake ◽  
Vortex Detection

scholarly journals Review of Idealized Aircraft Wake Vortex Models

2014 ◽  
Author(s):  
Nashat N. Ahmad ◽  
Fred Proctor
Keyword(s):  
Wake Vortex ◽  
Aircraft Wake

Measurements of aircraft wake vortex parameters by a Stream Line Doppler lidar

2017 ◽  
Vol 30 (6) ◽  
pp. 588-595 ◽  
Author(s):  
I. N. Smalikho ◽  
V. A. Banakh ◽  
A. V. Falits
Keyword(s):  
Stream Line ◽  
Wake Vortex ◽  
Doppler Lidar ◽  
Aircraft Wake
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