Governed by: Ministry of Industry and Information Technology of the People's Republic of China
Sponsored by: Northwestern Polytechnical University  Chinese Society Aeronautics and Astronautics
Address: Aviation Building,Youyi Campus, Northwestern Polytechnical University
A model clustering method suitable for approach wake separation reduction
Author:
Affiliation:

1.College of Civil Aviation,Nanjing University of Aeronautics and Astronautics;2.Nanjing University of Aeronautics and Astronautics,College of Civil Aviation

Clc Number:

V328;V355

Fund Project:

Nanjing University of Aeronautics and Astronautics Graduate Innovation Base (Laboratory) Open Funding

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    Abstract:

    At present, the standard of wake separation widely used in China is too conservative, which leads to the limitation of runway capacity. This article takes the approach aircraft wake encounter problem as the research object. On the one hand, it studies the approach wake safety separation reduction method to obtain the reduced critical wake separation. On the other hand, based on the PCA method to reduce the dimensionality of the aircraft performance data in the BADA database, a model hierarchical clustering method suitable for approach wake separation reduction is proposed. According to this method, new model classification results are obtained and constructed Reduced wake safety separation standards. The simulation results show that the model classification method used in this paper has good consistency with the mainstream classification methods at home and abroad, among the mainstream paired aircraft types at Huanghua International Airport, and the approach wake separation standard obtained in this paper can be reduced by more than 0.8km compared with the traditional wake separation standard.

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Jing-yu Zhang, Bao-hua Sang, tian yong. A model clustering method suitable for approach wake separation reduction[J]. Advances in Aeronautical Science and Engineering,2021,12(4):52-58

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History
  • Received:October 22,2020
  • Revised:November 26,2020
  • Adopted:December 07,2020
  • Online: August 26,2021
  • Published: