Comprehensive Analysis on the Contribution of Winglets Fuel Based on Contrast Experiment

DOI

10.2991/ammsa-17.2017.57How to use a DOI?

Keywords

fuel consumption; winglet; statistical analysis; BP neural network

Abstract

Previous research has shown that aviation fuel costs are the first major cost of air operations, and it is a key factor in profit and loss. In the operating environment under the combined effects of many factors, regardless of operating costs breakeven only to calculate the critical point of save fuel is challenging. This paper is to build fuel consumption mode based on comparative experiments and based on statistical analysis and BP neural network analysis. The model considers the main influence parameters including flight time, payload and so on. The results show that the installation of the winglets under given actual payload and flight time makes the fuel consumption increase.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yueli Sun
AU  - Jingjie Chen
AU  - Jincheng Cui
AU  - Qi Meng
AU  - Ziheng Xing
PY  - 2017/05
DA  - 2017/05
TI  - Comprehensive Analysis on the Contribution of Winglets Fuel Based on Contrast Experiment
BT  - Proceedings of the 2017 International Conference on Applied Mathematics, Modelling and Statistics Application (AMMSA 2017)
PB  - Atlantis Press
SP  - 256
EP  - 260
SN  - 1951-6851
UR  - https://doi.org/10.2991/ammsa-17.2017.57
DO  - 10.2991/ammsa-17.2017.57
ID  - Sun2017/05
ER  -