Scholarly
    Communications Project


Document Type:Master's Thesis
Name:Wing Ho Cheung
Email address:fwc@mail.vt.edu
URN:1997/00236
Title:Neural network aided aviation fuel consumption modeling
Degree:Master of Science
Department:Civil engineering
Committee Chair: Dr. Antonio Trani
Chair's email:vuela@mail.vt.edu
Committee Members:Dr. R.G. Greene
Dr. D.R. Drew
Keywords:neural network, fuel consumption, aviation
Date of defense:August 25, 1997
Availability:Release the entire work immediately worldwide.

Abstract:

This thesis deals with the potential application of neural network technology to aviation fuel consumption estimation. This is achieved by developing neural networks representative jet aircraft. Fuel consumption information obtained directly from the pilotís flight manual was trained by the neural network. The trained network was able to accurately and efficiently estimate fuel consumption of an aircraft for a given mission. Statistical analysis was conducted to test the reliability of this model for all segments of flight. Since the neural network model does not require any wind tunnel testing nor extensive aircraft analysis, compared to existing models used in aviation simulation programs, this model shows good potential. The design of the model is described in depth, and the MATLAB source code are included in appendices.

List of Attached Files

Thesis.PDF


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