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Virginia Tech

Neural network aided aviation fuel consumption modeling

Abstract

dc:description.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 pilot's 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.

Degree

thesis:*
Name thesis:degree_name
Master of Science
Level thesis:degree_level
masters
Discipline thesis:degree_discipline
Civil Engineering
Department dc:contributor.department
Civil Engineering
Grantor dc:publisher
Virginia Tech
Year dc:date.issued
1997

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Cheung, Wing Ho
Chair dc:contributor.committeechair
  • Trani, Antoino A.
Committee members dc:contributor.committeemember
  • Drew, David R.
  • Greene, Richard G.

Subjects

dc:subject × 3

Rights

dc:rights
Statement dc:rights
  • In Copyright

Identifiers

dc:identifier.*
Dc Identifier Other
etd-82597-205125
OAI identifier oai:identifier
oai:vtechworks.lib.vt.edu:10919/36998

Chain of custody

source
Harvested from
Virginia Tech
Base URL
vtechworks.lib.vt.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Cheung, Wing Ho. Neural network aided aviation fuel consumption modeling. masters thesis, Virginia Tech, 1997. http://hdl.handle.net/10919/36998