Enkelmann et al., 2020 - Google Patents
Comparison of a physical model and a machine learning approach for a more accurate assessment of fuel efficiency measuresEnkelmann et al., 2020
View PDF- Document ID
- 13986347905359665304
- Author
- Enkelmann F
- Heigl R
- Pfingsten K
- Publication year
- Publication venue
- AIAA Scitech 2020 Forum
External Links
Snippet
The paper focuses on a more accurate quantification method of fuel efficiency measures which can be applied to commercial transport airplanes. These measures or modifications can for example affect the engine or aerodynamical efficiency. Full flight data of a …
- 239000000446 fuel 0 title abstract description 69
Classifications
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- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/50—Computer-aided design
- G06F17/5009—Computer-aided design using simulation
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T50/00—Aeronautics or air transport
- Y02T50/60—Efficient propulsion technologies
- Y02T50/67—Relevant aircraft propulsion technologies
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