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An estimation method for the fuel burn and other performance characteristics of civil transport aircraft during cruise: part 2, determining the aircraft’s characteristic parameters

Published online by Cambridge University Press:  02 December 2020

D.I.A. Poll Open the ORCID record for D.I.A. Poll [Opens in a new window]  and
U. Schumann
D.I.A. Poll*
Affiliation:
Emeritus Professor of Aerospace Engineering Cranfield University
U. Schumann
Affiliation:
Deutsches Zentrum für Luft- und Raumfahrt Institut für Physik der Atmosphäre Oberpaffenhofen Germany
*
[email protected]
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Abstract

A simple yet physically comprehensive and accurate method for the estimation of the cruise fuel burn rate of turbofan powered transport aircraft operating in a general atmosphere was developed in part 1. The method is built on previously published work showing that suitable normalisation reduces the governing relations to a set of near-universal curves. However, to apply the method to a specific aircraft, values must be assigned to six independent parameters and the more accurate these values are the more accurate the estimates will be. Unfortunately, some of these parameters rarely appear in the public domain. Consequently, a scheme for their estimation is developed herein using basic aerodynamic theory and data correlations. In addition, the basic method is extended to provide estimates for cruise lift-to-drag ratio, engine thrust and engine overall efficiency. This step requires the introduction of two more independent parameters, increasing the total number from six to eight. An error estimate and sensitivity analysis indicates that, in the aircraft’s normal operating range and using the present results, estimates of fuel burn rate are expected to be in error by no more than 5% in the majority of cases. Initial estimates of the characteristic parameters have been generated for 53 aircraft types and engine combinations and a table is provided.

Keywords

Optimum fuel burnMinimum fuel burnEnvironmental impactCruise emissionsMinimum fuel trajectoryAircraft characteristics
Type
Research Article
Information
The Aeronautical Journal , Volume 125 , Issue 1284 , February 2021 , pp. 296 - 340
Copyright
© The Author(s), 2020. Published by Cambridge University Press on behalf of Royal Aeronautical Society

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References

REFERENCES

Poll, D.I.A. On the relationship between non-optimum operations and fuel requirement for large civil transport aircraft with reference to environmental impact and contrail avoidance. The Aeronautical J., 2018, 122, (1258), pp 1827–1870.Google Scholar
Poll, D.I.A. and Schumann, U. An estimation method for the fuel burn and other performance characteristics of civil transport aircraft in the cruise Part 1 Fundamental quantities and governing relations for a general atmosphere. The Aeronautical J., 2020, 1–39. doi: 10.1017/aer.2020.62.Google Scholar
Schumann, U., Busen, R. and Plohr, M. Experimental test of the influence of propulsion efficiency on contrail formation, J. Aircr., 2000, 37, 1083–1087. doi: 10.2514/2.2715.CrossRefGoogle Scholar
Shevell, R.S. Fundamentals of Flight, 2nd ed, Prentice Hall International (UK), London, 1989, ISBN 0-13-339060-8.Google Scholar
EASA, Airbus A318-A319-A320-A321 Type-Certificate Data Sheet, TCDS A.064 Issue 02, European Aviation Safety Agency, June 2006.Google Scholar
Airbus, Aircraft characteristics for airport and maintenance planning. https://www.airbus.com/aircraft/support-services/airport-operations-and-technical-data/aircraft-characteristics.htmlGoogle Scholar
Jackson, P. Jane’s All the World’s Aircraft 2006/2007, 97th ed, Jane’s Information Group, 2006, ISBN 978-0710627452.Google Scholar
Daly, M. Jane’s Aero-Engines, 2nd ed, HIS, Markit, London, 2014, ISBN 978-0710630926.Google Scholar
EASA (2018). ICAO Engine Emissions Databank. https://www.easa.europa.eu/easa-and-you/environment/icao-aircraft-engine-emissions-databankGoogle Scholar
Jenkinson, L.R., Simpkin, P. and Rhodes, D. Civil Jet Aircraft Design, Arnold, 1999, ISBN 0 340 74152 XGoogle Scholar
Torenbeek, E. Synthesis of Subsonic Airplane Design, Kluwer Academic Press, 1988. ISBN 90 247 2724 3Google Scholar
Torenbeek, E. Advanced aircraft design – conceptual design, analysis and optimisation of subsonic civil airplanes, 2013, Chichester, West Sussex, UK: John Wiley and Sons, ISBN 9781119969303.Google Scholar
Obert, E. Aerodynamic Design of Transport Aircraft, Delft University Press, IOS, The Netherlands, 2009. ISBN 978-1-58603-970-7Google Scholar
Poll, D.I.A. Transition in the infinite swept attachment line boundary layer. The Aeronautical Quarterly, 1979, 30, pp 607–628.CrossRefGoogle Scholar
ICAO (1964), Manual of the ICAO Standard Atmosphere Rep., ICAO Document No. 7488, 2nd ed.Google Scholar
ESDU Subsonic lift-dependent drag due to the trailing vortex wake for wings without camber of twist. Engineering Sciences Data Unit Item 74035, October 1974 (amended April 1996).Google Scholar
McLean, D. Understanding Aerodynamics arguing from the real physics, Wiley, Chichester, UK, 2013, 978-1-119-96751-4Google Scholar
Shevell, R.S. and Bayan, F.P. Development of a method for predicting the drag divergence Mach number and the drag due to compressibility for conventional and supercritical wings. SUDAAR 552 (NASA Ames Research Center Grant Number NAG 2-18), Department of Aeronautics and Astronautics, Stanford University, July 1980.Google Scholar
Cumpsty, N.A. and Heyes, A.L. Jet Propulsion. Cambridge University Press, 3rd ed, 2015, ISBN 978-1-107-51122-4.Google Scholar
ESDU Approximate methods for estimation of cruise range and endurance: aeroplanes with turbo-jet and turbo-fan engines. Engineering Sciences Data Unit Item 73019, October 1973 (amended May 1982).Google Scholar
Martinez-Val, R., Palacin, J.F. and Perez, E. The evolution of jet airliners explained through the range equation. Aerospace Engineering, Proc. IMechE., 2008, 222, pp 915–919.CrossRefGoogle Scholar
Randle, W.E., Hall, C.A. and Vera-Morales, M. Improved range equation based on aircraft data. J. Aircr., 2011, 48, (4), pp 1291–1298.Google Scholar
Airbus Getting to grips with aircraft performance. Airbus Customer Services, Toulouse, France, January 2002.Google Scholar
Nelder, J.A. and Mead, R. A simplex method for function minimization. Computer J., 1965, 7, pp 308–313.Google Scholar
Schumann, U., Mayer, B., Graf, K. and Mannstein, H. A parametric radiative forcing model for contrail cirrus, J. Appl. Meteorol. Clim., 2012, 51, 1391–1406, doi: 10.1175/JAMC-D-11-0242.1.Google Scholar