Statistical model for gas turbine engines exhaust emissions
A statistical analysis has been developed from the International Civil Aviation Organization (ICAO) databank to predict aero-engines exhaust emissions during a landing and take-off cycle (LTO). The ICAO databank contains updated emission indices for a vast number of turbojet and turbofan engines only, with thrust ratings greater than 26.7 kN. Correlations are developed and proposed for turboprop and turboshaft engines to overcome the difficulty of assessing exhaust emissions from these engines in absence of industry data. LTO emissions are predicted for a turbofan-powered commuter airplane (Embraer E195) using the surrogate model. It is demonstrated that the predictions are closer to the values extracted from the flight data recorder than to the emissions calculated with the ICAO method. Thus, approximate emissions indices applied to actual flight procedures are a better choice than a standard ICAO LTO emission estimate from the databank. The correlations are then applied to the prediction of LTO emissions of a turboprop airplane (Bombardier Q400).
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/13619209
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Supplemental Notes:
- Abstract reprinted with permission of Elsevier.
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Authors:
- Filippone, Antonio
- Bojdo, Nicholas
- Publication Date: 2018-3
Language
- English
Media Info
- Media Type: Web
- Features: Appendices; Figures; References; Tables;
- Pagination: pp 451-463
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Serial:
- Transportation Research Part D: Transport and Environment
- Volume: 59
- Publisher: Elsevier
- ISSN: 1361-9209
- Serial URL: http://www.sciencedirect.com/science/journal/13619209
Subject/Index Terms
- TRT Terms: Aircraft; Exhaust gases; Landing; Mathematical models; Statistical analysis; Takeoff; Turbine engines; Turboprop aircraft
- Subject Areas: Aviation; Environment; Operations and Traffic Management; Vehicles and Equipment;
Filing Info
- Accession Number: 01665851
- Record Type: Publication
- Files: TRIS
- Created Date: Apr 11 2018 11:37AM