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International Journal of Turbo & Jet-Engines

Ed. by Sherbaum, Valery / Erenburg, Vladimir


IMPACT FACTOR 2018: 0.863

CiteScore 2018: 0.66

SCImago Journal Rank (SJR) 2018: 0.211
Source Normalized Impact per Paper (SNIP) 2018: 0.625

Online
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2191-0332
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Volume 36, Issue 2

Issues

Predicting Lean Blowout and Emissions of Aircraft Engine Combustion Chamber Based on CRN

Yinli Xiao
  • Corresponding author
  • School of Engine and Energy, Northwestern Polytechnical University, Xi’an, Shaanxi 710072, People’s Republic of China
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/ Zhengxin Lai
  • School of Engine and Energy, Northwestern Polytechnical University, Xi’an, Shaanxi 710072, People’s Republic of China
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/ Zupeng Wang
  • School of Engine and Energy, Northwestern Polytechnical University, Xi’an, Shaanxi 710072, People’s Republic of China
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/ Kefei Chen
  • School of Engine and Energy, Northwestern Polytechnical University, Xi’an, Shaanxi 710072, People’s Republic of China
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Published Online: 2018-03-01 | DOI: https://doi.org/10.1515/tjj-2017-0063

Abstract

To predict the pollutant emissions and lean blowout, chemical reactor network (CRN) model is applied to the modern aircraft engine combustion chamber. In this study, the CRN which represent the major features of aerodynamics and combustion in the combustion chamber is set up based on the OpenFOAM simulation results. The boundary and the initial conditions used for the CRN derive from the operating modes of typical aircraft engine cycle. A 21 species 30 steps chemical mechanism of kerosene is employed in the CRN method. The levels of pollutant emissions are obtained under four ICAO engine power settings of idle, approach climb and take off. The lean blowout equivalent ratio is evaluated at the idle power setting. The results will be helpful to predict the aircraft engine exhaust emissions and lean blowout (LBO).

Keywords: combustion chamber; emissions; chemical reactor network; lean blowout; OpenFOAM

PACS: Classification (82.33.Vx)

References

  • 1.

    Lefebvre AH, Ballal DR. Gas turbine combustion: alternative fuels and emissions. 3rd ed. CRC Press, Taylor & Francis Group: Florida. 2010.Google Scholar

  • 2.

    Wang H, Lei F, Shao W, Zhang Z, Liu Y, Xiao Y, et al. Experimental and numerical studies of pressure effects on syngas combustor emissions. Appl Thermal Eng. 2016;102:318–28.CrossrefWeb of ScienceGoogle Scholar

  • 3.

    Leong CC, Blakey S, Wilson CW. Genetic algorithm optimised chemical reactors network: a novel technique for alternative fuels emission prediction. Swarm Evol Comput. 2016;27:180–87.CrossrefWeb of ScienceGoogle Scholar

  • 4.

    Sturgess G, Shouse DT. A hybrid model for calculating lean blow-outs in practical combustors. 32nd AIAA/ASME/SAEE Joint Propulsion Conference. July 1–3, 1996/Lake Buena Vista, FL. AIAA paper. 1996:96–3125.Google Scholar

  • 5.

    Levy Y, Gany A, Goldman Y, Erenburg V, Sherbaum V, Ovcharenko V, Rosentsvit L, et al. Increasing operational stability in low NOx GT combustor by a pilot flame. Proceeding of ASME Turbo Expo 2010: Power for Land, Sea and Air 14–18 June 2010, Glasgow, UK GT2010-22785.Google Scholar

  • 6.

    Lee D, Park J, Jin J, Lee M. A simulation for prediction of nitrogen oxide emissions in lean premixed combustor. J Mech Sci Technol. 2011;25(7):1871–8.CrossrefWeb of ScienceGoogle Scholar

  • 7.

    Fichet V, Kanniche M, Plion P, Gicquel O. A reactor network model for predicting nox emissions in gas turbines. Fuel. 2010;89:2202–10.Web of ScienceCrossrefGoogle Scholar

  • 8.

    Novosselov IV, Malte P, Yuan S, Srinivasan R, Lee J. Chemical reactor network application to emissions prediction for industrial DLE gas turbine. Proceeding of ASME Turbo Expo, GT2006-90282, Barcelona, Spain, 2006.Google Scholar

  • 9.

    Novosselov IV, Malte P. Development and application of an eight-step global mechanism for CFD and CRN simulations of lean-premixed combustors. Proceedings of ASME Turbo Expo, GT 2007-27990.Google Scholar

  • 10.

    Denney RK, Tai JC, Mavris DN. Emissions prediction for aircraft conceptual design. 48th AIAA/ASME/SAE/ASEE Joint Propulsion Conference & Exhibit 30 July–01 August 2012, Atlanta, Georgia. AIAA paper 2012-4273.Google Scholar

  • 11.

    Rezvani R, Denny RK, Mavris DN. A design-oriented semi-analytical emissions prediction method for gas turbine combustors. 47th AIAA Aerospace Sciences Meeting Including The New Horizons Forum and Aerospace Exposition. AIAA paper 2009-704.Google Scholar

  • 12.

    Allaire DL, Waitz IA, Willcox KE. A comparison of two methods for predicting emissions from aircraft gas turbine combustors. Proceedings of ASME Turbo Expo, GT2007-28346.Google Scholar

  • 13.

    Cantera documentation. Available at: http://www.cantera.org/docs/sphinx/html/index.html. Accessed: 2016.

  • 14.

    Müller H, Ferraro F, Pfitzner M. Implementation of a steady laminar flamelet model for nonpremixed combustion in LES and RANS simulations. 8th Internatioanal OpenFOAM Workshop. 11–14 Jun 2013, Jeju, Korea.Google Scholar

  • 15.

    Mattingly JD, Heiser WH, Pratt DT. Aircraft engine design. AIAA education series. 2002:336.Google Scholar

  • 16.

    Hsiao G, Mongia H Swirl cup modeling, part iII: grid independent solution with different turbulence models. AIAA-2003-1349, 2003.Google Scholar

  • 17.

    Xiao Y. Investigations on ethylene combustion in a scramjet combustor using resistance heaters. Proceedings of the Institution of Mechanical Engineers Part G Journal of Aerospace Engineering, 5 Jan 2008.Google Scholar

  • 18.

    Min C, Wenyan S, Yinli X, Chen M, Song W, Xiao Y, Chen L, et al. Optical measurement and characteristic analysis of aeroengine combustor primary zone with counter rotating swirler. J Aerosp Power China. 2013 Aug;28:1727–1735.Google Scholar

  • 19.

    Theory manual of Chemkin-Pro. Reaction design: San Diego. Sept 2008. Available at: www.pcimmesir.com/chemkin-pro-manual.pdf. Accessed: 2016.

  • 20.

    Xiaohua G. Aero gas turbine engine fuel nozzle technology. National Defense Industry Press. Beijing: China. ISBN 7-118-04153-X. April 2006:48.Google Scholar

  • 21.

    Turns SR. An introduction to combustion: concept and applications. 2nd ed. New York: McGraw-Hill, 1996:375.Google Scholar

  • 22.

    Charest MR. Design methodology for a lean premixed prevaporized can combustor. A thesis of Carleton University. Ottawa, Ontario. April 2005.Google Scholar

  • 23.

    Environmental Protection, Annex 16, No. 1993, Vol. II Aircraft Engine Emissions, Part III.Google Scholar

  • 24.

    Rezvani R. A conceptual methodology for the prediction of engine emissions. A Dissertation of PH.D, School of Aerospace. Georgia Institute of Technology. Dec 2010.Google Scholar

  • 25.

    Mishra RK, Ramanujam PS, Badrinath C, Bhat MN. Influence of operating pressure on the performance of an aero gas turbine combustor. XVII ISABE, Munich, Germany, 4–9 Sept 2005. ISABE-2005-1020.Google Scholar

  • 26.

    Mishra RK, Singh K. Effect of operating conditions on the emission characteristics of an annular combustor. J Aerosp Sci Technol. 2009 May;61(2):305–11.Google Scholar

  • 27.

    Yuzhen L, Quanhong X, Gaoen L. Gas turbine combustor. China: National defense industry press, May 2008:137.Google Scholar

About the article

Received: 2017-12-18

Accepted: 2018-02-01

Published Online: 2018-03-01

Published in Print: 2019-05-27


Citation Information: International Journal of Turbo & Jet-Engines, Volume 36, Issue 2, Pages 147–156, ISSN (Online) 2191-0332, ISSN (Print) 0334-0082, DOI: https://doi.org/10.1515/tjj-2017-0063.

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