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Modelling fuel injector spray characteristics in jet engines by using vine copulas

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  • Maximilian Coblenz
  • Simon Holz
  • Hans‐Jörg Bauer
  • Oliver Grothe
  • Rainer Koch

Abstract

The emission requirements for jet engines are becoming more stringent and the combustion process determines pollutant emissions. Therefore, we model the distribution of fuel drops generated by a fuel injector in a jet engine, which can be assumed to be a five‐dimensional problem in terms of drop size, x‐position, y‐position, x‐velocity and y‐velocity. The data are generated by numerical simulations of the fuel atomization process for several jet engine operating conditions. In combustion simulations, the variables are usually assumed to be independent at the start of the simulation, which is clearly not so as our data show. The dependence between some of the variables is non‐monotone and asymmetric, which makes the modelling task difficult. Our aim is to provide a realistic parametric model for the dependence structure. For this, we employ vine copulas which provide a flexible way to construct a multivariate distribution function. However, we need to use non‐standard bivariate copulas as building blocks. Using this copula representation enables us to create realistic samples of fuel spray droplets which improve the prediction of the combustion process and the pollutant emissions. Moreover, this approach is significantly faster than solving the set of differential equations describing fuel disintegration.

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  • Maximilian Coblenz & Simon Holz & Hans‐Jörg Bauer & Oliver Grothe & Rainer Koch, 2020. "Modelling fuel injector spray characteristics in jet engines by using vine copulas," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 69(4), pages 863-886, August.
  • Handle: RePEc:bla:jorssc:v:69:y:2020:i:4:p:863-886
    DOI: 10.1111/rssc.12421
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    1. Cornelia Savu & Mark Trede, 2010. "Hierarchies of Archimedean copulas," Quantitative Finance, Taylor & Francis Journals, vol. 10(3), pages 295-304.
    2. Dong Hwan Oh & Andrew J. Patton, 2017. "Modeling Dependence in High Dimensions With Factor Copulas," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(1), pages 139-154, January.
    3. Göran Kauermann & Christian Schellhase & David Ruppert, 2013. "Flexible Copula Density Estimation with Penalized Hierarchical B-splines," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 40(4), pages 685-705, December.
    4. Vuong, Quang H, 1989. "Likelihood Ratio Tests for Model Selection and Non-nested Hypotheses," Econometrica, Econometric Society, vol. 57(2), pages 307-333, March.
    5. Dißmann, J. & Brechmann, E.C. & Czado, C. & Kurowicka, D., 2013. "Selecting and estimating regular vine copulae and application to financial returns," Computational Statistics & Data Analysis, Elsevier, vol. 59(C), pages 52-69.
    6. Lorán Chollete & Andréas Heinen & Alfonso Valdesogo, 2009. "Modeling International Financial Returns with a Multivariate Regime-switching Copula," Journal of Financial Econometrics, Oxford University Press, vol. 7(4), pages 437-480, Fall.
    7. Simon Holz & Samuel Braun & Geoffroy Chaussonnet & Rainer Koch & Hans-Jörg Bauer, 2019. "Close Nozzle Spray Characteristics of a Prefilming Airblast Atomizer," Energies, MDPI, vol. 12(14), pages 1-22, July.
    8. Daniel Berg, 2009. "Copula goodness-of-fit testing: an overview and power comparison," The European Journal of Finance, Taylor & Francis Journals, vol. 15(7-8), pages 675-701.
    9. Tobias Eckernkemper, 2018. "Modeling Systemic Risk: Time-Varying Tail Dependence When Forecasting Marginal Expected Shortfall," Journal of Financial Econometrics, Oxford University Press, vol. 16(1), pages 63-117.
    10. Hofert, Marius, 2011. "Efficiently sampling nested Archimedean copulas," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 57-70, January.
    11. Holger Dette & Ria Van Hecke & Stanislav Volgushev, 2014. "Some Comments on Copula-Based Regression," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(507), pages 1319-1324, September.
    12. Luciana Dalla Valle & Fabrizio Leisen & Luca Rossini, 2018. "Bayesian non‐parametric conditional copula estimation of twin data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 67(3), pages 523-548, April.
    13. Noh, Hohsuk & El Ghouch, Anouar & Bouezmarni, Taoufik, 2013. "Copula-Based Regression Estimation and Inference," LIDAM Reprints ISBA 2013045, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    14. Andrew J. Patton, 2006. "Modelling Asymmetric Exchange Rate Dependence," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 47(2), pages 527-556, May.
    15. Hohsuk Noh & Anouar El Ghouch & Taoufik Bouezmarni, 2013. "Copula-Based Regression Estimation and Inference," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 108(502), pages 676-688, June.
    16. Grothe, Oliver & Hofert, Marius, 2015. "Construction and sampling of Archimedean and nested Archimedean Lévy copulas," Journal of Multivariate Analysis, Elsevier, vol. 138(C), pages 182-198.
    17. Nagler, Thomas & Czado, Claudia, 2016. "Evading the curse of dimensionality in nonparametric density estimation with simplified vine copulas," Journal of Multivariate Analysis, Elsevier, vol. 151(C), pages 69-89.
    18. Stöber, Jakob & Joe, Harry & Czado, Claudia, 2013. "Simplified pair copula constructions—Limitations and extensions," Journal of Multivariate Analysis, Elsevier, vol. 119(C), pages 101-118.
    19. Sun Wei & Rachev Svetlozar & Stoyanov Stoyan V. & Fabozzi Frank J., 2008. "Multivariate Skewed Student's t Copula in the Analysis of Nonlinear and Asymmetric Dependence in the German Equity Market," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 12(2), pages 1-37, May.
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    Cited by:

    1. Markus Wicker & Cihan Ates & Max Okraschevski & Simon Holz & Rainer Koch & Hans-Jörg Bauer, 2023. "Modeling Multivariate Spray Characteristics with Gaussian Mixture Models," Energies, MDPI, vol. 16(19), pages 1-15, September.
    2. Grothe Oliver & Rieger Jonas, 2024. "Decomposition and graphical correspondence analysis of checkerboard copulas," Dependence Modeling, De Gruyter, vol. 12(1), pages 1-31.

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