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Statistical Model Development for Military Aircraft Engine Exhaust Emissions Data

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Advances in Sustainable Aviation

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Abstract

Statistical regression models have a wide usage in various estimation problems. They can be used to find a relationship between dependent and independent variables. Generally, it is using regression parametric models to find the type of relationship between variables. But some problems could not be estimated with linear models, as they have a nonlinear effect on dependent variable. This study aims to show the difference between linear and nonlinear techniques. In this study, emission parameters of a military-type turboprop engine is determined at unmeasured operating points on the basis of data collected at various loads with the aid of regression techniques. It is using multivariate linear regression, additive models with B-spline basis function, and smoothing splines. Three different techniques used to reveal best approximation to the dataset. It is observed that the effect of three parameters: revolution per minute (min-1), air/fuel ratio (kg air/kg fuel), and mass flow rate (kg.s-1) to different mass flow rates (CO (kg/s), CO2 (kg/s); UHC (kg/s), NO2 (kg/s)). In the end of the study, results obtained from benefited approximations were compared with each other using MSE (mean squared error) performance criteria.

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Abbreviations

ṁ:

Mass flow rate [kg/s]

p:

Static pressure [Pa]

P:

Total pressure [Pa]

P-GAM:

Penalized generalized additive model

q:

Dynamic pressure [Pa]

T:

Temperature [K]

x 1 ,  ⋯  , x n :

Knot points

b j (x):

Basis function

CV(λ):

Cross-validation method

f(x):

Regression function

f(μ i ):

Link function

GCV(λ):

Generalized cross-validation method

S(f):

Minimization function

λ :

Smoothing parameter

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Acknowledgments

Support provided by Anadolu and Suleyman Demirel Universities is gratefully acknowledged.

Author information

Authors and Affiliations

  1. Department of Statistics, Graduate School of Sciences, Anadolu University, 26470, Eskisehir, Turkey

    Akhlitdin Nizamitdinov

  2. Department of Airframe and Powerplant Maintenance, Süleyman Demirel University, School of Civil Aviation, 32700, Isparta, Turkey

    Yasin Şöhret

  3. Department of Statistics, Faculty of Science, Anadolu University, 26470, Eskisehir, Turkey

    Aladdin Shamilov

  4. Department of Airframe and Powerplant Maintenance, Anadolu University, Faculty of Aeronautics and Astronautics, 26470, Eskisehir, Turkey

    T. Hikmet Karakoç

Authors
  1. Akhlitdin Nizamitdinov
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  2. Yasin Şöhret
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  3. Aladdin Shamilov
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  4. T. Hikmet Karakoç
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Corresponding author

Correspondence to Akhlitdin Nizamitdinov .

Editor information

Editors and Affiliations

  1. Department of Airframe and Powerplant Maintenance, Anadolu University, Faculty of Aeronautics and Astronautics, Eskisehir, Turkey

    Tahir Hikmet Karakoç

  2. Department of Mechanical Engineering, Dokuz Eylul University, Faculty of Engineering, Buca, Izmir, Turkey

    C. Ozgur Colpan

  3. Department of Airframe and Powerplant Maintenance, Süleyman Demirel University, School of Civil Aviation, Isparta, Turkey

    Yasin Şöhret

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Nizamitdinov, A., Şöhret, Y., Shamilov, A., Karakoç, T.H. (2018). Statistical Model Development for Military Aircraft Engine Exhaust Emissions Data. In: Karakoç, T., Colpan, C., Şöhret, Y. (eds) Advances in Sustainable Aviation. Springer, Cham. https://doi.org/10.1007/978-3-319-67134-5_12

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  • DOI: https://doi.org/10.1007/978-3-319-67134-5_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67133-8

  • Online ISBN: 978-3-319-67134-5

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