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UDC 629.764.017.1
Technical mechanics, 2018, 4, 105 - 118
USE OF TWO-DIMENSIONAL NORMAL COPULA IN PARAMETRIC RELIABILITY ESTIMATION MODELS
DOI:
https://doi.org/10.15407/itm2018.04.105
Gladky E. G.
Gladky E. G.
Yuzhnoye State Design Office
Ukraine
In most cases, determining the parametric reliability of the mechanical systems (MSs) of a launch vehicle (LV)
at the design stage can be reduced to one- and two-dimensional models. The use of the normal distribution
in such models is not always justified because the MS parameters often obey distribution laws distinct from
the normal one. This paper demonstrates that the LV MS parametric reliability can be estimated using
a two-dimensional normal copula constructed on the basis of one-dimensional generalized lambda distributions,
which show a considerable flexibility. The construction and features of a normal copula of this type are considered;
in particular, expressions for the distribution density, regression lines, and the distribution function
are presented. Such a distribution allows one to account for the difference of marginal distributions
from the normal one and a linear correlation between the components (a linear correlation between
the MS parameters is observed in 70 percent of cases). It is shown how the normal copula parameter
that characterizes a linear correlation between random variables can be obtained using the method
of moments.
In this paper, expressions for determining the LV MS parametric reliability are derived using the normal
copula constructed on the basis of one-dimensional generalized lambda distributions. With their help,
it is shown that accounting for both the difference of marginal distributions of random variables from
the normal one (first of all, the skew and the kurtosis) and for a linear correlation between them offers
a more accurate prediction of the MS reliability in comparison with the normal case. Accounting
for a nonlinear correlation between the MS parameters (a modified Farlie-Gumbel-Morgenstern copula
is used for comparison) does not either result in any significant deviation of the reliability index
from the values obtained with the use of the normal copula considered.
The practical use of the normal copula considered is demonstrated by the example of estimating
the probability of the propellant of an LV stage being sufficient for a trouble-free cutoff
of the propulsion system.
launch vehicle, probability of failure-free operation, state variables, normal copula, generalized lambda distribution
1. Volkov E. B., Sudakov R. S., Syritsyn T. A. Basics of Rocket Engine Reliability Theory. Moskow: Mashinostroyeniye, 1975. 399 pp. (in Russian).
2. Kramer G. Mathematical Methods of Statistics. Moscow: GIIL, 1975. 648 pp. (in Russian).
3. Mitropolsky A. K. Methods of Statistical Calculations. Moscow: Nauka, 1971. 576 pp. (in Russian).
4. Perlik V. I. Methodology of the reliability of flying vehicle mechanical systems. Space Hardware. Missilery. Dnipropetrovsk: Yuzhnoye State Design Office. 1995. Iss. 1-2. Pp. 37-43. (in Russian).
5. Perlik V. I., Gladky E .G. Statistical analysis of multidimensional samples of space hardware system characteristics. Kosmicheskaya Tekhnika. Raketnoye Vooruzheniye, 2002. Iss. 2. Pp. 16-27. (in Russian).
6. Perlik V. I., Savchuk V. P. On the determination of engineering system reliability by the method of functions. Probabilistic-Statistical Methods in Structural Design. Dnipropetrovsk: DGU. 1974. Pp. 29-35. (in Russian).
7. Kharitonova G. G., Perlik V. I. Generalization of a two-dimensional probability distribution system to the solution of nonlinear hardware reliability problems. Machine and Building Reliability and Longevity. Kyiv: Naukova Dumka. 1992. Iss. 21. Pp. 3-9. (in Russian).
8. Bairamov I, Kotz S., Bekci M. New generalized Farlie-Gumbel-Morgenstern distributions and concomitants of order statistics. Journal of Applied Statistics. 2001. V. 28. No. 5. Pp. 521-536.
https://doi.org/10.1080/02664760120047861
9. Balakrishnan N., Lai Chin-Diew. Continuous Bivariate Distributions. Springer-Verlag New York Inc., 2010. 684 pp.
10. Freimer M., Mudholkar G., Kollia G., Lin C. A study of the generalized Tukey Lambda family. Communications in Statistics, Theory and Methods. 1988. V. 17. No. 10. Pp. 3547-3567.
https://doi.org/10.1080/03610928808829820
11. Jonson N.L., Kotz S. Continuous Multivariate Distributions. Volume 2 - N.Y.e.a. John Wiley and Sons, 1972. 333 pp.
12. Karian Z., Dudewicz E. Fitting Statistical Distributions: The Generalized Lambda Distribution and Generalized Bootstrap Methods. CRC Press, Boca Raton, 2000. 435 pp.
https://doi.org/10.1201/9781420038040
13. Lee L. Generalized econometric models with selectivity. Econometrica. 1983. V. 51. Pp. 507-512.
https://doi.org/10.2307/1912003
14. Trivedi P. K., Zimmer D. M. Copula Modeling: An Introduction for Practitioners. Foundations and Trends in Econometric. 2005. V. 1. No. 1. Pp. 1-111.
https://doi.org/10.1561/0800000005
DOI:
https://doi.org/10.15407/itm2018.04.105
Copyright (©) 2018 Gladky E. G.
Copyright © 2014-2018 Technical mechanics
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