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Dynamic response of a spur gear system with uncertain parameters

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
In this paper, we propose a new approach for taking into account uncertainties based on the projection on polynomial chaos. The new approach is used to determine the dynamic response of a spur gear system with uncertainty associated to gear system parameters. The simulation results are obtained by the polynomial chaos approach for dynamic analysis under uncertainty. The proposed approach is an efficient probabilistic tool for uncertainty propagation. It has been found to be an interesting alternative to the parametric studies. The polynomial chaos results are compared with Monte Carlo simulations.
Rocznik
Strony
1039--1049
Opis fizyczny
Bibliogr. 31 poz., rys., tab.
Twórcy
autor
  • Laboratory Optimization and Reliability in Structural Mechanics LOFIMS, Mechanical Engineering Department, National Institute of Applied Sciences of Rouen, Cedex, France and Mechanics, Modelling and Manufacturing Laboratory LA2MP, Mechanical Engineering Department, National School of Engineers of Sfax, Sfax, Tunisia
autor
  • Laboratory Optimization and Reliability in Structural Mechanics LOFIMS, Mechanical Engineering Department, National Institute of Applied Sciences of Rouen, Cedex, France
autor
  • Mechanics, Modelling and Manufacturing Laboratory LA2MP, Mechanical Engineering Department, National School of Engineers of Sfax, Sfax, Tunisia
autor
  • Mechanics, Modelling and Manufacturing Laboratory LA2MP, Mechanical Engineering Department, National School of Engineers of Sfax, Sfax, Tunisia
autor
  • Mechanics, Modelling and Manufacturing Laboratory LA2MP, Mechanical Engineering Department, National School of Engineers of Sfax, Sfax, Tunisia
Bibliografia
  • 1. Abo Al-kheer A., El-Hami A., Kharmanda M.G., Mouazen A.M., 2011, Reliability-based design for soil tillage machines, Journal of Terramechanics, 48, 1, 57-64
  • 2. Askey R., Wilson J., 1985, Some basic hypergeometric polynomials that generalize jacobi polynomials, Memoirs of the American Mathematical Society, 319
  • 3. Babuska I., Nobile F., Tempone R., 2007, A stochastic collocation method for elliptic partial differential equations with random input data, SIAM Journal on Numerical Analysis, 45, 1005-1034
  • 4. Babuska I., Tempone R., Zouraris G.E., 2004, Galerkin finite element approximation of stochastic elliptic partial differential equations, SIAM Journal on Scientific Computing, 24, 619-644
  • 5. Begg C.D., Byington C.S., Maynard K., 2000, Dynamic simulation of mechanical fault transition, Proceedings of the 54th Meeting of the Society for Machinery Failure Prevention Technology, Virginia Beach
  • 6. Blanchard E., Sandu A., Sandu C., 2009, Parameter estimation for mechanical systems via an explicit representation of uncertainty, Engineering Computations, 26, 5, 541-569
  • 7. Cameron H., Martin W., 1947, The orthogonal development of nonlinear functional in series of Fourier-Hermite functional, Annals of Mathematics, 48, 385-392
  • 8. Crestaux T., Le Maitre O., Martinez J.M., 2009, Polynomial chaos expansion for sensitivity analysis, Reliability Engineering and System Safety, 94, 1161-1172
  • 9. Dalpiaz G., Rivola A., Rubini R., 1996, Dynamic modeling of gear systems for condition monitoring and diagnostics, Congress on Technical Diagnostics
  • 10. El Hami A., Lallement G., Minottiand P., Cogan S., 1993, Methods that combine finite group theory with component mode synthesis in the analysis of repetitive structures, International Journal Computers and Structures, 48, 975-982
  • 11. El Hami A., Radi B., 1996, Some decomposition methods in the analysis of repetitive structures, International Journal Computers and Structures, 58, 5, 973-980
  • 12. El Hami A., Radi A., Cherouat A., 2009, The frictional contact of the shaping of the composite fabric, International Journal of Mathematical and Computer Modelling, 49,7/8, 1337-1349
  • 13. Fishman G.S., 1996, Monte Carlo, Concepts, Algorithms and Applications, First Ed. SpringerVerlag
  • 14. Ghanem R.G., Spanos P.D., 1991, Stochastic Finite Elements: A Spectral Approach, Revised Ed. Springer Verlag
  • 15. Guerine A., El Hami A., Fakhfakh T., Haddar M., 2015a, A polynomial chaos method to the analysis of the dynamic behavior of spur gear system, Structural Engineering and Mechanics, 53, 819-831 1
  • 6. Guerine A., El Hami A., Walha L., Fakhfakh T., Haddar M., 2015b, A perturbation approach for the dynamic analysis of one stage gear system with uncertain parameters, Mechanism and Machine Theory, 92, 113-126
  • 17. Isukapalli S.S., Roy A., Georgopoulos P.G., 1998a, Development and application of methods for assessing uncertainty in photochemical air quality problems, Interim Report for U.S.EPA National Exposure Research Laboratory
  • 18. Isukapalli S.S., Roy A., Georgopoulos P.G., 1998b, Stochastic response surface methods (SRSMs) for uncertainty propagation: application to environmental and biological systems, Risk Analysis, 18, 351-363
  • 19. Le Maıtre O.P., Knio O.M., Najm H.N., Ghanem R.G., 2001, A stochastic projection method for fluid flow Basic formulation, Journal of Computational Physics, 173, 481-511
  • 20. Lindsley N.J., Beran P.S., 2005, Increased efficiency in the stochastic interrogation of an uncertain nonlinear aeroelastic system, International Forum on Aeroelasticity and Structural Dynamics, Munich, Germany
  • 21. Papadrakakis M., Papadopoulos V., 1999, Parallel solution methods for stochastic finite element analysis using Monte Carlo simulation, Computer Methods in Applied Mechanics and Engineering, 168, 305-320
  • 22. Saad G., Ghanem R., Masri S., 2007, Robust system identification of strongly nonlinear dynamics using a polynomial chaos based sequential data assimilation technique, Structural Dynamics and Materials Conference, Honolulu, USA
  • 23. Sandu A., Sandu C., Ahmadian M., 2006a, Modeling multibody dynamic systems with uncertainties. Part I: numerical application, Multibody System Dynamic, 15, 369-391
  • 24. Sandu C., Sandu A., Ahmadian M., 2006b, Modeling multibody dynamic systems with uncertainties. Part II: theoretical and computational aspects, Multibody System Dynamic, 15, 241-262
  • 25. Sarsri D., Azrar L., Jebbouri A., El Hami A., 2011, Component mode synthesis and polynomial chaos expansions for stochastic frequency functions of large linear FE models, Computers and Structures, 89, 3/4, 346-356
  • 26. Smith A.H.C., Monti A., Ponci F., 2007, Indirect measurements via a polynomial chaos observer, IEEE Transactions on Instrumentation and Measurement, 56, 743-752
  • 27. Walha L., Fakhfakh T., Haddar M., 2009, Nonlinear dynamics of a two-stage gear system with mesh stiffness fluctuation, bearing flexibility and backlash, Mechanism and Machine Theory, 44, 1058-1069
  • 28. Wiener N., 1938, The homogeneous chaos, American Journal of Mathematics, 60, 897-936
  • 29. Williams M.M.R., 2006, Polynomial chaos functions and stochastic differential equations, Annals of Nuclear Energy, 33, 774-785
  • 30. Xiu D., Karniadakis G.E., 2002, Modeling uncertainty in steady state diffusion problems via generalized polynomial chaos, Computer Methods in Applied Mechanics and Engineering, 191, 4927-4948
  • 31. Xiu D., Karniadakis G.E., 2003, Modelling uncertainty in flow simulations via generalized polynomial chaos, Journal of Computational Physics, 187, 137-167
Uwagi
PL
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniajacą naukę.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-aaffc577-a2c9-4328-8a3f-f252613a40be
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