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Modeling multibody systems with uncertainties. Part II: Numerical applications

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Abstract

This study applies generalized polynomial chaos theory to model complex nonlinear multibody dynamic systems operating in the presence of parametric and external uncertainty. Theoretical and computational aspects of this methodology are discussed in the companion paper “Modeling Multibody Dynamic Systems With Uncertainties. Part I: Theoretical and Computational Aspects”.

In this paper we illustrate the methodology on selected test cases. The combined effects of parametric and forcing uncertainties are studied for a quarter car model. The uncertainty distributions in the system response in both time and frequency domains are validated against Monte-Carlo simulations. Results indicate that polynomial chaos is more efficient than Monte Carlo and more accurate than statistical linearization. The results of the direct collocation approach are similar to the ones obtained with the Galerkin approach. A stochastic terrain model is constructed using a truncated Karhunen-Loeve expansion. The application of polynomial chaos to differential-algebraic systems is illustrated using the constrained pendulum problem. Limitations of the polynomial chaos approach are studied on two different test problems, one with multiple attractor points, and the second with a chaotic evolution and a nonlinear attractor set.

The overall conclusion is that, despite its limitations, generalized polynomial chaos is a powerful approach for the simulation of multibody dynamic systems with uncertainties.

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References

  1. Sandu, A., Sandu, C., Ahmadian, M.: Modeling multibody systems with uncertainties. Part I: Theoretical Development; Multibody System Dynamics #(#), #–# (2006)

  2. Ahmadian, M., Appleton, R., Norris, J.A.: Designing magneto-rheological recoil dampers in a fire-out-of battery recoil system. IEEE Transactions on Magnetics 37(1), 430–435 (2003)

    Google Scholar 

  3. Ahmadian, M., Poynor, J.C.: Effective test procedure for evaluating force characteristics of magneto-rheological dampers. In Proc. of ASME IMECE 2003, IMECE2003-38153, Nov. 15–21. Washington, D.C. (2003)

  4. Bekker, M.G.: Theory of land Locomotion. The U. of Michigan Press, Ann Arbor, Michigan (1956)

  5. Bekker, M.G.: Off-the-road locomotion. The University of Michigan Press, Ann Arbor. (1960)

  6. Bekker, M.G.: Introduction to terrain-vehicle systems, The University of Michigan Press, Ann Arbor, Michigan (1969)

  7. Harnisch, C., Jakobs, R.: Impact of Scattering Soil Strength and Roughness on Terrain Vehicle Dynamics. In Proc. of the 13th Int. Conf. of ISTVS, Munich. Germany (1999)

  8. Lucor, D., Su, C. H., Karniadakis, G.E.: Karhunen-Loeve Representation of Periodic Second Order Autoregressive Processes, M. Bubak editor, ICCS 2004, LNCS 3038. Springer-Verlag 827–834 (2004)

  9. Crandall, S.H.: Is stochastic linearization a fundamentally flawed procedure? Probabilistic Engineering Mechanics 16, 169–176 (2001)

    Article  Google Scholar 

  10. Lorenz, E.M.: Deterministic nonperiodic flow. J. Atmos. Sci. 20, 448–464 (1963)

    Google Scholar 

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Correspondence to Corina Sandu.

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Sandu, C., Sandu, A. & Ahmadian, M. Modeling multibody systems with uncertainties. Part II: Numerical applications. Multibody Syst Dyn 15, 241–262 (2006). https://doi.org/10.1007/s11044-006-9008-4

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  • DOI: https://doi.org/10.1007/s11044-006-9008-4

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