Abstract
Considering the unavoidable uncertainty of material properties, geometry, and external loads existing in rigid–flexible multibody systems, a new hybrid uncertain computational method is proposed. Two evaluation indexes, namely interval mean and interval error bar, are presented to quantify the system response. The dynamic model of a rigid–flexible multibody system is built by using the absolute node coordinate formula (ANCF). The geometry size and external loads of rigid components are considered as interval variables, while the Young’s modulus and Poisson’s ratio of flexible components are expressed by a random field. The continuous random field is discretized to Gaussian random variables by using the expansion optimal linear estimation (EOLE) method. This paper proposes an orthogonal series expansion method, termed as improved Polynomial-Chaos-Chebyshev-Interval (PCCI) method, which solves the random and interval uncertainty under one integral framework. The improved PCCI method has some sampling points located on the bounds of interval variables, which lead to a higher accuracy in estimating the bounds of multibody systems’ response compared to the PCCI method. A rigid–flexible slider–crank mechanism is used as a numerical example, which demonstrates that the improved PCCI method has a higher accuracy than the PCCI method.
Similar content being viewed by others
References
Arnold, M., Bruls, O.: Convergence of the generalized-\(\alpha \) scheme for constrained mechanical systems. Multibody Syst. Dyn. 18(2), 185–202 (2007)
Beer, M., Ferson, S., Kreinovich, V.: Imprecise probabilities in engineering analyses. Mech. Syst. Signal Process. 37(1–2), 4–29 (2013). https://doi.org/10.1016/j.ymssp.2013.01.024
Betz, W., Papaioannou, I., Straub, D.: Numerical methods for the discretization of random fields by means of the Karhunen–Loève expansion. Comput. Methods Appl. Mech. Eng. 271, 109–129 (2014). https://doi.org/10.1016/j.cma.2013.12.010
Do, D.M., Gao, W., Song, C.: Stochastic finite element analysis of structures in the presence of multiple imprecise random field parameters. Comput. Methods Appl. Mech. Eng. 300, 657–688 (2016). https://doi.org/10.1016/j.cma.2015.11.032
Du, X., Venigella, P.K., Liu, D.: Robust mechanism synthesis with random and interval variables. Mech. Mach. Theory 44(7), 1321–1337 (2009). https://doi.org/10.1016/j.mechmachtheory.2008.10.003
Fishman, G.S.: Monte Carlo: Concepts, Algorithms, and Applications. Springer, New York (1996)
Gao, W., Song, C., Tin-Loi, F.: Probabilistic interval analysis for structures with uncertainty. Struct. Saf. 32(3), 191–199 (2010)
García-Vallejo, D., Mayo, J., Escalona, J.L., Domínguez, J.: Three-dimensional formulation of rigid-flexible multibody systems with flexible beam elements. Multibody Syst. Dyn. 20(1), 1–28 (2008). https://doi.org/10.1007/s11044-008-9103-9
Gerstmayr, J., Shabana, A.A.: Analysis of thin beams and cables using the absolute nodal coordinate formulation. Nonlinear Dyn. 45(1–2), 109–130 (2006)
Gerstmayr, J., Matikainen, M.K., Mikkola, A.M.: A geometrically exact beam element based on the absolute nodal coordinate formulation. Multibody Syst. Dyn. 20(4), 359–384 (2008)
Ghanem, R.G., Spanos, P.D.: Stochastic Finite Elements: a Spectral Approach. Springer, New York (1991)
Isukapalli, S.S.: Uncertainty Analysis of Transport-Transformation Models. State University of New Jersey, New Brunswick (1999)
Jiang, C., Zheng, J., Han, X.: Probability-interval hybrid uncertainty analysis for structures with both aleatory and epistemic uncertainties: a review. Struct. Multidiscip. Optim. (2017). https://doi.org/10.1007/s00158-017-1864-4
Kang, Z., Luo, Y.: Non-probabilistic reliability-based topology optimization of geometrically nonlinear structures using convex models. Comput. Methods Appl. Mech. Eng. 198(41–44), 3228–3238 (2009)
Li, C.C., Der Kiureghian, A.: Optimal discretization of random field. J. Eng. Mech. 119, 1136–1154 (1993)
Sandu, C., Sandu, A., Blanchard, E.D.: Polynomial chaos-based parameter estimation methods applied to a vehicle system. J. Multi-Body Dyn. 224(1), 59–81 (2010). https://doi.org/10.1243/14644193jmbd204
Sarkar, A., Ghanem, R.: Mid-frequency structural dynamics with parameter uncertainty. Comput. Methods Appl. Mech. Eng. 191, 5499–5513 (2002)
Shabana, A.A.: An Absolute Nodal Coordinates Formulation for the Large Rotation and Deformation Analysis of Flexible Bodies. University of Illinois, Chicago (1997)
Shabana, A.A.: Definition of the slopes and absolute nodal coordinate formulation. Multibody Syst. Dyn. 1, 339–348 (1997)
Shabana, A.A.: Flexible multi-body dynamics review of past and recent developments. Multibody Syst. Dyn. 1, 189–222 (1997)
Shabana, A.A.: Dynamics of Multibody Systems. Cambridge University Press, New York (2005)
Shabana, A.A.: ANCF reference node for multibody system analysis. J. Multi-Body Dyn. 229(1), 109–112 (2014). https://doi.org/10.1177/1464419314546342
Sudret, B., Der Kiureghian, A.: Stochastic Finite Element Methods and Reliability a State-of-the-Art Report. University of Calnifornia, Berkeley (2000)
Tian, Q., Chen, L.P., Zhang, Y.Q., Yang, J.: An efficient hybrid method for multibody dynamics simulation based on absolute nodal coordinate formulation. J. Comput. Nonlinear Dyn. 4(2), 021009 (2009). https://doi.org/10.1115/1.3079783
Tian, Q., Liu, C., Machado, M., Flores, P.: A new model for dry and lubricated cylindrical joints with clearance in spatial flexible multibody systems. Nonlinear Dyn. 64(1–2), 25–47 (2010). https://doi.org/10.1007/s11071-010-9843-y
Tian, Q., Liu, C., Machado, M., Flores, P.: A new model for dry and lubricated cylindrical joints with clearance in spatial flexible multibody systems. Nonlinear Dyn. 64(1–2), 25–47 (2011). https://doi.org/10.1007/s11071-010-9843-y
Tian, Q., Xiao, Q., Sun, Y., Hu, H., Liu, H., Flores, P.: Coupling dynamics of a geared multibody system supported by ElastoHydroDynamic lubricated cylindrical joints. Multibody Syst. Dyn. 33(3), 259–284 (2014). https://doi.org/10.1007/s11044-014-9420-0
Wang, Z., Tian, Q., Hu, H.: Dynamics of spatial rigid–flexible multibody systems with uncertain interval parameters. Nonlinear Dyn. 84(2), 527–548 (2016). https://doi.org/10.1007/s11071-015-2504-4
Wang, Z., Tian, Q., Hu, H.: Dynamics of flexible multibody systems with hybrid uncertain parameters. Mech. Mach. Theory 121, 128–147 (2018). https://doi.org/10.1016/j.mechmachtheory.2017.09.024
Wu, J., Luo, Z., Zhang, Y., Zhang, N., Chen, L.: Interval uncertain method for multibody mechanical systems using Chebyshev inclusion functions. Int. J. Numer. Methods Eng. 95(7), 608–630 (2013). https://doi.org/10.1002/nme.4525
Wu, J., Luo, Z., Zhang, N., Zhang, Y.: A new uncertain analysis method and its application in vehicle dynamics. Mech. Syst. Signal Process. 50–51, 659–675 (2015). https://doi.org/10.1016/j.ymssp.2014.05.036
Wu, D., Gao, W., Song, C., Tangaramvong, S.: Probabilistic interval stability assessment for structures with mixed uncertainty. Struct. Saf. 58, 105–118 (2016). https://doi.org/10.1016/j.strusafe.2015.09.003
Wu, J., Luo, Z., Zhang, N., Zhang, Y.: Dynamic computation of flexible multibody system with uncertain material properties. Nonlinear Dyn. 85(2), 1231–1254 (2016). https://doi.org/10.1007/s11071-016-2757-6
Wu, J., Luo, Z., Li, H., Zhang, N.: Level-set topology optimization for mechanical metamaterials under hybrid uncertainties. Comput. Methods Appl. Mech. Eng. 319, 414–441 (2017). https://doi.org/10.1016/j.cma.2017.03.002
Wu, J., Luo, Z., Li, H., Zhang, N.: A new hybrid uncertainty optimization method for structures using orthogonal series expansion. Appl. Math. Model. 45, 474–490 (2017). https://doi.org/10.1016/j.apm.2017.01.006
Wu, J., Luo, Z., Zhang, N., Zhang, Y., Walker, P.D.: Uncertain dynamic analysis for rigid-flexible mechanisms with random geometry and material properties. Mech. Syst. Signal Process. 85, 487–511 (2017). https://doi.org/10.1016/j.ymssp.2016.08.040
Xia, B., Yu, D., Liu, J.: Change-of-variable interval stochastic perturbation method for hybrid uncertain structural-acoustic systems with random and interval variables. J. Fluids Struct. 50, 461–478 (2014)
Xiu, D., Karniadakis, G.E.: Modeling uncertainty in steady state diffusion problems via generalized polynomial chaos. Comput. Methods Appl. Mech. Eng. 191, 4927–4948 (2002)
Xiu, D., Karniadakis, G.E.: Modeling uncertainty in flow simulations via generalized polynomial chaos. J. Comput. Phys. 187(1), 137–167 (2003). https://doi.org/10.1016/s0021-9991(03)00092-5
Zhang, J., Ellingwood, B.: Orthogonal series expansion of random fields in reliability analysis. J. Eng. Mech. 120, 2660–2677 (1994)
Zhang, Y., Tian, Q., Chen, L., Yang, J.: Simulation of a viscoelastic flexible multibody system using absolute nodal coordinate and fractional derivative methods. Multibody Syst. Dyn. 21(3), 281–303 (2008). https://doi.org/10.1007/s11044-008-9139-x
Zhou, B., Zi, B., Qian, S.: Dynamics-based nonsingular interval model and luffing angular response field analysis of the DACS with narrowly bounded uncertainty. Nonlinear Dyn. 90, 2599–2626 (2017)
Acknowledgements
This research is supported by Natural-Science-Foundation of China (11502083) and Fundamental Research Funds for the Central Universities.
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Wu, J., Luo, L., Zhu, B. et al. Dynamic computation for rigid–flexible multibody systems with hybrid uncertainty of randomness and interval. Multibody Syst Dyn 47, 43–64 (2019). https://doi.org/10.1007/s11044-019-09677-1
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11044-019-09677-1