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Research Article

Random vibration analysis of an uncertain vehicle-track coupled system based on a polynomial dimensional decomposition

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Pages 233-252 | Received 17 Jul 2022, Accepted 28 Dec 2022, Published online: 09 Jan 2023

References

  • Xia H, Zhang N. Dynamic analysis of railway bridge under high-speed trains. Comput Struct. 2005;83(23–24):1891–1901.
  • Zhang N, Xia H. Dynamic analysis of coupled vehicle–bridge system based on inter-system iteration method. Comput Struct. 2013;114-115:26–34.
  • Zhu ZH, Gong W, Wang LD, et al. An efficient multi-time-step method for train-track-bridge interaction. Comput Struct. 2018;196:36–48.
  • Yu HL, Wang B, Li YL, et al. A two-step framework for stochastic dynamic analysis of uncertain vehicle-bridge system subjected to random track irregularity. Comput Struct. 2021;253:106583.
  • Wu SQ, Law SS. Dynamic analysis of bridge with non-Gaussian uncertainties under a moving vehicle. Probab Eng Eng Mech. 2011;26(2):281–293.
  • Wu SQ, Law SS. Evaluating the response statistics of an uncertain bridge-vehicle system. Mech Syst Signal Proc. 2012;27:576–589.
  • Xiang P, Zhao Y, Lin JH, et al. Random vibration analysis for coupled vehicle-track systems with uncertain parameters. Eng Comput. 2016;33(2):443–464. DOI:10.1108/EC-01-2015-0009
  • Yu ZW, Mao JF, Guo FQ, et al. Non-stationary random vibration analysis of a 3D train–bridge system using the probability density evolution method. J Sound Vibr. 2016;366:173–189.
  • Xu L, Zhai WM. Stochastic analysis model for vehicle-track coupled systems subject to earthquakes and track random irregularities. J Sound Vibr. 2017;407:209–225.
  • Xu L, Zhai WM. A new model for temporal–spatial stochastic analysis of vehicle–track coupled systems. Veh Syst Dyn. 2017;55(3):427–448.
  • Li J. Probability density evolution method: background, significance and recent developments. Probabilist Eng Mech. 2016;44:111–117.
  • Jaing ZM, Li J. A new reliability method combining kriging and probability density evolution method. Int J Struct Stab Dyn. 2017;17(10):1750113.
  • Peng YB, Zhou T, Li J. Surrogate modeling immersed probability density evolution method for structural reliability analysis in high dimensions. Mech Syst Signal Proc. 2021;152:107366.
  • Zhou T, Peng YB. Efficient reliability analysis based on deep learning-enhanced surrogate modelling and probability density evolution method. Mech Syst Signal Proc. 2022;162:108064.
  • Liu X, Jiang L, Xiang P, et al. Probability analysis of train-bridge coupled system considering track irregularities and parameter uncertainty. Mech Based Des Struct Mech. published online. 2021;1–18. DOI:10.1080/15397734.2021.1911665.
  • Jiang LZ, Liu X, Xiang P, et al. Train-bridge system dynamics analysis with uncertain parameters based on new point estimate method. Eng Struct. 2019;199:109454.
  • Jiang LZ, Liu X, Zhou T, et al. Application of KLE-PEM for Random Dynamic Analysis of Nonlinear Train-Track-Bridge System. Shock Vib. 2020;2020:8886737.
  • Li HL, Wang TY, Wu G .Probabilistic safety analysis of coupled train-bridge system using deep learning based surrogate model. Struct Infrastruct Eng. 2021:1–20. published online. doi:10.1080/15732479.2021.2010104.
  • Li HL, Wang TY, Wu G. A Bayesian deep learning approach for random vibration analysis of bridges subjected to vehicle dynamic interaction. Mech Syst Signal Proc. 2022;170:108799.
  • Wang W, Zhang YH, Ouyang HJ. Modeling uncertainties of vehicle-track coupled dynamic systems. Mech Based Des Struct Mech. 2021;49(7):947–968.
  • Rahman S. A polynomial dimensional decomposition for stochastic computing. Int J Numer Methods Eng. 2008;76(13):2091–2116.
  • Rahman S. Extended polynomial dimensional decomposition for arbitrary probability distributions. J Eng Mech. 2009;135(12):1439–1451.
  • Rahman S. Global sensitivity analysis by polynomial dimensional decomposition. Reliab Eng Syst Saf. 2011;96(7):825–837.
  • Lu K, Yang YF, Xia YB, et al. Statistical moment analysis of nonlinear rotor system with multi uncertain variables. Mech Syst Signal Proc. 2018;116:1029–1041.
  • Lu K, Hou L, Chen YS. Application of the polynomial dimensional decomposition method in a class of random dynamical systems. J Vibroeng. 2017;19(7):4827–4839.
  • Liu F, Zhao Y. A hybrid method for analysing stationary random vibration of structures with uncertain parameters. Mech Syst Signal Proc. 2022;164:108259.
  • Li J, Liao ST. Response analysis of stochastic parameter structures under non-stationary random excitation. Computational Mechanics. 2001;27(1):61–68.
  • Zhai WM. Vehicle-track coupled dynamics: theory and application. Singapore: Springer; 2020.
  • Zhai WM, Wang KY, Cai CB. Fundamentals of vehicle–track coupled dynamics. Veh Syst Dyn. 2009;47(11):1349–1376.
  • Lu F, Kennedy D, Williams FW, et al. Symplectic analysis of vertical random vibration for coupled vehicle track systems. J Sound Vibr. 2008;317(1–2):236–249. DOI:10.1016/j.jsv.2008.03.004
  • Lin JH, Fan Y, Bennett PN, et al. Propagation of stationary random waves along substructural chains. J Sound Vibr. 1995;180(5):757–767. DOI:10.1006/jsvi.1995.0113
  • Zhong WX, Williams FW. On the direct solution of wave propagation for repetitive structures. J Sound Vibr. 1995;181(3):485–501.
  • Rahman S. Statistical moments of polynomial dimensional decomposition. J Eng Mech. 2010;136(7):923–927.
  • Rahman S, Vadav V. Orthogonal polynomial expansions for solving random eigenvalue problems. Int J Uncertain Quan. 2011;1(2):163–187.
  • Rahman S. Mathematical Properties of Polynomial Dimensional Decomposition. SIAM-ASA J Uncertain. 2018;6(2):816–844.
  • Rahman S. Uncertainty quantification under dependent random variables by a generalized polynomial dimensional decomposition. Comput Methods Appl Mech Eng. 2019;344:910–937.
  • Liu X, Jiang L, Lai Z, et al. Sensitivity and dynamic analysis of train-bridge coupled system with multiple random factors. Eng Struct. 2020;221:111083.
  • Chen GH, Yang DX. A unified analysis framework of static and dynamic structural reliabilities based on direct probability integral method. Mech Syst Signal Proc. 2021;158:107783.
  • Liu J, Meng X, Xu C, et al. Forward and inverse structural uncertainty propagations under stochastic variables with arbitrary probability distributions. Comput Meth Appl Mech Eng. 2018;342:287–320.
  • Xu H, Rahman S. A generalized dimension-reduction method for multidimensional integration in stochastic mechanics. Int J Numer Methods Eng. 2004;61(12):1992–2019.

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