A novel stochastic-spectral finite element method for analysis of elastodynamic problems in the time domain
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  • 作者:P. Zakian ; N. Khaji
  • 关键词:Karhunen–Loève expansion (KLE) ; Polynomial chaos expansion (PCE) ; Stochastic finite element method ; Spectral finite element method ; Wave propagation ; Stochastic structural dynamics
  • 刊名:Meccanica
  • 出版年:2016
  • 出版时间:April 2016
  • 年:2016
  • 卷:51
  • 期:4
  • 页码:893-920
  • 全文大小:9,809 KB
  • 参考文献:1.Kaminski M (2013) The stochastic perturbation method for computational mechanics. Wiley, New YorkCrossRef MATH
    2.Chang TP, Chang HC (1994) Stochastic dynamic finite element analysis of a nonuniform beam. Int J Solids Struct 31(5):587–597CrossRef MATH
    3.Schuëller GI (1997) A state-of-the-art report on computational stochastic mechanics. Probab Eng Mech 12(4):197–321CrossRef
    4.Takada T (1990) Weighted integral method in stochastic finite element analysis. Probab Eng Mech 5(3):146–156CrossRef
    5.Ghanem RG, Spanos PD (2003) Stochastic finite elements: a spectral approach. Courier Dover Publications, New YorkMATH
    6.Deb MK, Babuška IM, Oden JT (2001) Solution of stochastic partial differential equations using Galerkin finite element techniques. Comput Methods Appl Mech Eng 190(48):6359–6372ADS MathSciNet CrossRef MATH
    7.Kamiński M (2008) On stochastic finite element method for linear elastostatics by the Taylor expansion. Struct Multidiscip Optim 35(3):213–223CrossRef
    8.Anders M, Hori M (1999) Stochastic finite element method for elasto-plastic body. Int J Numer Meth Eng 46(11):1897–1916CrossRef MATH
    9.Xu XF (2012) Quasi-weak and weak formulation of stochastic finite elements on static and dynamic problems—a unifying framework. Probab Eng Mech 28:103–109CrossRef
    10.Muscolino G, Sofi A (2013) Bounds for the stationary stochastic response of truss structures with uncertain-but-bounded parameters. Mech Syst Signal Process 37(1–2):163–181ADS CrossRef
    11.Muscolino G, Sofi A (2012) Stochastic analysis of structures with uncertain-but-bounded parameters via improved interval analysis. Probab Eng Mech 28:152–163CrossRef
    12.Gioffrè M, Gusella V (2002) Numerical analysis of structural systems subjected to non-gaussian random fields. Meccanica 37(1–2):115–128CrossRef MATH
    13.Impollonia N, Muscolino G (2002) Static and dynamic analysis of non-linear uncertain structures. Meccanica 37(1–2):179–192CrossRef MATH
    14.Arnst M, Ghanem R, Phipps E, Red-Horse J (2012) Dimension reduction in stochastic modeling of coupled problems. Int J Numer Meth Eng 92(11):940–968MathSciNet CrossRef
    15.Chevreuil M, Nouy A (2012) Model order reduction based on proper generalized decomposition for the propagation of uncertainties in structural dynamics. Int J Numer Meth Eng 89(2):241–268MathSciNet CrossRef MATH
    16.Adhikari S (2011) A reduced spectral function approach for the stochastic finite element analysis. Comput Methods Appl Mech Eng 200(21–22):1804–1821ADS MathSciNet CrossRef MATH
    17.Chowdhury R, Adhikari S (2010) High dimensional model representation for stochastic finite element analysis. Appl Math Model 34(12):3917–3932MathSciNet CrossRef MATH
    18.Xiu D (2010) Numerical methods for stochastic computations: a spectral method approach. Princeton University Press, PrincetonMATH
    19.Stefanou G (2009) The stochastic finite element method: past, present and future. Comput Methods Appl Mech Eng 198(9–12):1031–1051ADS CrossRef MATH
    20.Patera AT (1984) A spectral element method for fluid dynamics: laminar flow in a channel expansion. J Comput Phys 54(3):468–488ADS MathSciNet CrossRef MATH
    21.Dauksher W, Emery AF (2000) The solution of elastostatic and elastodynamic problems with Chebyshev spectral finite elements. Comput Methods Appl Mech Eng 188(1–3):217–233ADS CrossRef MATH
    22.Hennings B, Lammering R, Gabbert U (2013) Numerical simulation of wave propagation using spectral finite elements. CEAS Aeronaut J 4(1):3–10CrossRef
    23.Khaji N, Habibi M, Mirhashemian P (2009) Modeling transient elastodynamic problems using spectral element method. Asian J Civ Eng 10(4):361–380
    24.Witkowski W, Rucka M, Chróścielewski J, Wilde K (2012) On some properties of 2D spectral finite elements in problems of wave propagation. Finite Elem Anal Des 55:31–41CrossRef
    25.Komatitsch D, Tromp J (1999) Introduction to the spectral element method for three-dimensional seismic wave propagation. Geophys J Int 139(3):806–822ADS CrossRef
    26.Shafiei M, Khaji N (2014) Simulation of two-dimensional elastodynamic problems using a new adaptive physics-based method. Meccanica 49(6):1353–1366CrossRef MATH
    27.Ghanem RG, Spanos PD (1997) Spectral techniques for stochastic finite elements. Arch Comput Methods Eng 4(1):63–100MathSciNet CrossRef MATH
    28.Kudela P, Krawczuk M, Ostachowicz W (2007) Wave propagation modelling in 1D structures using spectral finite elements. J Sound Vib 300(1–2):88–100ADS CrossRef MATH
    29.Adler RJ, Taylor JE (2007) Random fields and geometry, vol 115. Springer, BerlinMATH
    30.Bobrowski A (2005) Functional analysis for probability and stochastic processes: an introduction. Cambridge University Press, CambridgeCrossRef MATH
    31.Abramowitz M, Stegun IA (1964) Handbook of mathematical functions: with formulas, graphs, and mathematical tables. Dover Publications, New YorkMATH
    32.Ziari S, Ezzati R, Abbasbandy S (2012) Numerical solution of linear fuzzy Fredholm integral equations of the second kind using fuzzy Haar wavelet. In: Greco S, Bouchon-Meunier B, Coletti G, Fedrizzi M, Matarazzo B, Yager R (eds) Advances in computational intelligence, vol 299., Communications in computer and information scienceSpringer, Berlin, pp 79–89CrossRef
    33.Ikebe Y (1972) The Galerkin method for the numerical solution of Fredholm integral equations of the second kind. SIAM Review 14(3):465–491MathSciNet CrossRef MATH
    34.Bathe KJ (1996) Finite element procedures. Prentice Hall
    35.Saleh MM, El-Kalla IL, Ehab MM (2007) Stochastic finite element technique for stochastic one-dimension time-dependent differential equations with random coefficients. Differ Equ Nonlinear Mech 2007:1–16. doi:10.​1155/​2007/​48527
    36.Kamiński M (2010) Generalized stochastic perturbation technique in engineering computations. Math Comput Model 51(3–4):272–285MathSciNet CrossRef MATH
    37.Ghanem R (1999) Higher-order sensitivity of heat conduction problems to random data using the spectral stochastic finite element method. J Heat Transf 121(2):290–299CrossRef
    38.Bruch JC, Zyvoloski G (1974) Transient two-dimensional heat conduction problems solved by the finite element method. Int J Numer Meth Eng 8(3):481–494CrossRef MATH
    39.Khodakarami MI, Khaji N (2011) Analysis of elastostatic problems using a semi-analytical method with diagonal coefficient matrices. Eng Anal Bound Elem 35(12):1288–1296MathSciNet CrossRef MATH
  • 作者单位:P. Zakian (1)
    N. Khaji (1)

    1. Faculty of Civil and Environmental Engineering, Tarbiat Modares University, P.O. Box 14115–397, Tehran, Iran
  • 刊物类别:Physics and Astronomy
  • 刊物主题:Physics
    Mechanics
    Civil Engineering
    Automotive and Aerospace Engineering and Traffic
    Mechanical Engineering
  • 出版者:Springer Netherlands
  • ISSN:1572-9648
文摘
This article proposes a stochastically-tuned spectral finite element method (SFEM) which is applied to elastodynamic problems. Stochastic finite element method is an efficient numerical method incorporating randomness for uncertainty quantification of engineering systems. On the other hand, SFEM is an excellent remedy for solving dynamic problems with fine accuracy, which employs Lobatto polynomials leading to reduction of domain discretization and making diagonal mass matrices. The presented method simultaneously collects the advantages of the both methods in order to solve stochastically linear elastodynamic problems with suitable computational efficiency and accuracy. Furthermore, spectral finite element is also proposed for numerical solution of Fredholm integral equation associated with Karhunen–Loève expansion followed by the presented hybrid method which enhances the efficiency of the methodology. Various types of numerical examples are prepared so as to demonstrate advantages of the proposed stochastic SFEM.

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