Citation:
Qing Wang and Jing-zheng Yao.Study on High Order Perturbation-based Nonlinear Stochastic Finite Element Method for Dynamic Problems[J].Journal of Marine Science and Application,2010,(4):386-392.
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Study on High Order Perturbation-based Nonlinear Stochastic Finite Element Method for Dynamic Problems
Qing Wang and Jing-zheng Yao.Study on High Order Perturbation-based Nonlinear Stochastic Finite Element Method for Dynamic Problems[J].Journal of Marine Science and Application,2010,(4):386-392.
Info
- Title:
- Study on High Order Perturbation-based Nonlinear Stochastic Finite Element Method for Dynamic Problems
- Author(s):
- Qing Wang and Jing-zheng Yao
- Affilations:
- DOI:
- -
- Abstract:
- Several algorithms were proposed relating to the development of a framework of the perturbation-based stochastic finite element method (PSFEM) for large variation nonlinear dynamic problems. For this purpose, algorithms and a framework related to SFEM based on the stochastic virtual work principle were studied. To prove the validity and practicality of the algorithms and framework, numerical examples for nonlinear dynamic problems with large variations were calculated and compared with the Monte-Carlo Simulation method. This comparison shows that the proposed approaches are accurate and effective for the nonlinear dynamic analysis of structures with random parameters.
References:
Bathe KJ (1996). Finite element procedure. Prentice- Hall, New York.
Belytschko T, Liu WK, Moran B (2000).
Nonlinear finite elements for continua and structures
. John Wiley & Sons, New York.
Falsone G, Ferro G (2007). An exact solution for the static and dynamic analysis of FE discretized uncertain structures. Comput. Methods Appl. Mech. Engrg, 196, 2390-2400.
Ghanem RG, Spanos PD (2003). Stochastic finite element: a spectral approach, Revised Edtion. Springer-Verlag, New York.
Haciefendioglu K, Basaga HB, Bayraktar A, Ates S (2007). Nonlinear analysis of rock-fill dams to non-stationary excitation by the stochastic Wilson-θ method. Applied Math. And Comput, 194(2), 333-345.
Haldar A, Zhou Y (1996). Reliability of geometrically nonlinear PR Frames. J. Engrg. Mech., ASCE, 118(10), 2148-2155.
Hisada T, Noguchi H (1989). Development of a nonlinear stochastic FEM and its application. Proceedings of the Fifth International Conference on Structural Safety and Reliability, San Francisco, USA, 1097-1104.
Ioannis D, Zhan K (2006). Perturbation-based stochastic FE analysis and robust design of inelastic deformation processes. Comput. Methods Appl. Mech. Engrg, 195, 2231-2251.
Kaminski M(2007) . Generalized perturbation-based stochastic finite element method in elastostatics. Computers and Structures, 85, 586-594.
Kleiber M, Hien TD (1992). The stochastic finite element method. Wiley, New York.
Liu PL , Der Kiureghian A (1988). Reliability of geometrically nonlinear structures, P.D. Spanos (Ed.) . Probabilistic Methods in Civil Engineering, ASCE, New York, 164-167.
Liu WK, Besterfield G, Mani A (1986). Probabilistic Finite element methods in nonlinear dynamics. Comput. Methods Appl. Mech. Eng, 56(1), 61-81.
Liu WK, Belytschko T, Mani A (1988). Prandom field finite elements. Int. J. Num. Mrth. Appl. Mech. Eng., 67, 27-54.
Oden JT, Babuska I, Nobile F, Feng Y, Tempone R (2005). Theory and methodology for estimation and control of errors due to modeling, approximation, and uncertainty. Comput. Methods Appl. Mech. Eng., 194, 195-204.
Shreider YA (1966). The Monte Carlo Method. Pergamon Press, New York.
Vanmarcke EH (1983). Random fields: analysis and synthesis. MIT Press, Cambridge.
Yang YB, Lin SP, Leu LJ (2007). Solution strategy and rigid element for nonlinear analysis of elastically structures base on updated Lagrangian formulation. Engineering Structures, 29, 1189-1200.
Zhao L, Chen Q (2000) .A stochastic variational formulation for nonlinear dynamic analysis of structure. Comput. Methods Appl. Mech. Engrg, 190, 597-608.
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