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A Galerkin-based formulation of the probability density evolution method for general stochastic finite element systems

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Abstract

The present paper proposes a Galerkin finite element projection scheme for the solution of the partial differential equations (pde’s) involved in the probability density evolution method, for the linear and nonlinear static analysis of stochastic systems. According to the principle of preservation of probability, the probability density evolution of a stochastic system is expressed by its corresponding Fokker–Planck (FP) stochastic partial differential equation. Direct integration of the FP equation is feasible only for simple systems with a small number of degrees of freedom, due to analytical and/or numerical intractability. However, rewriting the FP equation conditioned to the random event description, a generalized density evolution equation (GDEE) can be obtained, which can be reduced to a one dimensional pde. Two Galerkin finite element method schemes are proposed for the numerical solution of the resulting pde’s, namely a time-marching discontinuous Galerkin scheme and the StreamlineUpwind/Petrov Galerkin (SUPG) scheme. In addition, a reformulation of the classical GDEE is proposed, which implements the principle of probability preservation in space instead of time, making this approach suitable for the stochastic analysis of finite element systems. The advantages of the FE Galerkin methods and in particular the SUPG over finite difference schemes, like the modified Lax–Wendroff, which is the most frequently used method for the solution of the GDEE, are illustrated with numerical examples and explored further.

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Acknowledgments

This work has been supported by the European Research Council Advanced Grant “MASTER-Mastering the computational challenges in numerical modeling and optimum design of CNT reinforced composites” (ERC-2011-ADG_20110209).

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Correspondence to Ioannis Kalogeris.

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Papadopoulos, V., Kalogeris, I. A Galerkin-based formulation of the probability density evolution method for general stochastic finite element systems. Comput Mech 57, 701–716 (2016). https://doi.org/10.1007/s00466-015-1256-9

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  • DOI: https://doi.org/10.1007/s00466-015-1256-9

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