Reference : A stochastic Galerkin cell-based smoothed finite element method (SGCS-FEM) |
Scientific journals : Article | |||
Engineering, computing & technology : Aerospace & aeronautics engineering Engineering, computing & technology : Civil engineering Engineering, computing & technology : Materials science & engineering Engineering, computing & technology : Mechanical engineering Engineering, computing & technology : Multidisciplinary, general & others | |||
Computational Sciences | |||
http://hdl.handle.net/10993/40777 | |||
A stochastic Galerkin cell-based smoothed finite element method (SGCS-FEM) | |
English | |
Mathew, Tittu [Indian Institute of Technology Madras > Mechanical Engineering] | |
Beex, Lars ![]() | |
Bordas, Stéphane ![]() | |
Natarajan, Sundararajan [Indian Institute of Technology Madras > Mechanical Engineering] | |
Jul-2019 | |
International Journal of Computational Methods | |
World Scientific Publishing Co. | |
17 | |
8 | |
Yes (verified by ORBilu) | |
International | |
0219-8762 | |
Singapore | |
[en] Stochastic Galerkin Cell-based Smoothed Finite Element Method (SGCS- FEM) ; Karhunen-Loeve expansion (KLE) ; Polynomial Chaos Expansion (PLE) ; Random Material Properties ; Free Vibrations | |
[en] In this paper, the cell based smoothed finite element method is extended to solve stochastic partial diff erential equations with uncertain input parameters. The spatial field of Young's moduli and the corresponding stochastic results are represented by Karhunen-Lo eve expansion and polynomial chaos expansion, respectively. The Young's Modulus of structure is considered to be random for stochastic static as well as free vibration problems. Mathematical expressions and the solution procedure are articulated in detail to evaluate the statistical characteristics of responses in terms of static displacements and free vibration frequencies. The feasibility and eff ectiveness of the proposed SGCS-FEM method in terms of accuracy and lower requirement on the mesh size in the solution domain over that of conventional FEM for stochastic problems are demonstrated by carefully chosen numerical examples. From the numerical study, it is inferred that the proposed framework is computationally less demanding without compromising accuracy. | |
Researchers ; Professionals | |
http://hdl.handle.net/10993/40777 |
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