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1

Computer analysis of dynamic reliability of some concrete beam structure exhibiting random damping

Bredow R., Kamiński M.

International Journal of Applied Mechanics and Engineering

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2021

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Vol. 26, no. 1

45--64

EN

An efficiency of the generalized tenth order stochastic perturbation technique in determination of the basic probabilistic characteristics of up to the fourth order of dynamic response of Euler-Bernoulli beams with Gaussian uncertain damping is verified in this work. This is done on civil engineering application of a two-bay reinforced concrete beam using the Stochastic Finite Element Method implementation and its contrast with traditional Monte-Carlo simulation based Finite Element Method study and also with the semi-analytical probabilistic approach. The special purpose numerical implementation of the entire Stochastic perturbation-based Finite Element Method has been entirely programmed in computer algebra system MAPLE 2019 using Runge-Kutta-Fehlberg method. Further usage of the proposed technique to analyze stochastic reliability of the given structure subjected to dynamic oscillatory excitation is also included and discussed here because of a complete lack of the additional detailed demands in the current European designing codes.

2

Bridges for pedestrians with random parameters using the stochastic finite elements analysis

Szafran J., Kamiński M.

International Journal of Applied Mechanics and Engineering

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2017

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Vol. 22, no. 1

175--197

EN

The main aim of this paper is to present a Stochastic Finite Element Method analysis with reference to principal design parameters of bridges for pedestrians: eigenfrequency and deflection of bridge span. They are considered with respect to random thickness of plates in boxed-section bridge platform, Young modulus of structural steel and static load resulting from crowd of pedestrians. The influence of the quality of the numerical model in the context of traditional FEM is shown also on the example of a simple steel shield. Steel structures with random parameters are discretized in exactly the same way as for the needs of traditional Finite Element Method. Its probabilistic version is provided thanks to the Response Function Method, where several numerical tests with random parameter values varying around its mean value enable the determination of the structural response and, thanks to the Least Squares Method, its final probabilistic moments.

3

The least squares stochastic finite element method in structural stability analysis of steel skeletal structures

Kamiński M., Szafran J.

International Journal of Applied Mechanics and Engineering

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2015

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Vol. 20, no. 2

299--318

EN

The main purpose of this work is to verify the influence of the weighting procedure in the Least Squares Method on the probabilistic moments resulting from the stability analysis of steel skeletal structures. We discuss this issue also in the context of the geometrical nonlinearity appearing in the Stochastic Finite Element Metod equations for the stability analysis and preservation of the Gaussian probability density function employed to model the Young modulus of a structural steel in this problem. The weighting procedure itself (with both triangular and Dirac-type) shows rather marginal influence on all probabilistic coefficients under consideration. This hybrid stochastic computational technique consisting of the FEM and computer algebra systems (ROBOT and MAPLE packages) may be used for analogous nonlinear analyses in structural reliability assessment.

4

Navier–Stokes problems with random coefficients by the Weighted Least Squares Technique Stochastic Finite Volume Method

Kamiński M., Ossowski R. L.

Archives of Civil and Mechanical Engineering

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2014

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Vol. 14, no. 4

745--756

EN

The main aim of this article is numerical solution to the Navier–Stokes equations for incompressible, non-turbulent and subsonic fluid flows with Gaussian physical random parameters. It is done with the use of the specially adopted Finite Volume Method extended towards probabilistic analysis by the generalized stochastic perturbation technique. The key feature of this approach is the weighted version of the Least Squares Method implemented symbolically in the system MAPLE to recover nodal polynomial response functions of the velocities, pressures and temperatures versus chosen input random variable(s). Such an implementation of the Stochastic Finite Volume Method is applied to model 3D flow problem in the statistically homogeneous fluid with uncertainty in its viscosity and, separately, coefficient of the heat conduction. Probabilistic central moments of up to the fourth order and the additional characteristics are determined and visualized for the cavity lid driven flow owing to the specially adopted graphical environment FEPlot. Further numerical extension of this technique is seen in an application of the Taylor–Newton–Gauss approximation technique, where polynomial approximation may be replaced with the exponential or hyperbolic ones.

5

Reaction-diffusion problems with Random parameters using the generalized stochastic finite difference method

Kamiński M.

Journal of Applied Computer Science

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2011

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Vol. 19, nr 2

31-45

EN

The main idea here is to demonstrate the new stochastic discrete computational approach consisting of the generalized stochastic perturbation technique based on the Taylor expansions of the random variables and, at the same time, classical Finite Difference Method on the regular grids. As it is documented by the computational illustrations, it is possible to determine using this approach also higher probabilistic moments and to provide full hybrid analytical-discrete analysis for any random dispersion of input variables unlike in the second order second moment technique worked out before. A numerical algorithm is implemented here using the straightforward partial differentiation of the reaction-diffusion equation with respect to the random input quantity; all symbolic computations of probabilistic moments and characteristics are completed by the computer algebra system MAPLE.