Issue |
ITM Web Conf.
Volume 15, 2017
II International Conference of Computational Methods in Engineering Science (CMES’17)
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Article Number | 03005 | |
Number of page(s) | 5 | |
Section | Computer Simulations Of Processes And Phenomena | |
DOI | https://doi.org/10.1051/itmconf/20171503005 | |
Published online | 15 December 2017 |
Stochastic higher order finite element elasto-plastic analysis of the necking phenomenon
Łódź University of Technology, Faculty of Civil Engineering, Architecture and Environmental Engineering, Department of Structural Mechanics, Politechniki Avenue 6, 90-924 Łódź, Poland
* Corresponding author: michal.strakowski@p.lodz.pl
The principal goal of this work is to investigate an application of the stochastic perturbation technique of the 10th order in coupled thermo-elasto-plastic analysis of tension of the steel elastic bar exposed to fire with thermally dependent material characteristics. An ambient temperature, calculated from the fire curve after ISO 834-1, equivalent to the fire exposure of the steel structure is treated here as the input Gaussian random variable. It is uniquely defined by the constant mean value at outer surfaces of this element, where material parameters of the steel as Young modulus, yield strength, heat conductivity, capacity and thermal elongation are considered all as highly temperature-dependent. Computational implementation known as the Stochastic Finite Element Method is carried out with the use of the FEM system ABAQUS and computer algebra system MAPLE. It uses both polynomial and non-polynomial local response functions of stresses and displacements. The basic probabilistic characteristics of time-dependent structural response are determined (expectations, coefficients of variation, skewness and kurtosis) and verified with classical Monte-Carlo simulation scheme and semi-analytical technique for input coefficient of variation not larger than 0.20. Finally, probabilistic convergence of all three methods versus increasing input uncertainty level is investigated.
© The Authors, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (http://creativecommons.org/licenses/by/4.0/).
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