Issue |
E3S Web Conf.
Volume 45, 2018
VI International Conference of Science and Technology INFRAEKO 2018 Modern Cities. Infrastructure and Environment
|
|
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Article Number | 00062 | |
Number of page(s) | 8 | |
DOI | https://doi.org/10.1051/e3sconf/20184500062 | |
Published online | 30 July 2018 |
The stochastic finite element method in the assessment of bridge infrastructure objects - review
Faculty of Materials, Civil and Environmental Engineering, University of Bielsko-Biala, 43-309, st. Willowa 2, Poland
* Corresponding author: powerko@ath.bielsko.pl, piotrowerko@gmail.com
The stochastic finite element method (SFEM) is an extension of classical FEM which allows the representation of various types and sources of uncertainty in one computational system. This review paper presents information regarding SFEM implementation in the assessment of bridge objects. A concise theoretical background of the three most commonly used branches of SFEM is also presented. This technique is used in the assessment of bridge structures with regards to, e.g. load in motion problems, wind and seismic excitation analysis, random material property analysis, reliability and fatigue reliability analysis. However, it seems that the main feasibility concern is the lack of proper SFEM implementation into general purpose FEM systems which are used by bridge engineers. This is why, arguably, one of the most effective ways to introduce SFEM in real-life bridge engineering problems is with the methods that rely on multiple calculations of classical deterministic FEM e.g. Monte Carlo Simulation, or Response Function Method. To introduce randomness directly into individual finite elements of the model in a complete SFEM procedure it is usually necessary to develop proprietary computer programs.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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