| Issue |
MATEC Web Conf.
Volume 234, 2018
BulTrans-2018 – 10th International Scientific Conference on Aeronautics, Automotive and Railway Engineering and Technologies
|
|
|---|---|---|
| Article Number | 04002 | |
| Number of page(s) | 4 | |
| Section | Dynamics, Strength and Reliability of Vehicles | |
| DOI | https://doi.org/10.1051/matecconf/201823404002 | |
| Published online | 21 November 2018 | |
Using statistical methods to determine the load-bearing capacity of rectangular CFST columns
1 Ukrainian State University of Railway Transport, Structural Mechanics and Hydraulics Department, 7 Feuerbach Sq., 61050 Kharkiv, Ukraine
2 Ukrainian State University of Railway Transport, Applied Mathematics Department, 7 Feuerbach Sq., 61050 Kharkiv, Ukraine
* Corresponding author: glebvatulya@gmail.com
In the current practice of construction and design of transport facilities, structures with external reinforcement are commonly used which effectively resist compression. The use of steel-concrete and composite structures enables us to reduce material consumption and cost of structures significantly. There are a few established approaches used to evaluate the load-bearing capacity of steel-concrete structures under axial and eccentric compression, each being based on the initial prerequisites, which underlie the calculation formulas. In this paper, the functional relationship of the value of the maximum load-bearing capacity of rectangular concrete-filled steel tubular (CFST) columns under axial compression with the random eccentricity is plotted. A regression model is proposed based on the methods of mathematical statistics, which allows for the evaluation of the impact of geometrical and physical characteristics of rectangular CFST columns on the value of their load-bearing capacity. The correspondence of the obtained model to the experimental data, as well as the significance of the regression parameters are confirmed by Fisher and Student criteria.
© The Authors, published by EDP Sciences, 2018
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.
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