Issue |
MATEC Web Conf.
Volume 95, 2017
2016 the 3rd International Conference on Mechatronics and Mechanical Engineering (ICMME 2016)
|
|
---|---|---|
Article Number | 17001 | |
Number of page(s) | 4 | |
Section | Civil and Architectural Engineering | |
DOI | https://doi.org/10.1051/matecconf/20179517001 | |
Published online | 09 February 2017 |
Structural Reliability Analysis Using Orthogonalizable Power Polynomial Basis Vector
School of Civil Engineering and Architecture, Wuhan University of Technology, Wuhan, China
A new method for structural reliability analysis using orthogonalizable power polynomial basis vector is presented. Firstly, a power polynomial basis vector is adopted to express the initial series solution of structural response, which is determined by a series of deterministic recursive equation based on perturbation technique, and then transferred to be a set of orthogonalizable power polynomial basis vector using the orthogonalization technique. By conducting Garlekin projection, an accelerating factor vector of the orthogonalizable power polynomial expansion is determined by solving small scale algebraic equations. Numerical results of a continuous bridge structure on reliability analysis shows that the proposed method can achieve the accuracy of the Direct Monte Carlo method and can save a lot of computation time at the same time, it is both accurate and efficient, and is very competitive to be used in structural reliability analysis.
© 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.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.