Research Article | OPEN ACCESS
An Imprecise Probability Model for Structural Reliability Based on Evidence and Gray Theory
1Bin Suo, 2Ying Yan, 1Chao Zeng and 1Jun Li
1Institute of Electronic Engineering, China Academy of Engineering Physics, Mianyang 621900, China
2School of Economics and Management, Southwest University of Science and Technology, Mianyang 621010, China
Research Journal of Applied Sciences, Engineering and Technology 2013 2:452-457
Received: May 06, 2012 | Accepted: June 08, 2012 | Published: January 11, 2013
Abstract
To avoid the shortages and limitations of probabilistic and non-probabilistic reliability model for structural reliability analysis in the case of limited samples for basic variables, a new imprecise probability model is proposed. Confidence interval with a given confidence is calculated on the basis of small samples by gray theory, which is not depending on the distribution pattern of variable. Then basic probability assignments and focal elements are constructed and approximation methods of structural reliability based on belief and plausibility functions are proposed in the situation that structure limit state function is monotonic and non-monotonic, respectively. The numerical examples show that the new reliability model utilizes all the information included in small samples and considers both aleatory and epistemic uncertainties in them, thus it can rationally measure the safety of the structure and the measurement can be more and more accurate with the increasing of sample size.
Keywords:
Epistemic uncertainty, evidence theory, gray theory, imprecise probability model, structural reliability,
Competing interests
The authors have no competing interests.
Open Access Policy
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Copyright
The authors have no competing interests.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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