DocumentCode :
2728413
Title :
Notice of Retraction
Research on reliability sensitivity for ranking the importance of random influential factors
Author :
Lai Xiongming ; Wu Zhenghui
Author_Institution :
Coll. of Mech. & Electr. Eng., Central South Univ., Changsha, China
fYear :
2011
fDate :
15-17 July 2011
Firstpage :
235
Lastpage :
238
Abstract :
Notice of Retraction

After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.

We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.

The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.

During the reliability analysis, the influential factors that play important role on reliability, mainly contain two aspects: the influence of the randomicity of the influential factors itself on reliability and its coupling influence combined with the randomicity of other influential factors on reliability. Considering the above two aspects of influence, two kinds of reliability sensitivity, including single reliability sensitivity and synthetical reliability sensitivity, are defined in this paper for estimating the influence of each variable on reliability. To improve the computation efficiency of the above methods and expand their applicability, especially aiming at solving the case that the limit state function is implicit and its solution consumes much time of computer simulation, a fast method for computing reliability sensitivity by combining the kriging model with Monte Carlo simulation is presented in this paper. As shown by the example, agreement between results computed by both methods appears very good and the proposed methods are efficient and available for engineering application.
Keywords :
Monte Carlo methods; reliability theory; statistical analysis; Monte Carlo simulation; computer simulation; kriging model; random influential factors; reliability analysis; reliability sensitivity; Computational modeling; Couplings; Force; Random variables; Reliability engineering; Sensitivity; Kriging model; reliability; sensitivity;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Software Engineering and Service Science (ICSESS), 2011 IEEE 2nd International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-9699-0
Type :
conf
DOI :
10.1109/ICSESS.2011.5982297
Filename :
5982297
Link To Document :
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