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《Journal of East China Shipbuilding Institute(Natural Science Edition)》 2003-03
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An Adaptive Important Sampling Method Based on Markov Chain Sample Simulation Algorithm

WU Jiancheng,WU Jianguo,WU Yage(Dept.of Naval Architecture and Civil Eng.,East China Shipbuilding Institute,Zhenjiang Jiangsu 212003,China)  
Importance sampling method,which is commonly used in the reliability analysis of structures and requires the socalled 'the most probable point'or design point'to be known before applyingimportance sampling techniqueto determine the failure probability, may cause difficulties and lose its conveniencein calculation when there are multidesign points existing in the failure region or applied to system reliability analysis, and will result in ludicrousdeviation from precise value. In this paper, an adaptive importance sampling method has been developedto overcome this drawback, which is mainly based on Markov chain samples simulation algorithm according to Metropolis criterionto populate the higher probability density zones in the failure region and get the distributioninformation of these areas, thena general importance sampling method is introduced to calculate the failure probability with the mean and standard deviation of priorsamples. For not needing to determine the multi-design points that are in system reliabilityanalysis,it is particularly suitable for structural system reliability calculation. Finally,this paper gives some examples, which take the failure modes of series and parallel systems into account, to verify itsaccuracy and efficiency.
【Fund】: 船舶行业基金项目(院编2000102)
【CateGory Index】: TU311.2
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