| NUMERICAL SIMULATION ALGORITHM FOR RELIABILITY ANALYSIS OF COMPLEX STRUCTURAL SYSTEM BASED ON INTELLIGENT OPTIMIZATION |
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| 作者姓名： | LU Zhenzhou LIU Chengli FU Lin School of Aeronautics Northwestern Polytechnical University Xi'an China |
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| 作者单位： | LU Zhenzhou LIU Chengli FU Lin School of Aeronautics，Northwestern Polytechnical University，Xi'an 710072，China |
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| 基金项目： | 国家自然科学基金;山西省自然科学基金 |
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| 摘 要： | An efficient importance sampling algorithm is presented to analyze reliability of complex structural system with multiple failure modes and fuzzy-random uncertainties in basic variables and failure modes. In order to improve the sampling efficiency, the simulated annealing algorithm is adopted to optimize the density center of the importance sampling for each failure mode, and results that the more significant contribution the points make to fuzzy failure probability, the higher occurrence possibility the points are sampled. For the system with multiple fuzzy failure modes, a weighted and mixed importance sampling function is constructed. The contribution of each fuzzy failure mode to the system failure probability is represented by the appropriate factors, and the efficiency of sampling is improved furthermore. The variances and the coefficients of variation are derived for the failure probability estimations. Two examples are introduced to illustrate the rationality of the present method. Comparing with the direct Monte-Carlo method, the improved efficiency and the precision of the method are verified by the examples.
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| 关 键 词： | 重要性抽样 模拟退火算法 人工智能 优化 复合结构系统 可靠性分析 |
NUMERICAL SIMULATION ALGORITHM FOR RELIABILITY ANALYSIS OF COMPLEX STRUCTURAL SYSTEM BASED ON INTELLIGENT OPTIMIZATION |
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| LU Zhenzhou LIU Chengli FU Lin School of Aeronautics,Northwestern Polytechnical University,Xi''''an ,China.NUMERICAL SIMULATION ALGORITHM FOR RELIABILITY ANALYSIS OF COMPLEX STRUCTURAL SYSTEM BASED ON INTELLIGENT OPTIMIZATION[J].Chinese Journal of Mechanical Engineering,2006,19(1):67-71. |
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| Authors: | LUE Zhenzhou LIU Chengli FU Lin |
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| Abstract: | An efficient importance sampling algorithm is presented to analyze reliability of complex structural system with multiple failure modes and fuzzy-random uncertainties in basic variables and failure modes. In order to improve the sampling efficiency, the simulated annealing algorithm is adopted to optimize the density center of the importance sampling for each failure mode, and results that the more significant contribution the points make to fuzzy failure probability, the higher occurrence possibility the points are sampled. For the system with multiple fuzzy failure modes, a weighted and mixed importance sampling function is constructed. The contribution of each fuzzy failure mode to the system failure probability is represented by the appropriate factors, and the efficiency of sampling is improved furthermore. The variances and the coefficients of variation are derived for the failure probability estimations. Two examples are introduced to illustrate the rationality of the present method. Comparing with the direct Monte-Carlo method, the improved efficiency and the precision of the method are verified by the examples. |
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| Keywords: | Importance sampling Simulated annealing algorithm Randomness Fuzziness |
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