摘要
基于全局优化的模拟退火方法,提出了结构可靠性灵敏度分析的自适应重要抽样方法。所提方法由模拟退火来逐步寻找结构最可能失效点,通过逐步优化的最可能失效点来构建可靠性灵敏度分析所需的重要抽样函数。从重要抽样密度函数中抽取样本,来对结构可靠性灵敏度作无偏估计,推导了可靠性灵敏度估计量方差和变异系数的计算公式。与基于Monte-Carlo法的可靠性参数灵敏度分析相比,该方法具有更高的抽样效率,算例证明了所提方法的优越性。
On the basis of the simulated annealing algorithm for global optimization, an adaptive importance sampling method is presented for evaluation of reliability sensitivity. In the presented method, the simulated annealing optimization is employed to seek, in the failure region gradually, the most probable failure point used as the sampling center of the adaptive importance sampling function. The samples generated by ＇the adaptive importance sampling functions are utilized to estimate the reliability sensitivity. The reliability sensitivity evaluation, the variance and the variation coefficient of the evaluation are derived for the adaptive importance sampling based on the reliability sensitivity method. Compared to the Monte-Carlo method through the demonstration of examples, it can be observed that the presented method is more efficient.
出处
《工程力学》
EI
CSCD
北大核心
2008年第4期80-84,共5页
Engineering Mechanics
基金
国家自然科学基金项目(10572117)
新世纪优秀人才支持计划项目(NCET-05-0868)
航空基金项目(2007ZA53012)
关键词
蒙特卡洛法
模拟退火算法
自适应重要抽样
失效概率
可靠性灵敏度
Monte-Carlo method
simulated annealing algorithm
the adaptive importance sampling
failure probability
reliability sensitivity
