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基于概率密度演化方法的装配式箱涵构件可靠度研究 被引量:2

Reliability Study of Prefabricated Box Culvert Components Based on Probability Density Evolution Method
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摘要 为提高装配式箱涵构件可靠度分析的计算精度和效率,依托实际工程,基于概率密度演化方法对其进行了研究.首先,建立了装配式箱涵构件的功能函数,推导出功能函数的广义概率密度演化方程,并采用有限差分法进行求解;其次,对求解得到的概率密度函数进行积分,得到构件的失效概率,进而获得相应的可靠指标;最后,与蒙特卡罗法进行对比,分析概率密度演化方法的适用性.研究表明:概率密度演化方法在装配式箱涵构件可靠度的求解过程中,从物理系统与随机系统联系的角度出发,更加充分地考虑了构件参数的随机性和样本点之间的概率联系.该方法与蒙特卡罗法相比可以有效避免随机收敛性,在保证结果唯一的前提下,提高了计算精度和效率. The calculation accuracy and efficiency of reliability analysis of prefabricated box culvert components are studied using the probability density evolution method based on the actual project.Firstly,the function of prefabricated box culvert is established,the generalized probability density evolution equation of the function is derived,and the finite difference method is used to solve the problem.Secondly,the probability density function is integrated to get the failure probability of components,and then the corresponding reliability index is obtained.Finally,it is compared with Monte Carlo method to analyze the applicability of probability density evolution method.The results show that:in the process of solving the reliability of prefabricated box culvert components,the probability density evolution method fully considers the randomness of component parameters and the probability relationship between sample points based on the relationship between physical system and stochastic system.Compared with Monte Carlo method,probability density evolution method can avoid random convergence effectively,and improve the accuracy and efficiency of calculation under the premise of guaranteeing the unique result.
作者 康玉梅 李佳其 刘子傲 于佳月 KANG Yu-mei;LI Jia-qi;LIU Zi-ao;YU Jia-yue(School of Resources&Civil Engineering,Northeastern University,Shenyang 110819,China.)
出处 《东北大学学报(自然科学版)》 EI CAS CSCD 北大核心 2021年第12期1782-1789,共8页 Journal of Northeastern University(Natural Science)
基金 国家自然科学基金资助项目(U1602232).
关键词 概率密度演化方法 装配式箱涵 构件可靠度 蒙特卡罗法 功能函数 probability density evolution method prefabricated box culvert reliability of components Monte Carlo method function
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