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考虑非高斯特性的结构首次失效时间计算
引用本文:何军,严再春. 考虑非高斯特性的结构首次失效时间计算[J]. 计算力学学报, 2008, 25(4)
作者姓名:何军  严再春
作者单位:上海交通大学,船舶海洋与建筑工程学院,土木工程系,上海,200240;上海交通大学,船舶海洋与建筑工程学院,土木工程系,上海,200240
摘    要:本文发展了一个计算具有非高斯特性的结构首次失效时间的解析方法.该方法利用Hemite矩模型将非高斯结构反应映射为标准高斯过程,由此计算反应的平均超越率、成群超越以及初始状态的影响,并最终给出结构的首次失效时问概率.二次力函数激励下线性单自由度系统的首次失效时间分析说明了该方法的使用过程,同时对该方法的计算结果与Monte Carlo模拟结果进行了对比.

关 键 词:首次失效时间  非高斯结构反应  超越率  Hermite矩模型  平均群超尺寸  初始条件

Structural first failure time under non-gaussian stochastic behavior
HE Jun,YAN Zai-chun. Structural first failure time under non-gaussian stochastic behavior[J]. Chinese Journal of Computational Mechanics, 2008, 25(4)
Authors:HE Jun  YAN Zai-chun
Abstract:The main focus of this paper is the development of an analytical moment-based procedure for calculating structural first failure time probabilities under non-Gaussian stochastic behavior.In the procedure,Hermite moment models based on structural response moments(skewness,kurtosis,etc.) are used to map a non-Gaussian structural response into a standard Gaussian process,and then the mean up-crossing rate of the original response process for a critical level is estimated from the mapped standard Gaussian process.Through introducing the mean clump size and the probability of instantaneous failure of the original structural response process for a critical level,the procedure can account for effects of clumping and initial conditions in the problem of structural first failure time.The procedure,therefore,can be used to estimate structural first failure time probabilities under non-Gaussian stochastic behavior.An analysis of a linear SDOF system excited by a quadratic forcing function demonstrates how the procedure is used for the structures considered,Moreover,comparisons between the results from the procedure and those from the Monte Carlo simulation method are performed in order to show the accuracy and effectiveness of the procedure.
Keywords:first failure time  non-Gaussian structural response  up-crossing rate  hermite moment models  mean clump size  initial condition
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