柳春光, 李会军. 多维多点地震激励下随机K8单层球面网壳的可靠度分析[J]. 工程力学, 2010, 27(12): 21-026,.
引用本文: 柳春光, 李会军. 多维多点地震激励下随机K8单层球面网壳的可靠度分析[J]. 工程力学, 2010, 27(12): 21-026,.
LIU Chun-guang, . RELIABILITY ANALYSIS OF K8 SINGLE-LAYER SPHERICAL LATTICE SHELL UNDER MULTI-DIMENSIONAL AND MULTI-SUPPORT EXCITATIONS[J]. Engineering Mechanics, 2010, 27(12): 21-026,.
Citation: LIU Chun-guang, . RELIABILITY ANALYSIS OF K8 SINGLE-LAYER SPHERICAL LATTICE SHELL UNDER MULTI-DIMENSIONAL AND MULTI-SUPPORT EXCITATIONS[J]. Engineering Mechanics, 2010, 27(12): 21-026,.

多维多点地震激励下随机K8单层球面网壳的可靠度分析

RELIABILITY ANALYSIS OF K8 SINGLE-LAYER SPHERICAL LATTICE SHELL UNDER MULTI-DIMENSIONAL AND MULTI-SUPPORT EXCITATIONS

  • 摘要: 大跨度空间钢结构的多维多点抗震分析已有不少研究,但针对其随机反应极值分布的研究甚少。传统的基于跨越理论的方法仅在简单的场合和很强的假定下才可得解析解;而扩散过程理论方法仅在单自由度体系等简单情形下才能使用,基于此,将近年来提出的概率密度演化法引入到多维多点激励下大跨度空间钢结构动力反应极值分布的计算中,该法构造了一个虚拟时间过程,建立概率密度演化方程并求解给出随机结构动力反应的极值分布,在安全域内积分即可给出结构动力可靠度。为验证其效率与精度,应用此法求得了多维多点地震激励下单层球面网壳结构的可靠度与极值分布,与随机模拟结果一致,因此引入的算法具有准确、高效和通用的特点。

     

    Abstract: Although much work has been done on seismic analysis for large span space lattice structures subjected to multi-dimensional multi-support excitations, its extreme value distribution of the stochastic response remains unaddressed. Analytical solutions can be obtained only in simple cases involving strong assumptions using the traditional level-crossing process theory; the diffusion process theory is just feasible for SDOF system. Based on this, the recently developed probability density evolution method is used to capture extreme value of large span space lattice structures subjected to multi-dimensional multi-support excitations. A virtual stochastic process is firstly constructed, then PDEM is built to evaluate extreme value distribution, and dynamic reliability of space structures can be obtained through simple integration. To verify the efficiency and accuracy of the introduced approach, the reliability and extreme value distribution of a long span single layer lattice shell structure under multi-dimensional multi-support excitations are observed. The results agree well with the ones obtained by the stochastic simulation method, so the introduced PDEM is of accuracy, efficiency and versatility.

     

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