非独立平稳脉冲载荷过程在高门限上的极值指标和最大值
The Extremal Index and the Maximum of a Dependent Stationary Pulse Load Process Observed above a High Threshold
摘要：
在结构可靠性分析中，观察高阈值以上的载荷过程，将其建模为具有随机发生时间和幅度的脉冲过程，并从数据中推断寿命最大或设计载荷是一项常见的任务。在本文中，我们考虑一个平稳的活荷载序列，到达根据一个依赖的点过程，并允许一个削弱的混合型依赖的负载脉冲幅度，渐近减少到零，增加分离的序列。在模型中包含相关性消除了由独立同分布引入的不必要的保守性。在确定最大活荷载分布时，常作独立同分布的假定。的加载过程的波动的规模被用来识别集群的高阈值以上，这反过来又被用来估计的极值指数的过程。贝叶斯更新的经验分布函数，从分布的顺序统计量在一个依赖的平稳序列，进行。脉冲到达时刻被建模为由平稳对数正态强度控制的Cox过程。一个说明性示例利用在大容量公路桥上收集的环境交通的在役峰值应变数据，并分析最大载荷的渐进行为。
英文摘要：
Observing a load process above high thresholds, modeling it as a pulse process with random occurrence times and magnitudes, and extrapolating life-time maximum or design loads from the data is a common task in structural reliability analyses. In this paper, we consider a stationary live load sequence that arrive according to a dependent point process and allow for a weakened mixing-type dependence in the load pulse magnitudes that asymptotically decreases to zero with increasing separation in the sequence. Inclusion of dependence in the model eliminates the unnecessary conservatism introduced by the i.i.d. (independent and identically distributed) assumption often made in determining maximum live load distribution. The scale of fluctuation of the loading process is used to identify clusters of exceedances above high thresholds which in turn is used to estimate the extremal index of the process. A Bayesian updating of the empirical distribution function, derived from the distribution of order statistics in a dependent stationary series, is performed. The pulse arrival instants are modeled as a Cox process goverened by a stationary lognormal intensity. An illustrative example utilizes in-service peak strain data from ambient traffic collected on a high volume highway bridge, and analyzes the asymptotic behavior of the maximum load.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
