朱瑞广, 于晓辉, 吕大刚. 基于地震动模拟的一致危险谱和条件均值谱生成及应用[J]. 工程力学, 2015, 32(增刊): 196-201. DOI: 10.6052/j.issn.1000-4750.2014.05.S016
引用本文: 朱瑞广, 于晓辉, 吕大刚. 基于地震动模拟的一致危险谱和条件均值谱生成及应用[J]. 工程力学, 2015, 32(增刊): 196-201. DOI: 10.6052/j.issn.1000-4750.2014.05.S016
ZHU Rui-guang, YU Xiao-hui, LÜ Da-gang. GENERATION AND APPLICATION OF THE UNIFORM HAZARD SPECTRUM AND THE CONDITIONAL MEAN SPECTRUM BASED ON GROUND MOTION SIMULATION[J]. Engineering Mechanics, 2015, 32(增刊): 196-201. DOI: 10.6052/j.issn.1000-4750.2014.05.S016
Citation: ZHU Rui-guang, YU Xiao-hui, LÜ Da-gang. GENERATION AND APPLICATION OF THE UNIFORM HAZARD SPECTRUM AND THE CONDITIONAL MEAN SPECTRUM BASED ON GROUND MOTION SIMULATION[J]. Engineering Mechanics, 2015, 32(增刊): 196-201. DOI: 10.6052/j.issn.1000-4750.2014.05.S016

基于地震动模拟的一致危险谱和条件均值谱生成及应用

GENERATION AND APPLICATION OF THE UNIFORM HAZARD SPECTRUM AND THE CONDITIONAL MEAN SPECTRUM BASED ON GROUND MOTION SIMULATION

  • 摘要: 提出了一种基于地震动模拟的一致危险谱和条件均值谱的生成方法。该方法采用AB95_BC点源模型和基于有限断层的混合震源模型来生成人工模拟地震动,进一步对模拟地震动的反应谱进行统计分析,生成研究地区的一致危险谱及条件均值谱。为说明该文方法,选择缺乏历史地震资料的美国Memphis TN地区作为研究区域,模拟了该地区未来1000年可能发生的地震,并生成该地区50年超越概率为2%一致危险谱及相应的条件均值谱。最后考虑不同调幅方法、匹配均值和标准差等因素的影响,结合贪心优化算法,利用条件均值谱挑选地震动记录。

     

    Abstract: A method is proposed to generate the uniform hazard spectrum (UHS) and the conditional mean spectrum (CMS) based on ground motion simulation. This method adopts the hybrid source model including the AB95_BC point source model and the stochastic finite fault model to generate artificial ground motions. Then the response spectra of the artificial ground motions are used for statistics and the UHS and the CMS are developed for the concerned region. To illustrate the presented method, the region in terms of Memphis TN in US is selected as the concerned region, and the possible ground motions occurring in 1000 years are simulated. Then the UHS with the exceedance probability of 2% in 50 years and the corresponding CMS were generated. Finally, some ground motion records are selected based on the generated CMS in combination with the greedy optimization algorithm with the consideration of different scaling methods and different matching targets: the mean and the standard deviation.

     

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