Simulating earthquake ground motion at a site, for given intensity and uncertain source location
Simulating earthquake ground motion at a site, for given intensity and uncertain source location
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在给定强度和不确定震源位置的情况下模拟现场地震地面运动
DOI：
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发表时间：
2001
期刊：
影响因子：
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通讯作者：
O. Diaz
中科院分区：
文献类型：
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作者：
J. Alamilla;L. Esteva;J. Garcia;O. Diaz
根据另一篇文章，地震期间的地震动加速度时程可以被描述为具有演化频率内容和瞬时强度的非平稳随机过程的实现。表征这些过程的参数可以作为不确定变量处理，其概率分布取决于每个地震事件的震级和相应的震源到站点的距离。因此，对于给定强度的地震，人工地震动加速度时程的有限样本的生成被表示为两个阶段的蒙特卡罗模拟过程。第一阶段包括对地震地面运动随机过程模型的参数集样本进行模拟。第二阶段包括时间历史本身的模拟，给定相关随机过程模型的参数。为了说明后一个参数的概率分布对震级和震源到站点距离的依赖性，对于给定的地震动强度值，必须得到这些变量的联合条件概率分布。这是通过求助于贝叶斯定理关于交替假设的概率来实现的。提出了地面运动时程条件模拟的两种方法。更精细的方法是利用有关震级和距离条件分布的所有信息来模拟地震动随机过程模型的统计参数值。第二种选择考虑所有集中在震级和距离的最可能组合上的概率，这些震级和距离对感兴趣的地点的地震危害有重大影响。
Following a companion article, ground motion acceleration time historiesduring earthquakes can be described as realizations of non-stationarystochastic processes with evolutionary frequency content and instantaneousintensity. The parameters characterizing those processes can be handled asuncertain variables with probabilistic distributions that depend on themagnitude of each seismic event and the corresponding source-to-sitedistance. Accordingly, the generation of finite samples of artificial groundmotion acceleration time histories for earthquakes of given intensities isformulated as a two-stage Monte Carlo simulation process. The first stageincludes the simulation of samples of sets of the parameters of thestochastic process models of earthquake ground motion. The second stageincludes the simulation of the time histories themselves, given theparameters of the associated stochastic process model. In order to accountfor the dependence of the probability distribution of the latter parameterson magnitude and source-to-site distance, the joint conditional probabilitydistribution of these variables must be obtained for a given value of theground motion intensity. This is achieved by resorting to Bayes Theoremabout the probabilities of alternate assumptions.Two options for the conditional simulation of ground motion time historiesare presented. The more refined option makes use of all the informationabout the conditional distribution of magnitude and distance for thepurpose of simulating values of the statistical parameters of the groundmotion stochastic process models. The second option considers allprobabilities concentrated at the most likely combination of magnitude anddistance for each of the seismic sources that contribute significantly to theseismic hazard at the site of interest.