中文摘要：

采用Monte Carlo模拟手段,提出描述场地土层特性变异性对传递函数变异性影响的分析方法。选取日本Kik-Net强震数据库中软(FKSH14)、硬(FKSH12)两类场地,建立场地概率模型。应用Monte Carlo技术随机生成50组场地剖面,分别计算场地的传递函数STF及STF标准差,讨论场地土层厚度、剪切波速,以及二者组合情况下场地传递函数的标准差及场地特征频率的变化。结果显示:对于硬土场地而言,场地特征频率标准差相对于软土场地较大,且剪切波速变异性影响比土层厚度变异性的影响略大,而二者组合工况下最大;而软土场地,土层厚度、剪切波速变化工况下场地特征频率的标准差相当,比二者组合工况下略低;软、硬两类场地,土层厚度与剪切波速二者组合工况下STF的标准差比单一量变化情况下略大,但3种工况下场地STF标准差相差不明显;场地STF的标准差在场地自振频率附近的频率段取值较大,极值点与场地STF的极值点相对应。

英文摘要：

Adopting Monte Carlo simulation technique, a method for describing the variability of site transfer function (STF) with respect to the variability of site characteristic parameters is proposed. Two Kik-Net seismic strong-motion stations, which were installed on hard ground (FKSH12) and soft site (FKSH14) in Japan, were selected and corresponding probability site models were established. 50 site soil profiles were randomly generated for hard ground and soft site via Monte Carlo simulation;and then the STFs were calculated as well their standard deviations, respectively. The standard deviations of STFs and the site characteristic frequencies were discussed in three cases, i.e. varying subsoil thicknesses (case I), varying subsoil shear wave velocities (case II), and varying subsoil thickness and shear wave velocities (case III). The results show that:the standard deviations of site characteristic frequencies of hard ground is overall larger than those of soft site;the standard deviation of site characteristic frequency of hard ground is the smallest in case I, followed by case II, while in case III the standard deviation of site characteristic frequency is the largest; the standard deviations of soft site characteristic frequencies in case I and case II are comparative but weakly smaller than that in case III;the standard deviations of STFs in case III for soft site and hard ground are slightly larger than those in case I and case II;but the standard deviations in the three cases are not considerably different;the standard deviations of STF are fairly large in the vicinity of site predominant frequencies with peak values corresponding to peak values of relevant mean STF.