共查询到20条相似文献，搜索用时 687 毫秒
1.
考虑地震荷载的随机性及强度、频率的非平稳性,基于作者提出的适用于非平稳随机过程的一般随机地震动模型,采用虚拟激励法,建立了非平稳随机地震反应分析方法,并将其应用于某实际均质土坝动力分析中。土石坝及坝基体系采用整体有限元离散,坝体和坝基材料的动力非线性性能以等效线性化方法考虑。首先,基于目标加速度时程的强度和能量信息,确定了作为输入的加速度时—频演变功率谱密度;其次,比较了确定性时程动力分析和非平稳随机分析的结果,探讨了频率非平稳随机地震激励下的土石坝地震反应特性;最后,比较了2种不同坝基条件下的土石坝非平稳随机地震反应,探讨了频率非平稳随机激励下的土石—坝基动力相互作用。分析结果表明：地震动的频率非平稳性对土石坝动力反应有一定影响;坝体—坝基动力相互作用在地震过程中的不同阶段表现有所不同,主震阶段的相互作用显著。 相似文献
2.
设计用随机地震动的模型及其参数确定 总被引：51，自引：21，他引：51
本文假定基岩地震动为“马尔柯夫”有色谱,通过地表覆盖土层的滤波,修正了金井清的随机地震动模型。文中从工程抗震设计的应用角度出发,利用随机极值理论和强震记录统计分析的结果,确定了随机地震动模型的参数(平稳持时、谱强度因子和非平稳强度函数)与地震烈度和场地类别的定量关系以及直接与震级、震中距和场地类别的定量关系。本文提出的随机地震动修正模型和确定的模型参数直接为工程结构的随机地震反应分析和动力可靠性设计提供了初步可用的随机地震动荷载设计标准。 相似文献
3.
地震动非平稳性与幅值谱和相位差谱的关系 总被引：9，自引：1，他引：9
本文将地震动时程视为非平稳的随机过程，通过将其分解为一系列窄频带波包的方法，讨论了地震动强度及频率非平稳性与幅值谱和相应差谱的关系，并着重分析了相位差谱及其均值和对地震动非平稳性作用的机制。 相似文献
4.
本文在对实际地震加速度记录统计分析的基础上,给出了能够合理描述地震动强度非平稳特性的参数及其取值范围;然后引入实验设计方法,建立了适合于地震动强度非平稳特性参数分析的实验设计算法,用来分析地震动强度非平稳特性参数的变化对结构响应的影响;最后通过与近似技术相结合,建立了地震动强度非平稳特性参数与结构响应之间的近似定量关系模型.结果表明,本文提出的实验设计方法适合于对地震动强度非平稳特性参数进行分析,该方法在有效地减小计算量的同时,获得了结构响应与参数变化之间的对应关系.基于实验设计方法进行的特性参数方差分析结果表明:地震动的稳态持时对结构地震响应的影响比较显著;对于周期较小的结构,特性参数之间的交互作用对结构地震响应的影响显著,但当周期大于1 s时,则不显著.本文建立的近似定量关系模型能够较好地反映不同特性参数、不同周期结构动力响应之间的联系,为工程实践中基于结构特性合理设置地震动特性参数、合成或挑选地震加速度时程提供理论依据. 相似文献
5.
在平稳地震动过程的Clough-Penzien功率谱基础上,采用林家浩非均匀调制函数建立全非平稳地震动过程的演变功率谱。根据我国现行的《建筑抗震设计规范》进行全非平稳地震动演变功率谱的参数识别研究。应用非平稳随机过程模拟的谱表示-随机函数方法,生成建筑结构抗震设计所用地震动的代表性样本集合。通过代表性样本集合的二阶统计值及地震反应谱与目标值的拟合比较,验证本文方法的有效性。最后结合概率密度演化方法,进行以层间位移角为控制准则的结构随机地震反应分析与抗震可靠度计算。 相似文献
6.
7.
本文基于与物理随机模型相对应的随机Fourier谱,通过对地震动非平稳性及其所受影响机制的分析,建立了非平稳地震动合成的新方法。通过引入基本相位差谱,并将初始相角视为随机变量,以相位差谱的分布特性、随机地震动的统计特征以及对结构随机反应的影响为原则,利用计算机程序生成相位差谱,提出了基于随机Fourier谱的合成地震动方法。同时,利用快速FFT技术提高合成精度。根据本文提出的合成方法获得的地震动具有非平稳特性,将为后续研究工作提供合理的地震动加速度时程。 相似文献
8.
基于物理的随机地震动模型研究 总被引：15，自引：0，他引：15
基于物理联系研究地震动随机性,建立了随机地震动与基底输入傅氏谱、场地固有圆频率和场地等价阻尼比之间的物理关系,从随机傅氏谱函数角度描述了地震动随机过程的随机性本质。结合Ⅳ类工程场地的实测地震动记录资料,由数值方法识别了给出基本随机变量的概率分布参数。与实测记录对比表明,本文建立的随机地震动模型具有明确的物理概念,可充分反映地震动的变异性特征。 相似文献
9.
地震动的强度,一般用烈度或地面峰值加速度、地面峰值速度等地震动参数表示。但是,地面运动是一种典型的非平稳信号,幅值和频率成分均随时间变化,瞬时的幅值最大值并不能完全代表其破坏能力。 相似文献
10.
本文详细论述了功率谱与功率谱密度、平方和SS与平方平均值MS的适用范围及物理意义,比较深入地分析了平稳和非平稳加速度时间历程的统计特征,通过引入时域包线获取特定相位的方法,考虑了非平稳特性。本文基于非平稳时间历程,在不考虑频率非平稳性的基础上,提出了设计地震动三要素:(1)平方和SS;(2)归一化自相关函数或其对应的功率谱;(3)地震动时域包线.本文提出了在设计地震动合成中考虑超随机特性的实用方法,并指出地震动的超随机特性(即归一化功率谱的锯齿状波动部分,或归一化自相关函数的随机噪声部分)与相位的随机性是地震动随机特性的两个重要方面。本文将地震动的统计分析直接建立在非平稳时间历程的基础之上,从而避开了要对地震动进行平稳化处理的困难。这样提取出的地震动统计特征完全是以真实地震动记录为基础的。应用这些统计特征,可模拟出符合统计要求的基于非平稳时间历程的设计地震动。最后本文还讨论了工程上常用的将反应谱近似转换为功率谱的转换式的一些缺陷。 相似文献
11.
随机方法在地震烈度速报中的应用 总被引：1，自引：0，他引：1
我国地震监测台网间距大,很难实现大震发生时地震烈度分布图的快速编制.基于随机方法,利用历史小震数据反演地震动估计模型的参数,参考地震发生时获取的少量强震动数据,选取合适的震源参数,正演地震动场的分布.根据地震烈度与地震动参数的经验关系,实现地震烈度速报.本方法可以模拟大震的近断层地震动特征,对高烈度区的判断较目前常用的烈度速报方法更为合理.研究成果既可以用于首张烈度分布图的发布,还能够用于地震烈度的动态修正. 相似文献
12.
A method to combine probabilistic seismic hazard analysis and stochastic earthquake motion models is presented. A set of parameters characterizing stochastic earthquake motion models is determined on a consistent probabilistic basis. The method proposed herein consists of two steps. First, the ground motion intensity is determined in the context of the conventional hazard curve technique. Next, other ground motion parameters such as duration, predominant frequency and spectral shape parameters are determined as conditional means corresponding to the annual probability of exceedance for the ground motion intensity. Some example applications are presented. 相似文献
13.
利用谐小波变换对实际强震记录的时变谱进行估计,并统计分析了远场3类不同场地上地震波的时变谱特征,分析发现对于硬场地上的远场地震波在时域内平稳段较短,下降段衰减较快,而在频域内则具有较大的中心频率和较宽的频带.利用均匀调制非平稳模型和时变修正Kanai-Tajimi非平稳模型模拟地震波的时变谱,把非线性函数的参数识别问题转化成求解无约束优化问题,利用拟牛顿迭代法求得最优解,得到3类不同场地上这两种模型的参数具体取值以及参数函数集的具体表达式.为了定量地确定模拟模型的精度,定义了误差函数,验证了所提时变谱参数识别方法的精度,给出了与建筑抗震规范相对应的不同场地不同烈度下多遇和罕遇地震的谱强度因子的大小.最后提出了利用求解时变线性微分方程组来合成非平稳地震波的方法. 相似文献
14.
Influence of time‐varying frequency content in earthquake ground motions on seismic response of linear elastic systems 
下载免费PDF全文
下载免费PDF全文 Earthquake ground motion records are nonstationary in both amplitude and frequency content. However, the latter nonstationarity is typically neglected mainly for the sake of mathematical simplicity. To study the stochastic effects of the time‐varying frequency content of earthquake ground motions on the seismic response of structural systems, a pair of closely related stochastic ground motion models is adopted here. The first model (referred to as ground motion model I) corresponds to a fully nonstationary stochastic earthquake ground motion model previously developed by the authors. The second model (referred to as ground motion model II) is nonstationary in amplitude only and is derived from the first model. Ground motion models I and II have the same mean‐square function and global frequency content but different features of time variation in the frequency content, in that no time variation of the frequency content exists in ground motion model II. New explicit closed‐form solutions are derived for the response of linear elastic SDOF and MDOF systems subjected to stochastic ground motion model II. New analytical solutions for the evolutionary cross‐correlation and cross‐PSD functions between the ground motion input and the structural response are also derived for linear systems subjected to ground motion model I. Comparative analytical results are presented to quantify the effects of the time‐varying frequency content of earthquake ground motions on the structural response of linear elastic systems. It is found that the time‐varying frequency content in the seismic input can have significant effects on the stochastic properties of system response. Copyright © 2016 John Wiley & Sons, Ltd. 相似文献
15.
A method for generating a suite of synthetic ground motion time‐histories for specified earthquake and site characteristics defining a design scenario is presented. The method employs a parameterized stochastic model that is based on a modulated, filtered white‐noise process. The model parameters characterize the evolving intensity, predominant frequency, and bandwidth of the acceleration time‐history, and can be identified by matching the statistics of the model to the statistics of a target‐recorded accelerogram. Sample ‘observations’ of the parameters are obtained by fitting the model to a subset of the NGA database for far‐field strong ground motion records on firm ground. Using this sample, predictive equations are developed for the model parameters in terms of the faulting mechanism, earthquake magnitude, source‐to‐site distance, and the site shear‐wave velocity. For any specified set of these earthquake and site characteristics, sets of the model parameters are generated, which are in turn used in the stochastic model to generate the ensemble of synthetic ground motions. The resulting synthetic acceleration as well as corresponding velocity and displacement time‐histories capture the main features of real earthquake ground motions, including the intensity, duration, spectral content, and peak values. Furthermore, the statistics of their resulting elastic response spectra closely agree with both the median and the variability of response spectra of recorded ground motions, as reflected in the existing prediction equations based on the NGA database. The proposed method can be used in seismic design and analysis in conjunction with or instead of recorded ground motions. Copyright © 2010 John Wiley & Sons, Ltd. 相似文献
16.
在Vlachos等提出的双模态时变修正Kanai-Tajimi功率谱模型及其参数识别方法的基础上,利用杜修力等提出的Kanai-Tajimi功率谱滤波方法并引进遗传算法及二次优化识别技术进行改进,建立地震动时变功率谱的参数模型化方法。通过集集地震波的时变功率谱模型参数识别及模拟地震动算例,验证改进后的双模态时变修正Kanai-Tajimi功率谱模型的可行性和有效性,其方法可运用到重大工程结构抗震分析的设计地震动输入中。 相似文献
17.
A method for generating an ensemble of orthogonal horizontal ground motion components with correlated parameters for specified earthquake and site characteristics is presented. The method employs a parameterized stochastic model that is based on a time‐modulated filtered white‐noise process with the filter having time‐varying characteristics. Whereas the input white‐noise excitation describes the stochastic nature of the ground motion, the forms of the modulating function and the filter and their parameters characterize the evolutionary intensity and nonstationary frequency content of the ground motion. The stochastic model is fitted to a database of recorded horizontal ground motion component pairs that are rotated into their principal axes, a set of orthogonal axes along which the components are statistically uncorrelated. Model parameters are identified for each ground motion component in the database. Using these data, predictive equations are developed for the model parameters in terms of earthquake and site characteristics and correlation coefficients between parameters of the two components are estimated. Given a design scenario specified in terms of earthquake and site characteristics, the results of this study allow one to generate realizations of correlated model parameters and use them along with simulated white‐noise processes to generate synthetic pairs of horizontal ground motion components along the principal axes. The proposed simulation method does not require any seed recorded ground motion and is ideal for use in performance‐based earthquake engineering. Copyright © 2011 John Wiley & Sons, Ltd. 相似文献
18.
震后快速产出的震动烈度分布是地震应急救援非常有效的依据, 通常由烈度与地震动参数的经验关系给出. 有台站的场点, 地震动参数可以直接由台站数据给出确定性的结果; 而无台站的场点, 地震动参数只能由衰减关系给出估计值. 目前我国台站覆盖有限, 且难于实时获取, 快速生成的地震动参数主要依赖于地震动衰减关系, 再依据烈度与地震动参数的经验关系, 输出确定性的震动烈度分布. 由于衰减关系本身存在着不确定性, 将其估计值用于生成确定性的震动烈度分布是不准确的. 而且实践证明, 震动烈度与实际调查烈度存在差异. 鉴于此, 从衰减关系模型中的ε出发, 提出了场点(城镇)遭遇不同烈度的概率计算方法: 利用衰减关系的估计值与衰减关系的标准差, 构造峰值加速度(PGA)变化的对数正态分布, 然后以烈度分档对应的PGA范围, 计算震区各城镇遭遇不同烈度的概率及各城镇抗震设防烈度被超越的概率. 具体以1966年3月8日河北邢台MS6.8地震为例, 说明了此方法的可行性, 认为以概率形式给出城镇可能遭遇的烈度在表述上更为合理, 并建议将场点(城镇)遭遇烈度的概率表达方法用于震害快速评估. 相似文献
19.
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. 相似文献
20.
Best estimate seismic analysis are generally based on time‐domain simulations of structural responses. The seismic load is then modeled by a stochastic process representing ground motion. For this purpose, the analyst can use recorded accelerograms or work with synthetically generated ones. The number of ground motion time‐histories available for a given scenario and site condition is limited and generally not sufficient for carrying out more advanced probabilistic structural response analysis. It is then necessary to have at our disposal methods that allow for generating synthetic accelerograms that realistically characterize earthquake ground motions. However, most of the methods proposed in literature for generating synthetic accelerograms do not accurately reproduce the natural variability of ground motion parameters (such as PGA, cumulative absolute velocity, and Arias intensity) observed for recorded time histories. In this paper, we introduce a new method for generating synthetic ground motion, based on Karhunen‐Loève decomposition and a non‐Gaussian stochastic model. The proposed method enables the structural analyst to simulate ground motion time histories featuring the properties mentioned above. To demonstrate its capability, we study the influence of the simulation method on different ground motion parameters and on soil response spectra. We finally compute fragility curves to illustrate the practical application of the proposed method. Copyright © 2012 John Wiley & Sons, Ltd. 相似文献