Computational modeling of cyclic mobility and post-liquefaction site response

Under seismic excitation, liquefied clean medium to dense cohesionless soils may regain a high level of shear resistance at large shear strain excursions. This pattern of response, known as a form of cyclic mobility, has been documented by a large body of laboratory sample tests and centrifuge experiments. A plasticity-based constitutive model is developed with emphasis on simulating the cyclic mobility response mechanism and associated pattern of shear strain accumulation. This constitutive model is incorporated into a two-phase (solid–fluid), fully coupled finite element code. Calibration of the constitutive model is described, based on a unique set of laboratory triaxial tests (monotonic and cyclic) and dynamic centrifuge experiments. In this experimental series, Nevada sand at a relative density of about 40% is employed. The calibration effort focused on reproducing the salient characteristics of dynamic site response as dictated by the cyclic mobility mechanism. Finally, using the calibrated model, a numerical simulation is conducted to highlight the effect of excitation frequency content on post-liquefaction ground deformations.     

上海地震台阵的地震定位方法

详细介绍了上海地震台阵数据处理软件系统中的地震定位方法，用台阵的聚束方法得到地震的方位角和视慢度，根据统计得到的视慢度－震中距表推算震中距。并结合了地震台网的定位方法，由单台记录的各类主要震相从J－B走时表得到震中距，然后进行地震定位。该定位方法可对近震、远震进行定位处理，并由深震相得到震源深度。     

F-K分析在上海地震台阵建设中的应用

利用F K分析处理地震台阵数据 ,进行地震波场分析 ,按频率分量、速度矢量来分解几乎同时到达台阵的信号 ,识别不同慢度的波 ,有助于地震波类型鉴别研究 .主要讨论了F K分析具体实现的方法和如何应用于上海地震台阵的选址与建设     

北京地区3500a来的气候与环境变迁——兼论昆明湖的沧桑

通过对北京颐和园昆明湖中沉积物的沉积特征的研究,结合历史记载,对昆明湖水域的形成时间和发展过程有了深入的了解,据此对北京地区3500a以来的气候与环境变迁作出了科学的划分,为探讨北京地区未来的气候变化趋势将会有所启迪。     

探地雷达检测道路厚度结构的应用现状及进展

对探地雷达检测道路厚度结构的应用现状进行介绍,分析雷达检测道路厚度结构的物理前提.将探地雷达的道路厚度检测技术与常规的钻孔取芯方法进行对比,并根据笔者在工作中应用的实际情况,说明探地雷达在公路厚度结构检测方面有广阔应用前景.     

探地雷达检测中如何计算速度

雷达波的传播速度随介质而变,这给准确定位探测目标带来了一些困难,因为目标深度取决于速度与讯号反射时间的乘积.但另一方面,利用速度变化与介质的关系,反过来可以推断介质的物质架构.作者结合实用例举了7种求速度的方法,以供使用探地雷达的同行们选用.     

地震台阵滤波及子台分布对聚束效果的影响(Ⅱ)——子台分布及聚束效果的分析

本假设对于确定的相关系数及子台间距存在一个相干波长，将不同频率、震中距的相关性变化的原因归纳为视波长的变化．对近事件而言，几乎不存在相关系数十分理想的子台间距的区间范围．对非理想相关的台阵，应用S．Mykkeltveit等介绍的增益公式来预测台阵的增益，其效果与实际情况吻合的较好．论述了区域台阵与侦察远处事件的台阵有诸多不同之处．     

Statistical tests for regional seismic phase characterizations

In seismic analysis some assumptions are often made aboutthe data, e.g. stationarity and Gaussianity. This is not obvious for all realseismic data. Here, we use statistical tests for characterization of regionalseismic data. We apply tests for stationarity, symmetry, linearity, andtime-reversibility. In the analysis we use twelve regional seismic events inFennoscandia recorded with the seismic small-aperture arrays NORESS,ARCESS and FINESA at hypocentral distances in the range from 160 to1580 km. For the tests we use the regional phases Pn, secondary P, Sn and Lg-phases and the preceding noise. Two of the eventsare explosions, two are rockbursts and eight are earthquakes. Theperformance and possibilities of using statistical tests based on bispectra, asa complementary tool for conventional analysis of seismic phases isdemonstrated. The preceding noise recorded before the first onset of theP-wave for the twelve events is tested to be spatially stationarybetween each channel within each array and temporal stationary in 21consecutive time windows of 3.2 sec each. Also, the preceding noise issymmetric and linear. The seismic phases defined by the symmetry test asnon-Gaussian (not symmetric) are all linear. This means a linear model canbe used to characterize both the noise and the phases. The first P-phase for the two explosions is characterized as non-Gaussian at thethree arrays. For all 36 possibly first P-phase arrivals at the three arraystations, 23 are non-Gaussian. The second P-phase is non-Gaussian at13 of 36 data records, the S-phase at eleven of 36 and the Lg-phase at nine of 36. For all the four phases more than 32 of possible36 are time-reversible.     

Identification of soil degradation during earthquake excitations by Bayesian inference

A Bayesian inference approach is introduced to identify soil degradation behaviours at four downhole array sites. The approach of inference is based on a parametric time‐varying infinite impulse response filter model. The approach is shown to be adaptive to the changes of filter parameters and noise amplitudes. Four sites, including the Lotung (Taiwan), Chiba (Japan), Garner Valley (California), and Treasure Island (California) sites with downhole seismic arrays are analysed. Our results show two major types of soil degradation behaviour: the well‐known strain‐dependent softening, and reduction in stiffness that is not instantaneously recoverable. It is also found that both types of soil degradation are more pronounced in sandy soils than in clayey soils. The mechanism for the second type of soil degradation is not yet clear to the authors and suggested to be further studied. Copyright © 2003 John Wiley & Sons, Ltd.     

A quantitative study of the energy release in the aftershocks of the Bhuj earthquake, 2001, India, using Lg phase

The devastating earthquake on 26 January 2001 at Bhuj, India, resulted in large-scale death and destruction of properties of several million US dollars. The moment magnitude of the earthquake was 7.7 and its maximum focal intensity exceeded X in MM scale. The rate of aftershocks of this earthquake, recorded at Gauribidanur seismic array station (GBA), shows a monotonic decay with time superposed with oscillations. For the Indian continent the Lg phase is a prominent arrival at regional distances. The estimate of Lg amplitude is obtained by optimally fitting the Lg wave train to a exponential decay curve. The logarithm of these amplitudes and logarithm of root mean square (rms) value of actual amplitudes of the Lg are calibrated with USGS m_b to create a local m_bLg magnitude scale. The energy released from these aftershocks is calculated from the rms value of Lg phase. The plot of cumulative energy release with time follows the power law of the form t^p, superposed with oscillations. The exponent of the power law, p, is estimated both by a time-window scanning method and by an interpolation method. The value of p is 0.434 for time-window scanning method and 0.432 for the interpolation method. The predominant periods found in the oscillatory part of the cumulative energy, obtained by differencing the observed from the power law fit, are 10.6, 7.9, 5.4, 4.6 and 3.5 h for time-window scanning method. The corresponding periods for interpolation method are 13.4, 11.5, 7.4, 4.2, 3.5, 2.6 and 2.4 h.