Study and review on crust-mantle velocity structure in Bohai Bay and its vicinity

Introduction Bohai Bay, along with its adjacent areas, is one of the seismically active areas in North China. Understanding its crust/upper-mantle structural characteristics and lateral heterogeneity of the medium in this area is of great significance to the study of seismogenic environment, thus improvimg the level of earthquake prediction. For years, scientists have studied the area by gravity and magnetic methods (FENG, et al, 1989), geothermal field (WU, et al, 1988; TIAN, ZHANG, 19…     

Application of genetic BP network to discriminating earthquakes and explosions

Introduction Artificial Neural Network (ANN) is an important branch of artificial intelligence. It is proposed on the foundation of the study on modern neural science, is a man-made network that can implement some functions based on the mans comprehensive understanding for cerebral neural network (HAN, WANG, 1997). ANN is a mathematical model of simplified human brain neural network and is used to simulate the structures and functions of human brain neural network. ANN is a complex netw…     

Estimation of azimuth and slowness of tele-seismic signals recorded by a local seismic network

Introduction The azimuth and slowness are two major features of seismic signals. The accurate estimation of them is quite important for both phase identification and event location. Generally, there are two types of seismic stations, i.e. 3-component stations (3C) and arrays. To estimate the two direc-tional parameters, the polarization analysis (Jurkevics, 1988) is commonly used for 3C stations and the frequency-wavenumber spectrum analysis ( f-k) (Capon, 1969; Kvaerna, Doornbos, 1986) is …     

有限弹性变形地壳中的地震波

地壳由半无限大的基岩上一层厚度为H^-的表土层组成，入射地震波为垂直的SH波，产生水平地面运动。当浅源大地震发生时，在极震区以外行波传播产生地面运动将使地壳介质有非线性的有限弹性变形。用小参数摄动法使非线性控制方程为线性化的小参数各阶控制方程，得出头两阶线性控制方程的解析解。     

Fuzzy neural network models for liquefaction prediction

Integrated fuzzy neural network models are developed for the assessment of liquefaction potential of a site. The models are trained with large databases of liquefaction case histories. A two-stage training algorithm is used to develop a fuzzy neural network model. In the preliminary training stage, the training case histories are used to determine initial network parameters. In the final training stage, the training case histories are processed one by one to develop membership functions for the network parameters. During the testing phase, input variables are described in linguistic terms such as ‘high’ and ‘low’. The prediction is made in terms of a liquefaction index representing the degree of liquefaction described in fuzzy terms such as ‘highly likely’, ‘likely’, or ‘unlikely’. The results from the model are compared with actual field observations and misclassified cases are identified. The models are found to have good predictive ability and are expected to be very useful for a preliminary evaluation of liquefaction potential of a site for which the input parameters are not well defined.     

《CT理论与应用研究》杂志新刊标和地幔速度模型的说明

在《ＣＴ理论与应用研究》杂志１９９４~２００１年本杂志“刊标”的基础上,在其上方增加了象征三维体视学成像的三角形四面体的透视图;该刊标的右下侧为医学断面成像扫描仪(包括各种Ｘ－ＣＴ机与核磁共振ＭＲＩ扫描仪等);其左下侧为三维地幔速度模型和地球核的示意图,切出有两个地幔剖面,表示纵波速度二维变化的剖面。该速度剖面系根据赵大鹏教授的理论和计算方法,按照地球上的两个大圆弧做计算和绘制的彩色图,排在本期封４:第一大圆弧,从北极经西巴基斯坦(２８°Ｎ, ６４°Ｅ)到马尔代夫群岛(３°Ｎ,７３°Ｅ);第二大圆弧从马尔代夫群岛点(３°Ｎ,７３°Ｅ)连接巴布新几内亚之南点(１２°Ｓ,１５０°Ｅ),来计算两剖面速度分布并作图的结果,其具体分布参见封４的两条彩色剖面和相应的地理位置图。由于赵教授这篇论文[１]在中国国内只有很少数图书馆收藏,在Ｅｌｓｅｖｉｅｒ Ｓｃｉｅｎｃｅ的ＥＰＳＬ网站上一般人只能查到摘要,本刊对于该地幔速度模型的制作方法和所用数据资料,该模型的优越性和特征进行了叙述,他所用的地震事件数目,多达７１２８个;用于层析反演成像的震相到时数多到近一百万条。该速度如下的特点:在所采用的速度结构中,包含用几个复杂形状的地质速度界面,如莫霍面,以及下沉板块的分界     

桥梁隔震体系振动台试验研究(III)——测试结果分析

根据前文所述的测试结果 ,本文主要分析了隔震构造、橡胶支座水平刚度、地震输入频谱特性、地震烈度、输入方向、桥墩高度、桥墩嵌固程度等因素对隔震效果的影响 ,揭示了隔震体系耗散地震能量输入的机理 ,所得出的结论对工程实践具有指导意义。     

3D shear-wave velocity structure of the Eifel plume, Germany

The Quaternary Eifel volcanic fields, situated on the Rhenish Massif in Germany, are the focus of a major interdisciplinary project. The aim is a detailed study of the crustal and mantle structure of the intraplate volcanic fields and their deep origin. Recent results from a teleseismic P-wave tomography study reveal a deep low-velocity structure which we infer to be a plume in the upper mantle underneath the volcanic area [J.R.R. Ritter et al., Earth Planet. Sci. Lett. 186 (2001) 7-14]. Here we present a travel-time investigation of 5038 teleseismic shear-wave arrivals in the same region. First, the transverse (T) and radial (R) component travel-time residuals are treated separately to identify possible effects of seismic anisotropy. A comparison of 2044 T- and 2994 R-component residuals demonstrates that anisotropy does not cause any first-order travel-time effects. The data sets reveal a deep-seated low-velocity anomaly beneath the volcanic region, causing a delay for teleseismic shear waves of about 3 s. Using 3773 combined R- and T-component residuals, an isotropic non-linear inversion is calculated. The tomographic images reveal a prominent S-wave velocity reduction in the upper mantle underneath the Eifel region. The anomaly extends down to at least 400 km depth. The velocity contrast to the surrounding mantle is depth-dependent (from −5% at 31-100 km depth to at least −1% at 400 km depth). At about 170-240 km depth the anomaly is nearly absent. The resolution of the data is sufficient to recover the described features, however the anomaly in the lower asthenosphere is underestimated due to smearing and damping. The main anomaly is similar to the P-wave model except the latter lacks the ‘hole’ near 200 km depth, and both are consistent with an upper mantle plume structure. For plausible anhydrous plume material in the uppermost 100 km of the mantle, an excess temperature as great as 200-300 K is estimated from the seismic anomaly. However, 1% partial melt reduces the required temperature anomaly to about 100 K. The temperature anomaly associated with the deeper part of the plume (250 to about 450 km depth) is at least 70 K. However, this estimate is quite uncertain, because the amplitude of the shear-wave anomaly may be larger than the modelled one. Another possibility is water in the upwelling material. The gap at 170-240 km depth could arise from an increase of the shear modulus caused by dehydration processes which would not affect P-wave velocities as much. An interaction of temperature and compositional variations, including melt and possibly water, makes it difficult to differentiate quantitatively between the causes of the deep-seated low-velocity anomaly.     

ARTIFICIAL NEURAL NETWORK CORRECTION OF ROUGH ERRORS OF OBSERVATIONS*

In the context of tower measured radiation datasets.following the correction principle meeting a diagnostic equation in data quality control and in terms of a technique for model construction on data and ANN (artificial neural network) retrieval for BP correction of radiation measurements with rough errors available,a BP model is presented.Evidence suggests that the developed model works well and is superior to a convenient multivariate linear regression model,indicating its wide applications.     

辽宁省地震前兆台网技术改造概述

“九五”期间实施的《辽宁省地震前兆台网技术改造项目》使辽宁省地震前兆观测技术系统由模拟到数字实现了质的飞跃，本文对项目的技术思路，实施情况，取得的成果及建设特色进行了介绍。