用天然地震探测青藏高原中部地壳、上地幔结构

从西藏南部的定日、嘎拉至青海铜铁山的天然地震探测剖面,实际路线长约２０００ｋｍ,布设了约１１０台便携地震仪,记录了数百次远震和近震事件,采用多种方法进行了资料处理与解释．依据ＳＫＳ,ＰＫＳ,ｐｓ等横波分裂特征计算的青藏高原中部上地幔的地震各向异性表明：研究区各构造单元内的地震各向异性有明显变化,发现上地幔各向异性快速波的偏振方向与造山带的走向不完全一致．在雅江缝合线、崩错－嘉黎、唐古拉山口、昆仑山口几条断裂带处南、北各向异性出现显著的差异,而金沙江缝合线和班公－怒江缝合线的南、北则没有明显的各向异性变化．由Ｐ波走时残差,利用层析技术反演了４００ｋｍ深度内的速度图像,可以看出近地表１００ｋｍ范围内速度的不均匀变化与地表划分的构造单元很吻合,进一步佐证了青藏高原是由不同时期的微板块拼合而成的认识．在青藏高原中部１５０ｋｍ深度以下发现了多处低速区．在金沙江缝合带下方约２００ｋｍ深度处有一长２５０ｋｍ以上、延伸１５０ｋｍ的低速体,推测可能是一地幔柱．利用ＰＳ转换波划分的界面,显示出青藏高原北部具有低速层和高速层交替出现的地壳结构．     

港口靠船桩工作性状计算的双参数法

港口靠船桩是承受重复性荷载或多循环荷载的一种横向承载桩。双参数法能较好地描述靠船桩 (单桩、群桩 )的桩土工作性状。用双参数法进行计算时 ,所给的地面条件必须由重复荷载或多循环荷载作用下实测出来。根据现场试桩资料 ,标定桩土参数 ,即k =mx1/n的指数l/n、桩土相对柔度系数α、桩土综合刚度EI等值 ,可以用来设计试桩附近局部地区同类条件下的其它长桩。对于没有进行试桩的某些工程 ,可以联合运用双参数法和p -y曲线法进行桩的分析     

冀中坳陷北部河西务断层结构及新近纪以来的活动特征分析

河西务断层是渤海湾盆地冀中坳陷北部地区一条重要的控盆断裂,新近纪-第四纪时期渤海湾盆地整体进入热沉降 阶段后,该断层仍然存在构造活动,2018年在河北永清县发生的地震就是由该断层的活动所引发。文章利用地震数据对河 西务断层的结构特征和新近纪以来的活动特征进行分析,结果表明,河西务断层新近纪以来具有右旋走滑的张扭特征,主 断层在剖面上具有负花状结构,平面上具有分段性,北段和南段兼具右旋走滑和拉张的特征,中段则主要表现为右旋走滑 特征。运动学模型表明,这种分段差异性主要由各段主断层走向和块体走滑运动方向的夹角所决定。     

2022年泸定Ms6.8级地震发震构造与鲜水河断裂带强震迁移规律

2022年9月5日12时52分在四川甘孜州泸定县发生Ms6.8级地震,震源深度16 km。这是继2014年康定地震后,发生在鲜水河断裂带上的又一次强震。笔者等通过已有文献资料,结合鲜水河断裂带南段野外地质调查,统计了滑动速率及历史地震资料,并总结了近代鲜水河断裂带强震迁移规律,对认识鲜水河断裂带活动特征及未来地震危险性具有重要意义。主要得出以下几点认识：①鲜水河断裂带各段滑动速率差异较大,以乾宁为界,从NW至SE段整体上呈现出“先减速后加速”的滑动特点;②泸定地震发震构造磨西断裂,为一次左旋走滑事件;③川滇地区近代历史强震活跃期具有“跳跃性”迁移的特点。自1981年道孚地震后,鲜水河断裂带断进入相对平静期,持续了33 a。自2014年康定地震发生,鲜水河断裂带再次进入地震活跃期;④鲜水河断裂带的强震破裂并非单次地震的“贯通型”模式,而是多次地震的渐进式。断层间相互作用尤其是大地震的发生对断裂带强震复发间隔具有重大影响,相同断裂带的强震也会对后续地震的发生概率产生变化。     

An scientific evaluation of annual earthquake prediction ability

Introduction There have been nearly 40 years for earthquake prediction since the research on earthquake prediction was carried out in plan by some advanced countries since 1960s. For the hard long process of earthquake prediction, Alen, American famous scientist and former president of the evaluation commission of earthquake prediction in California, USA, said that the difficulty of earthquake prediction is more than the expected and the practical progress of earthquake prediction is more sl…     

A distributed parameter model of a frame pin‐supported wall structure

Many reinforced‐concrete frames collapse via a soft‐story mechanism during severe earthquakes. Such collapses are mainly attributed to concentrated deformation in a soft story. Deformation control is thus important in preventing collapse. The frame pin‐supported wall structure is a type of rocking structure that releases constraints at the bottom of the wall. Previous research has obtained good results for the deformation control of this type of structure. However, the interior forces and strength demands of the pin‐supported wall have not been systematically explored. In this paper, a distributed parameter model is developed to investigate the strength demand of the wall in a frame pin‐supported wall structure. In the model, the pin‐supported wall is simplified as a bending beam and the frame is simplified as a shear beam. The two beams are joined by distributed shear connectors, so that the shear force can be transferred at any location on the interface. The model can be solved using differential equations based on equilibrium and compatibility. The accuracy of the model is verified using SAP2000 (Computers and Structures Inc., Berkeley, CA, USA). Displacement distribution of the structure and distributions of the moment and shear force within the pin‐supported wall are obtained for two typical external force profiles. It is found that the pin‐supported wall can effectively reduce the drift concentration factor. Distributions of the displacement, moment, and shear force are closely correlated with the relative stiffness of the wall and frame. Finally, recommendations on the stiffness and strength of a pin‐supported wall are made. Copyright © 2015 John Wiley & Sons, Ltd.     

新疆某水利枢纽工程软弱结构面抗剪强度参数的试验研究

某水利枢纽工程位于伊犁地区,影响工程的主要问题为坝基岩体软弱结构面和断层的抗滑稳定问题。根据工程实际条件和软弱夹层特性,采取现场断层软弱结构面试验和室内模拟试验相结合,获得软弱夹层的抗剪参数。实践证明,把两种方法结合起来的试验成果可靠,尤其对一些不具备进行现场大型岩体软弱夹层抗剪试验的工程,采用室内中型直剪仪进 行剪切试验具有实用意义。     

Possible creep-related tilt precursors obtained in the Central Apennines (Italy) and in the Southern Caucasus (Georgia)

Daily averaged tilt component data from two sites of the Central Apennines (Italy) and of the Southern Caucasus (Georgia), respectively, revealed intermediate-term tilts as possible precursors to earthquakes (M=3.0÷4.7) which occurred in the above-mentioned seismic areas within a distance of 50 km from the sites. A good temporal correlation as well as a fair spatial correspondence between these residual tilts (with amplitude and duration of some microradians and months, respectively) and main shocks were pointed out, by removing both secular trends and seasonal thermoelastic effects from the raw tilts. An attempt was made to justify the above-mentioned results, based on the assumption that the observed intermediate-term preseismic tilts are the manifestation of aseismic creep episodes of comparable duration in the fault materials of thrust faults close to the tilt sites. The mechanism refers to a strain field slowly propagating from the preparation focal area to the tilt site, through crustal blocks separated by weak transition zones. This propagation is thought to be the cause of the local aseismic fault slip recorded by the tiltmeters. Previously, both discrete structures and strain propagation effects were revealed in the Central Apennines and are thought also to exist in the Southern Caucasus. As in the past, the rheological properties of fault materials are revealed as viscoelastic ones. In fact, creep equations obtained by applying several viscoelastic models on our data, proved to fit quite well some of the observed tilt precursors, producing viscosity and rigidity values very similar to those reported in literature.Professor Petr Viktorovich Manjgaladze died during the writing of this paper     

基于卷积神经网络的地震波形智能识别研究

随着世界上多个国家和地区的地震预警系统投入运行,误报和漏报等问题逐渐突显,特别是将标定以及强干扰波形误识别为大震事件,快速、精确地区分地震与其他波形是一个难题。针对于此,该研究提出了基于卷积神经网络地震波形智能识别方法。首先收集并处理了2012—2017年中国境内福建以及周边邻省共683个地震和478个爆破事件,并对这些样本筛选、截取和基线校正等预处理,共得到了27 500条三通道波形。在此基础上,构建了3 s波形输入的卷积神经网络模型(SW-CNN)。结果表明：模型对地震、噪声、爆破和异常波形的识别率分别为97.9、99、99.2和99.3%。相比于人工手动分类识别,该模型更省时和更稳定,为地震预警目前所面临的问题提供了一个新的解决方法。     

Hydrological system analysis and modelling of the Kara River basin (West Africa) using a lumped metric conceptual model

This paper discusses the analysis and modelling of the hydrological system of the basin of the Kara River, a transboundary river in Togo and Benin, as a necessary step towards sustainable water resources management. The methodological approach integrates the use of discharge parameters, flow duration curves and the lumped conceptual model IHACRES. A Sobol sensitivity analysis is performed and the model is calibrated by applying the shuffled complex evolution algorithm. Results show that discharge generation in three nested catchments of the basin is affected by landscape physical characteristics. The IHACRES model adequately simulates the rainfall–runoff dynamics in the basin with a mean modified Nash-Sutcliffe efficiency measure of 0.6. Modelling results indicate that parameters controlling rainfall transformation to effective rainfall are more sensitive than those routing the streamflow. This study provides insights into understanding the catchment’s hydrological system. Nevertheless, further investigations are required to better understand detailed runoff generation processes.

EDITOR M.C. Acreman; ASSOCIATE EDITOR N Verhoest