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101.
汉源县城位于汶川M_S8.0特大地震六度区内唯一的八度异常区,为典型且罕见的远震高烈度异常区.汉源县城处于流沙河的河流阶地之上,河谷地形对地震震害有显著的影响.为定量分析河谷地形对汶川大地震汉源县高烈度异常的影响,基于汉源县城震害科学考察和场地勘察获取的资料,根据震害分布特征和流沙河谷地形的特点,选取1条实测得到的横切汉源县城并垂直流沙河河谷方向的典型剖面作为计算模型,以脉冲作为基底输入,采用有限差分方法研究了该剖面的场地放大效应,分析了地形对高烈度异常的影响.计算结果表明:汉源县城场地对地震动放大效应的显著频段是1.0~10Hz,且这一频段老县城场地的放大效应比新县城场地显著;汉源老县城场地对汶川M_S8.0地震主震的地震动有显著的放大效应,地表峰值加速度大大超过了抗震设计规范的规定值;汉源场地地形放大效应显著频段与汶川M_S8.0地震的能量集中频段基本吻合,汉源老县城建筑物的自振频率恰恰位于该频段,产生共振效应,从而造成更显著的放大效应,这也是汉源震害异常的主要原因之一.由此可见,河谷地形对地表地震动有重要的影响,在工程选址和抗震设计时应考虑其影响. 相似文献
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宁波地区属浙东南陆相火山岩区,地层在数千米深度内以侏罗系和白垩系的火山碎屑岩(凝灰质粉砂岩为主)及少量熔岩为主。这一套地层总体上孔隙不发育,渗透性极弱,岩石热导率低,属于非地热异常区。地质构造发展的长期地质历史造就了断裂和裂隙系统,该地区地热类型属隆起区断裂深循环型。九龙湖地区采用可控源音频大地电磁测深、氡气和热释汞综合测量及高精度重力等综合物探手段,以寻找孔隙度较高的地层或断裂构造带,对于寻找地热资源起到了很好的效果。分析研究区地表水和地热水的水文地球特征,运用地球化学温标预测地热水温度,表明地层深部可能还赋存有更高温度的热水。 相似文献
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Two great earthquakes occurred in the sea northwest of Sumatra, Indonesia, on December 26, 2004 and March 29,2005. The observation of water levels in Yunnan yielded abundant information about the two earthquakes. This paper presents the water level response to the two earthquakes in Yunnan and makes a preliminary analysis. It is observed that the large earthquake- induced abnormal water level change could be better recorded by analog recording than by digital recording. The large earthquake-caused water level rise or decline may be attributed to the effect of seismic waves that change the stress in tectonic units, and is correlated with the geological structure where the well is located. The water level response mode in a well is totally the same for earthquakes occurring on the same fault and with the same fracture mode. The only difference is that the response amplitude increases with the growth of the earthquake magnitude. 相似文献
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The deep learning method has made nurnerials achievements regarding anomaly detection in the field of time series. We introduce the speech production model in the field of artificial intelligence, changing the convolution layer of the general convolution neural network to the residual element structure by adding identity mapping, and expanding the receptive domain of the model by using the dilated causal convolution. Based on the dilated causal convolution network and the method of log probability density function, the anomalous events are detected according to the anomaly scores. The validity of the method is verified by the simulation data, which is applied to the actual observed data on the observation staion of Pingliang geoeletric field in Gansu Province. The results show that one month before the Wenchuan MS8.0, Lushan MS7.0 and Minxian-Zhangxian MS6.6 earthquakes, the daily cumulative error of log probability density of the predicted results in Pingliang Station suddenly decreases, which is consistent with the actual earthquake anomalies in a certain time range. After analyzing the combined factors including the spatial electromagnetic environment and the variation of micro fissures before the earthquake, we explain the possible causes of the anomalies in the geoelectric field of before the earthquake. The successful application of deep learning in observed data of the geoelectric field may behefit for improving the ultilization rate both the data and the efficiency of detection. Besides, it may provide technical support for more seismic research. 相似文献
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Significant anomalies were observed at the geomagnetic stations in the southwest region of China before the Yingjiang MS6.1 earthquake and the Ludian MS6.5 earthquake in 2014. We processed the geomagnetic vertical component diurnal variation data by the spatial correlation method. The results show that during the period from April 1 to May 20, 2014,there existed quasi-synchronous decrease changes in the coefficient curves between the five geomagnetic stations of Guiyang,Hechi,Nanshan,Muli,Yongning and Xinyi and Hongshan stations.Furthermore,there was a high gradient zone in the normalized correlation coefficient contour map with background values removed. The epicenters of the Yingjiang MS6.1 earthquake and the Ludian MS6.5 earthquake are located in the gradient zone or near the gradient zone. 相似文献
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简要介绍2020年伽师M S6.4地震周围地质构造背景,研究分析了M S6.4地震前新疆地区和柯坪块体地震活动状态、区域地震活动图像特征。结果表明:①本次地震前1~2年和震前半年,新疆境内中强和中小地震呈现“平静—成组活跃”或显著增强特征;②本次地震发生在柯坪块体M S≥6.0地震平静近15年的背景下,震前区域地震活动存在时间渐进的中短期异常特征,即震前2年,5级以上地震活动呈现NE向有序条带分布;震前1年南天山西段小震群累积月频度呈现“加速”活动特征;震前半年震区附近4级地震条带形成共扼分布特征;震前3个月震区附近出现地震窗超限异常;震前2个月震区附近地区视应力呈现显著高值异常;③震前地震活动具有较好的“长、中、短”期异常配套出现的特征。 相似文献