确定砂土动剪切模量和阻尼比的方法对比

确定土体动剪切模量的常用方法有规范法、Kumar法和自相关函数法,确定相应阻尼比的方法有规范法、Das and Luo法、Kokusho法、Kumar法和互相关函数法,为了分析不同方法所产生差异,实现定量化对比分析,笔者以福建标准砂（粒径为0.5~1.0 mm）为研究对象,采用不排水的应力控制动三轴试验,探讨不同的确定土体动剪切模量和阻尼比方法的差异性,并给出了不同土体条件建议选用的方法。结果表明：1）3种方法确定动剪切模量的结果有一定的差异,随剪应变的增大结果的差异逐渐增大,有效围压对结果的差异性有所影响,当剪应变为4×10^-3,有效围压为100 kPa时,3种方法差异显著,相对误差最大接近20%;2）而5种方法确定阻尼比的结果差异显著,随着剪应变的增大,5种方法确定的阻尼比相对误差大体上均在迅速减小,只有规范法在有效围压为100 kPa时,其相对误差有较小的增大趋势;5种方法中,Kumar法确定的阻尼比最接近平均阻尼比,互相关函数法远高于平均阻尼比,Das and Luo法和Kokusho法确定的阻尼比基本一致但低于平均阻尼比。建议以后的工程应用中,加载方式为应力控制时,可采用自相关函数法确定动剪切模量,采用Kumar法确定阻尼比,二者确定的动剪切模量和阻尼比均最接近平均值。     

Landslide susceptibility zonation method based on C5.0 decision tree and K-means cluster algorithms to improve the efficiency of risk management

Machine learning algorithms are an important measure with which to perform landslide susceptibility assessments,but most studies use GIS-based classification methods to conduct susceptibility zonation.This study presents a machine learning approach based on the C5.0 decision tree(DT)model and the K-means cluster algorithm to produce a regional landslide susceptibility map.Yanchang County,a typical landslide-prone area located in northwestern China,was taken as the area of interest to introduce the proposed application procedure.A landslide inventory containing 82 landslides was prepared and subse-quently randomly partitioned into two subsets:training data(70％landslide pixels)and validation data(30％landslide pixels).Fourteen landslide influencing factors were considered in the input dataset and were used to calculate the landslide occurrence probability based on the C5.0 decision tree model.Susceptibility zonation was implemented according to the cut-off values calculated by the K-means clus-ter algorithm.The validation results of the model performance analysis showed that the AUC(area under the receiver operating characteristic(ROC)curve)of the proposed model was the highest,reaching 0.88,compared with traditional models(support vector machine(SVM)=0.85,Bayesian network(BN)=0.81,frequency ratio(FR)=0.75,weight of evidence(WOE)=0.76).The landslide frequency ratio and fre-quency density of the high susceptibility zones were 6.76/km2 and 0.88/km2,respectively,which were much higher than those of the low susceptibility zones.The top 20％interval of landslide occurrence probability contained 89％of the historical landslides but only accounted for 10.3％of the total area.Our results indicate that the distribution of high susceptibility zones was more focused without contain-ing more"stable"pixels.Therefore,the obtained susceptibility map is suitable for application to landslide risk management practices.     

台风“摩羯”与“温比亚”环流中龙卷小尺度涡旋特征及可预警性分析

利用多普勒天气雷达探测资料,结合常规气象观测资料和天气实况及灾情调查,对2018年8月14日台风“摩羯”（1814）和8月19日台风“温比亚”（1818）产生龙卷的环境物理量及龙卷风暴强度结构特征进行了分析,对诱发龙卷和未诱发龙卷的小尺度气旋性涡旋特征进行了对比。结果表明：两次台风减弱低压东北象限是龙卷发生的关键区,低层高湿,强的低层垂直风切变和大的相对风暴螺旋度是关键物理量;龙卷出现时都伴有ΔV＞20.0 m·s-1的小尺度气旋性涡旋,且基本出现在2.0 km高度以下,但并不是所有这种低层小尺度气旋性涡旋都能诱发龙卷;以ΔV＞20.0 m·s-1为阈值,龙卷识别具有较高的命中率,识别准确率为31.8%,空报率为67.4%,漏报率为6.7%;约35.7%的龙卷没有识别时间提前量,半数龙卷几乎没有预警时间提前量。     

相控震源对地震信号信噪比的改善研究

当测区噪声很强,采用组合震源工作仍然不能满足信噪比要求时,为进一步提高地震勘探信噪比,引入能形成定向地震波的相控震源.针对水平层状介质模型,对组合震源、相控震源地震进行了数值模拟,并定量计算了采用4,8,15,20单元的组合与相控震源地震数据的信噪比,同组合地震相比,相控地震使来自不同反射层的反射波信号的信噪比平均提高了154～990 dB.结果表明,相控震源地震得到的反射波信号信噪比高于组合地震,并且随着激震器数目增加,相控震源合成地震记录中的反射波地震数据信噪比明显提高.     

关于井炮激发参数优化设计的思考

利用正演模拟的手段进行分析,对影响井炮激发的不同影响因素展开分析,结合对炸药特征阻抗与围岩的阻抗匹配系数、炸药几何耦合系数、激发药量、井深等方面进行分析,对井炮激发参数进行优化设计.通过优化设计,寻求有效提高地震子波品质的方法.结合实际的地震地质条件和地震勘探目标,设计最佳的井炮激发参数,提高地震勘探的效益.     

轴压比对中等高度LC结构剪力墙抗震性能的影响

轻骨料混凝土(L ight-we ight concrete,简称LC)剪力墙的轴压比是剪力墙抗震设计时一个重要的控制因素,直接关系到其延性性能。为使设计规程具有足够的理论依据,本文通过对六榀轻骨料混凝土剪力墙试件的试验,研究了在低周反复荷载作用下,着重考虑不同轴压比对中等高度有边框剪力墙的破坏形态和变形性能的影响效应,对其滞回特性进行分析,计算了各剪力墙的刚度退化率与延性系数,并将无竖缝剪力墙与带竖缝剪力墙的抗震性能进行了对比。     

震源机制和场地条件对近场强震地面运动特性的影响

将欧洲数百条地震动记录按震级、震中距、场地类别及震源机制等条件分类,通过对地震动记录加速度峰值比、加速度峰值衰减规律及反应谱比等内容的统计分析,研究了震源机制、场地类别等因素对竖向地震动的影响。结果表明,震源机制和场地类别这两种因素在近场区对竖向地震动特性有显著的影响。     

Landslide susceptibility modeling based on ANFIS with teaching-learning-based optimization and Satin bowerbird optimizer

As threats of landslide hazards have become gradually more severe in recent decades,studies on landslide prevention and mitigation have attracted widespread attention in relevant domains.A hot research topic has been the ability to predict landslide susceptibility,which can be used to design schemes of land exploitation and urban development in mountainous areas.In this study,the teaching-learning-based optimization(TLBO)and satin bowerbird optimizer(SBO)algorithms were applied to optimize the adaptive neuro-fuzzy inference system(ANFIS)model for landslide susceptibility mapping.In the study area,152 landslides were identified and randomly divided into two groups as training(70%)and validation(30%)dataset.Additionally,a total of fifteen landslide influencing factors were selected.The relative importance and weights of various influencing factors were determined using the step-wise weight assessment ratio analysis(SWARA)method.Finally,the comprehensive performance of the two models was validated and compared using various indexes,such as the root mean square error(RMSE),processing time,convergence,and area under receiver operating characteristic curves(AUROC).The results demonstrated that the AUROC values of the ANFIS,ANFIS-TLBO and ANFIS-SBO models with the training data were 0.808,0.785 and 0.755,respectively.In terms of the validation dataset,the ANFISSBO model exhibited a higher AUROC value of 0.781,while the AUROC value of the ANFIS-TLBO and ANFIS models were 0.749 and 0.681,respectively.Moreover,the ANFIS-SBO model showed lower RMSE values for the validation dataset,indicating that the SBO algorithm had a better optimization capability.Meanwhile,the processing time and convergence of the ANFIS-SBO model were far superior to those of the ANFIS-TLBO model.Therefore,both the ensemble models proposed in this paper can generate adequate results,and the ANFIS-SBO model is recommended as the more suitable model for landslide susceptibility assessment in the study area considered due to its excellent accuracy and efficiency.     

唐山7.8级地震前地磁异常的综合分析

利用昌黎等台的磁测资料,并用多种方法进行综合分析,结果显示,在震前出现了约3个月的短期异常,这对于地震的预测预报有一定意义。     

基于分布式检测与决策融合的海底油气管线检漏

利用多传感器的信息融合思想,提出分布式检测与决策融合方法进行长距离海底管线泄漏监测。试验水管和天然气／凝析油管线现场数据分析表明此算法不仅降低了误报警概率,且对流体在输送过程中动态变化具有稳健性。