基岩倾角对盆地地震响应的影响分析

为了研究盆地基岩倾角对盆地地表动力反应的影响,选取了一个跨度2 km,深度500 m的二维成层盆地为研究对象进行有限元动力反应分析。以持时0.25 s的狄拉克脉冲作为输入地震动,探讨了P波和SV波垂直入射时,盆地基岩倾角从10°\,20°\,30°\,40°依次增加的情况下盆地地震反应。结果表明:入射波在倾斜基岩处发生波型转化,同时产生面波,在盆地中心区域发生汇聚;随着基岩倾角的增加地表中心处的卓越频率有减小的趋势。     

高地应力V级围岩相似材料研制及岩体开挖卸载模型试验分析

以黄土、砂为骨料,石膏、水泥为胶结材料,水为调节剂,以正交试验方法配制出V级围岩相似材料,该材料能够很好的模拟隧道Ⅴ级软弱围岩。在此基础上,以钢筒模型试验为媒介,通过千斤顶配合反力架加载,观察不同材料配比下的试验组应力变化斜率、自稳时间、应变大小等方面的差异,结合加载完成后模型开口处岩体变化情况,探索高地应力下Ⅴ级围岩开挖卸载效应。试验结果表明:虽然相似材料会因配比不同改变物理力学性质,但主要是对弹性模量的影响较大;在增大垂直压力作用下,试验中材料自稳时间变长,应力释放也较为彻底,但整体趋势放缓。     

Efficient risk assessment of lifeline networks under spatially correlated ground motions using selective recursive decomposition algorithm

For effective hazard mitigation planning and prompt-but-prudent post-disaster responses, it is essential to evaluate the reliability of infrastructure networks accurately and efficiently. A nonsimulation-based algorithm, termed as a recursive decomposition algorithm (RDA), was recently proposed to identify disjoint cut sets and link sets and to compute the network reliability. This paper introduces a ‘selective’ RDA, which preferentially identifies critical disjoint cut sets and link sets to calculate the probabilities of network disconnection events with a significantly reduced number of identified sets. To this end, the original RDA is improved by replacing the shortest path algorithm with an algorithm that identifies the most reliable path, and by using a graph decomposition scheme based on the probabilities associated with the subgraphs. The critical sets identified by the algorithm are also used to compute conditional probability-based importance measures that quantify the relative importance of network components by their contributions to network disconnection events. This paper also introduces a risk assessment framework for lifeline networks based on the use of the selective RDA, which can consider both interevent and intraevent uncertainties of spatially correlated ground motions. The risk assessment framework and the selective RDA are demonstrated by a hypothetical network example, and the gas and water transmission networks of Shelby County in Tennessee, USA. The examples show that the proposed framework and the selective RDA greatly improve efficiency of risk assessment of complex lifeline networks, which are characterized by a large number of components, complex network topology, and statistical dependence between component failures. Copyright © 2012 John Wiley & Sons, Ltd.     

竖向地震动对大跨度高断面Y形柱地铁车站地震响应分析研究

以北京地铁6号线新华大街站公共区Y型柱地铁车站为工程背景,利用FLAC3D有限差分程序数值模拟分析,研究超浅埋大跨度、高断面、Y形柱地铁车站结构分别在仅输入水平向地震动和同时输入水平向与竖向地震动情况下的地震响应特性。结果表明:(1)与仅输入单向地震动相比,双向地震动耦合作用下车站各测点的峰值加速度和应力值均增大,而相对水平位移减小,且随着输入地震动强度的增加,竖向地震动影响率呈递减趋势;(2)双向地震动作用下,同一工况Y形柱叉支处各测点的竖向位移明显增大,且各测点的竖向位移值较为均匀,而单向水平地震动作用下各测点竖向位移差异较大;(3)与单向水平地震动相比,竖向地震动的输入对各测点间的水平方向地震动特性规律影响较小。     

2014年云南鲁甸地震和景谷地震的震害对比研究

2014年8月3日云南鲁甸发生MS6.5地震,10月7日云南景谷发生MS6.6地震。这2次地震的震级、地震类型、震源深度等相差不大,但地震所造成的人员伤亡、房屋建筑损毁程度、地震地质灾害等却相差很大。在地震现场调查资料的基础上,对比分析地震造成的崩塌、滑坡、地裂缝、砂土液化、房屋建筑损毁等灾害轻重差别的主要原因。研究表明,鲁甸地震灾区地质构造复杂,地层破碎,人口密度大,房屋建筑抗震性能差;而景谷地震灾区地质环境较好,植被茂密,人口密度低,相比同量级地震的加速度小,房屋建筑结构抗震性能较好。总体而言,鲁甸MS6.5地震的震害比景谷MS6.6地震要严重得多。     

Polarimetric scattering model for estimation of above ground biomass of multilayer vegetation using ALOS-PALSAR quad-pol data

Forests are important biomes covering a major part of the vegetation on the Earth, and as such account for seventy percent of the carbon present in living beings. The value of a forest’s above ground biomass (AGB) is considered as an important parameter for the estimation of global carbon content. In the present study, the quad-pol ALOS-PALSAR data was used for the estimation of AGB for the Dudhwa National Park, India. For this purpose, polarimetric decomposition components and an Extended Water Cloud Model (EWCM) were used. The PolSAR data orientation angle shifts were compensated for before the polarimetric decomposition. The scattering components obtained from the polarimetric decomposition were used in the Water Cloud Model (WCM). The WCM was extended for higher order interactions like double bounce scattering. The parameters of the EWCM were retrieved using the field measurements and the decomposition components. Finally, the relationship between the estimated AGB and measured AGB was assessed. The coefficient of determination (R²) and root mean square error (RMSE) were 0.4341 and 119 t/ha respectively.     

A framework for the evaluation of ground motion selection and modification procedures

This study develops a framework to evaluate ground motion selection and modification (GMSM) procedures. The context is probabilistic seismic demand analysis, where response history analyses of a given structure, using ground motions determined by a GMSM procedure, are performed in order to estimate the seismic demand hazard curve (SDHC) for the structure at a given site. Currently, a GMSM procedure is evaluated in this context by comparing several resulting estimates of the SDHC, each derived from a different definition of the conditioning intensity measure (IM). Using a simple case study, we demonstrate that conclusions from such an approach are not always definitive; therefore, an alternative approach is desirable. In the alternative proposed herein, all estimates of the SDHC from GMSM procedures are compared against a benchmark SDHC, under a common set of ground motion information. This benchmark SDHC is determined by incorporating a prediction model for the seismic demand into the probabilistic seismic hazard analysis calculations. To develop an understanding of why one GMSM procedure may provide more accurate estimates of the SDHC than another procedure, we identify the role of ‘IM sufficiency’ in the relationship between (i) bias in the SDHC estimate and (ii) ‘hazard consistency’ of the corresponding ground motions obtained from a GMSM procedure. Finally, we provide examples of how misleading conclusions may potentially be obtained from erroneous implementations of the proposed framework. Copyright © 2014 John Wiley & Sons, Ltd.     

Intensity measures for probabilistic assessment of non‐structural components acceleration demand

A fundamental issue in the framework of seismic probabilistic risk analysis is the choice of ground motion intensity measures (IMs). Based on the floor response spectrum method, the present contribution focuses on the ability of IMs to predict non‐structural components (NSCs) horizontal acceleration demand. A large panel of IMs is examined and a new IM, namely equipment relative average spectral acceleration (E‐ASA_R), is proposed for the purpose of NSCs acceleration demand prediction. The IMs efficiency and sufficiency comparisons are based on (i) the use of a large dataset of recorded earthquake ground motions; (ii) numerical analyses performed on three‐dimensional numerical models, representing actual structural wall and frame buildings; and (iii) systematic statistical analysis of the results. From the comparative study, the herein introduced E‐ASA_R shows high efficiency with respect to the estimation of maximum floor response spectra ordinates. Such efficiency is particularly remarkable in the case of structural wall buildings. Besides, the sufficiency and the simple formulation allowing the use of existing ground motion prediction models make the E‐ASA_R a promising IMs for seismic probabilistic risk assessment. Copyright © 2015 John Wiley & Sons, Ltd.     

Comparison of 1D linear,equivalent-linear,and nonlinear site response models at six KiK-net validation sites

Vertical seismometer arrays represent a unique interaction between observed and predicted ground motions, and they are especially helpful for validating and comparing site response models. In this study, we perform comprehensive linear, equivalent-linear, and nonlinear site response analyses of 191 ground motions recorded at six validation sites in the Kiban–Kyoshin network (KiK-net) of vertical seismometer arrays in Japan. These sites, which span a range of geologic conditions, are selected because they meet the basic assumptions of one-dimensional (1D) wave propagation, and are therefore ideal for validating and calibrating 1D nonlinear soil models. We employ the equivalent-linear site response program SHAKE, the nonlinear site response program DEEPSOIL, and a nonlinear site response overlay model within the general finite element program Abaqus/Explicit. Using the results from this broad range of ground motions, we quantify the uncertainties of the alternative site response models, measure the strain levels at which the models break down, and provide general recommendations for performing site response analyses. Specifically, we find that at peak shear strains from 0.01% to 0.1%, linear site response models fail to accurately predict short-period ground motions; equivalent-linear and nonlinear models offer a significant improvement at strains beyond this level, with nonlinear models exhibiting a slight improvement over equivalent-linear models at strains greater than approximately 0.05%.     

Multifractal characteristic analysis of near-fault earthquake ground motions

This study aims to reveal the multi-scaling behavior and quantify the irregularity of near-fault earthquake ground motions from a new perspective of multifractal theory. Based on multifractal detrended fluctuation analysis, the multifractal characteristic parameters of acceleration time series for typical near-fault ground motions are calculated, and their correlations with two period parameters (i.e., mean period T_m and characteristic period T_c) and box-counting fractal dimensions are analyzed. Numerical results of strong nonlinear dependence of generalized Hurst exponents h(q) upon the fluctuation orders q indicate that near-fault ground motions present the multifractal properties and long-range correlation obviously. Furthermore, the scaling exponent h(2) of near-fault records has a strong correlation with their periods T_m and T_c, and strongly negative correlation with their box dimension. Moreover, h(2) can be regarded as a measure of frequency content and irregularity degree of strong earthquake ground motions. Finally, it is pointed out that the long-range correlation of small and large fluctuation is the major source of multifractality of near-fault ground motions.