花岗岩风化料弃土快速堆填过程中不排水抗剪强度评估

沿海沿江城市地下开挖产生的工程渣土含泥量大、含水率高且较松散,主要运往渣土场进行堆填处置。由于产量巨大而处置场地有限,许多渣土场在运营过程中存在堆填速度快、缺乏排水设施、超高超库容堆填等问题,容易引发堆填体失稳事故。目前对于非饱和工程渣土堆体在快速堆填过程中的失稳机制认识尚不清晰,尤其是对这一过程中的高饱和度工程渣土强度增长规律缺乏足够的认识。以深圳红坳渣土场填料——花岗岩风化料(CDG)填土为研究对象,对不同初始饱和度土样进行三轴不排水不排气等向压缩和剪切试验,结果表明:非饱和CDG填土不排水抗剪强度随围压增大呈非线性增长,增长速率与试样初始饱和度密切相关;当土样压缩后的饱和度超过0.7,不排水强度随围压的增长速率显著降低。基于有效固结应力法的原理,结合Hilf孔压公式和修正剑桥模型,提出了一种工程渣土不排水抗剪强度估算方法,并通过与试验结果对比验证了该方法对初始饱和度高于0.6的CDG填土的适用性。利用该方法确定的不排水强度cu与正应力σn的关系可应用于高饱和度工程渣土快速堆填中的稳定性分析。     

节理分布空间变异的地下洞室稳定性概率分析

以岩土材料力学参数空间变异性的"点估计-有限元"分析方法为基础,结合节理分析时自身存在几何模型、网格划分等特性,扩展了该方法在节理分布空间变异性分析方面的适用性,明确了具体的研究步骤与方法。以某抽水蓄能水电站为例,通过分析节理空间变异性对围岩变形与塑性区的影响,验证了扩展后该方法的准确性和合理性。对工程案例开挖揭露的1400余条节理进行概率统计,建立了节理空间变异性的有限元分析模型;采用扩展后的概率分析方法,研究了节理分布对地下洞室群围岩开挖稳定性的影响。研究结果表明:(1)对比概率分析得到的围岩变形概率分布与现场监测结果,发现剔除变形异常点后监测变形量值大部分位于得到的位移概率分布范围内,说明节理的空间变异性是导致监测变形波动的主要影响因素;(2)围岩变形概率分布的标准差能有效识别出围岩开挖变形受节理空间变异性的影响程度,对于所给出的案例依次为:机窝>边墙>顶拱;(3)围岩塑性区的概率分区能合理判断地下洞室群开挖时受节理影响较大的区域和范围,为工程施工的支护设计提供依据。     

微束分析测试技术十年(2011~2020)进展与展望

现代地球科学研究的重大突破在很大程度上取决于观测和分析技术的创新。新世纪以来,我国地球科学领域引进了一批高性能新型微束分析仪器设备,建立了一批高规格的实验室。本文回顾了近十年来微束分析技术与方法的主要进展及其在地球科学研究中的应用实例,包括电子探针、扫描电镜、透射电镜、大型离子探针、纳米离子探针、飞行时间二次离子质谱、激光剥蚀等离子体质谱、激光诱导原子探针、原子探针技术、显微红外光谱、同步辐射等,这些分析技术的进步和广泛应用极大地提高了我们对地球和行星演化历史及许多地质过程的理解。今后,应加快微束分析的新技术、新方法和新标准的开发,特别是高水平人才队伍建设,提高创新能力并在国际学术舞台上发挥重要作用。     

利用滩坝砂体规模研究古风力的定量恢复*

古风力是一项重要的古气候指标,其定量恢复是一个难题。风作用于水体产生的波浪大小间接地反映了风力,能够为古风力的恢复提供思路。发育于破浪带和冲浪回流带的破浪沙坝、沿岸沙坝分别记录了破浪和冲浪过程,作者分别介绍利用古湖泊中发育的破浪沙坝和沿岸沙坝进行古波况和古风力恢复的原理和操作流程。(1)根据破浪沙坝的几何形态,可以将其厚度与破浪水深建立函数关系,而破浪水深又由破浪波高决定,因此破浪沙坝厚度可以恢复破浪波高,据此可以进一步根据波浪统计关系恢复有效波高、根据风浪关系恢复风力。此方法依托以下3个参数: 单期次的破浪沙坝厚度、破浪沙坝的基座坡角、古风程。(2)沿岸沙坝厚度近似记录了冲浪的极限高度,后者受控于有效波高,据此也可以恢复有效波高和风力。此方法依托以下5个参数: 单期次的沿岸沙坝厚度、古(平均)水深、古风程、古风向相对于岸线的入射角、组成沿岸沙坝的沉积物粒度。上述2种方法综合性较强,涉及古风向、古地形坡度、风程或盆地直径、古水深等参数的恢复,需要综合运用古地貌恢复、去压实校正、古岸线识别、古水深恢复等技术,并需要结合波浪理论。古湖泊滨岸带地层中保存有大量的滩坝沉积,利用其恢复古波况和古风况具有一定的应用前景,能够有助于更详细地重建沉积盆地的古地理背景。     

Brittleness index predictions from Lower Barnett Shale well-log data applying an optimized data matching algorithm at various sampling densities

The capability of accurately predicting mineralogical brittleness index(BI)from basic suites of well logs is desir-able as it provides a useful indicator of the fracability of tight formations.Measuring mineralogical components in rocks is expensive and time consuming.However,the basic well log curves are not well correlated with BI so correlation-based,machine-learning methods are not able to derive highly accurate BI predictions using such data.A correlation-free,optimized data-matching algorithm is configured to predict BI on a supervised basis from well log and core data available from two published wells in the Lower Barnett Shale Formation(Texas).This transparent open box(TOB)algorithm matches data records by calculating the sum of squared errors be-tween their variables and selecting the best matches as those with the minimum squared errors.It then applies optimizers to adjust weights applied to individual variable errors to minimize the root mean square error(RMSE)between calculated and predicted(BI).The prediction accuracy achieved by TOB using just five well logs(Gr,pb,Ns,Rs,Dt)to predict BI is dependent on the density of data records sampled.At a sampling density of about one sample per 0.5 ft BI is predicted with RMSE～0.056 and R2～0.790.At a sampling density of about one sample per 0.1 ft BI is predicted with RMSE～0.008 and R2～0.995.Adding a stratigraphic height index as an additional(sixth)input variable method improves BI prediction accuracy to RMSE～0.003 and R2～0.999 for the two wells with only 1 record in 10,000 yielding a BI prediction error of＞±0.1.The model has the potential to be applied in an unsupervised basis to predict BI from basic well log data in surrounding wells lacking mineralogical measure-ments but with similar lithofacies and burial histories.The method could also be extended to predict elastic rock properties in and seismic attributes from wells and seismic data to improve the precision of brittleness index and fracability mapping spatially.     

宁波地区空气质量及大气自净能力海陆差异对比

以镇海、奉化分别作为宁波沿海和内陆空气质量代表站。基于代表站2013-2017年污染物资料和2015年12月至2017年2月冬季激光雷达资料,对比分析宁波地区沿海和内陆站点的空气质量差异;利用NCEP的GDAS(Global Data Assimilation System)资料和ERA-Interim高分辨率再分析资料评估两地气溶胶来源及大气自净能力差异。结果表明:宁波沿海和内陆地区中度及以上污染主要集中于冬季,冬季首要污染物以PM2.5为主;镇海NO2浓度较奉化显著偏高,而两地PM2.5 和PM10 浓度差异较小。冬季镇海和奉化3km以下都存在消光系数大的气溶胶集中层,镇海3km内消光系数平均值较奉化偏高约40%。两地中度及以上污染时,镇海和奉化的气溶胶粒子主要来自宁波西北方向的内陆地区,比例分别为90%和63%,镇海地区其余10%左右来自近距离低空偏东气流的输送,而奉化地区有37%来自浙江西南部的短距离输送。冬季当宁波地区出现区域性优和中度以上污染时,浙江北部沿海分别盛行东北风和西北风,空气质量优时混合层内平均风速大于中度以上污染时。浙江省大气自净能力比值呈自西北向东南减小,宁波地区优等空气质量大气自净能力约为中度以上污染的 1.5倍。大气自净能力在不同空气质量等级下差异显著,可作为大气污染发生、发展和消退判定的参考依据。     

Response of ocean dynamics to multiple equilibria of the Kuroshio path South of Japan

Variability of the Kuroshio path to the south of Japan plays a central role in the local climate change and exerts tremendous influences on the local atmosphere and ocean. In this study, the response of ocean dynamics, in terms of the eddy kinetic energy (EKE), potential vorticity (PV), relative vorticity, and eddy-mean flow interaction, to the Kuroshio path change is discussed. Kuroshio path south of Japan includes the near-shore non-large meander (nNLM), the off-shore non-large meander (oNLM), and the typical large meander (tLM). Analyses reveal that the distribution of EKE, PV, relative vorticity, and energy exchange between the eddy field and the mean flow respectively varies with the Kuroshio path: (1) The tLM has the maximum EKE along the path; (2) The positive and negative PV are located at the onshore and offshore side of Kuroshio axis, respevetively; (3) The distributions of anomalous relative voritcity of nNLM, oNLM, and tLM are consistent with sea surface height anomalies (SSHAs); (4) The tLM has the largest energy exchange between the eddy field and the mean flow in terms of the rate of barotropic energy conversion. On the other hand, the stability analysis of ocean currents suggests that the three Kuroshio paths south of Japan have their own intrinsic properties of the instability.     

Climate change perceptions and their individual-level determinants: A cross-European analysis

There is now an extensive literature on the question of how individual-level factors affect climate change perceptions, showing that socio-political variables, notably values, worldviews and political orientation, are key factors alongside demographic variables. Yet little is known about cross-national differences in these effects, as most studies have been conducted in a single or small number of countries and cross-study comparisons are difficult due to different conceptualisations of key climate change dimensions. Using data from the European Social Survey Round 8 (n = 44,387), we examine how key socio-political and demographic factors are associated with climate change perception across 22 European countries and Israel. We show that human values and political orientation are important predictors of climate change beliefs and concern, as are the demographics of gender, age, and education. Certain associations with climate change perceptions, such as the ones for the self-transcendence versus self-enhancement value dimension, political orientation, and education, are more consistent across countries than for gender and age. However, even if the direction of the associations are to a large extent consistent, the sizes of the effects are not. We demonstrate that the sizes of the effects are generally smaller in Central and Eastern European countries, and that some demographic effects are larger in Northern European as compared to Western European countries. This suggests that findings from one country do not always generalize to other national contexts.     

基于ARMA模型的广元市中区经济增长预测分析

利用广元市市中区1978年到2004年GDP数据,构建了广元市市中区时间序列趋势的ARMA模型.在此基础上,对广元市市中区2006年到2010年未来5年内的GDP进行了预测,并针对该区"十一五"规划的各项目标任务提出了一些对策建议,为广元市市中区未来的发展提供参考依据.     

PARAMETER AND VARIANCE ESTIMATION IN GEOTECHNICAL BACKANALYSIS USING PRIOR INFORMATION

A probabilistic framework to perform inverse analysis of geotechnical problems is presented. The formulation allows the incorporation of existing prior information on the parameters in a consistent way. The method is based on the maximum likelihood approach that allows a straightforward introduction of the error structure of field measurements and prior information. The difficulty of ascribing definite values to the uncertainties associated with the various types of observations is overcome by including the corresponding variances in the set of parameters to be identified. The inverse analysis results in a minimization problem that is solved by coupling the optimization technique to the finite element method. Two examples are presented to illustrate the performance of the method. The first one corresponds to a synthetic case simulating the excavation of a tunnel. Young's modulus, K₀ value and measurements variances are identified. The second case concerns the excavation of a large underground cavern in which again Young's modulus and K₀ are identified. It is shown that introduction of prior information permits the estimation of parameters more consistent with all available informations that include not only monitored displacements but also results from in situ tests carried out during the site investigation stage.