基于WBS-RBS的地铁基坑故障树风险识别与分析

针对地铁基坑工程环境复杂、影响因素多的特点,提出以故障树分析为基础结合工作分解结构（WBS）-风险分解结构（WBS）进行风险识别的方法。此方法引入WBS-RBS将地铁基坑工程工作分解结构和风险源分解结构耦合判断并说明相应风险因素或风险事件,并按照故障树建树原则根据彼此间的逻辑关系,用逻辑门连接上下层事件,形成地铁基坑工程主要故障树。在此基础上,对风险因素进行敏感性分析并提出相应的预防措施。     

麻江古油藏油源识别与油气运聚分析：来自油气地球化学的证据

充分考虑热演化过程中烃源岩干酪根、族组分、固体沥青及正构烷烃碳同位素相互关系及变化规律,通过地球化学分析并结合前人碳同位素及芳烃标志物研究进行综合分析,结果表明古油藏各区域储层早期均存在下寒武统黑色泥岩来源,后期来源有较大差别,麻江古背斜以南各地沥青均不同程度与中寒武统都柳江组有关,北凯里液态原油及油苗为五峰组及龙马溪组印支期成藏产物,其保存环境为储层早期成岩过程中形成的独立封闭系统。在油源识别的基础上,结合构造地质背景、油气成藏条件及流体活动规律分析,认为黔南坳陷及邻区下寒武统、都柳江组、五峰组及龙马溪组烃源岩的分布控制了该区油气富集规律,黔南海西期断裂系统与加里东运动形成的不整合面构成不同期次油气运聚的输导系统,海西期形成的一系列正断裂是麻江古油藏成藏的关键。     

Groundwater contaminant source identification based on iterative local update ensemble smoother

Identification of the location and intensity of groundwater pollution source contributes to the effect of pollution remediation, and is called groundwater contaminant source identifcation. This is a kind of typical groundwater inverse problem, and the solution is usually ill-posed. Especially considering the spatial variability of hydraulic conductivity field, the identification process is more challenging. In this paper, the solution framework of groundwater contaminant source identification is composed with groundwater pollutant transport model (MT3DMS) and a data assimilation method (Iterative local update ensemble smoother, ILUES). In addition, Karhunen-Loève expansion technique is adopted as a PCA method to realize dimension reduction. In practical problems, the geostatistical method is usually used to characterize the hydraulic conductivity feld, and only the contaminant source information is inversely calculated in the identifcation process. In this study, the identification of contaminant source information under Kriging K-field is compared with simultaneous identification of source information and K-field. The results indicate that it is necessary to carry out simultaneous identification under heterogeneous site, and ILUES has good performance in solving high-dimensional parameter inversion problems.     

Threshold of motion of bivalve and gastropod shells under oscillatory flow in flume experiments

The threshold of motion of non-fragmented mollusc shells was studied for the first time under oscillatory flow. In this regard, flume experiments were used to investigate the threshold of motion of three bivalve and three gastropod species, two typical mollusc classes of coastal coquina deposits. The sieve diameters ranged from 2·0 to 15·9 mm. These experiments were performed on a flat-bottom setup under regular non-breaking waves (swell) produced by a flap-type wave generator. The critical Shields values for each species of mollusc were plotted against the sieve and nominal diameter. Moreover, the dimensionless Corey shape factor of the shells was evaluated in order to investigate the effect of mollusc shell shapes on the threshold of motion. According to their critical Shields parameter, the mollusc threshold data under oscillatory flow present smaller values than the siliciclastic sediments when considering their sieve diameter. In addition, the mollusc datasets are below the empirical curves built from siliciclastic grain data under current and waves. When considering the nominal diameter, the critical Shields parameter increases and the mollusc data are closer to siliciclastic sediments. Bivalves, which have a flat-concave shape (form factor: 0·27 to 0·37), have a higher critical Shields parameter for smaller particles and more uniform datasets than the gastropod scattered data, which have a rounded shape (form factor: 0·58 to 0·62) and have varied morphologies (ellipsoidal, conical and cubic). The comparison between previous current-driven threshold data of bioclastic sediment motion and the data of mollusc whole shells under oscillatory flow shows a fair correlation on the Shields diagram, in which all datasets are below the mean empirical curves for siliciclastic sediments. These findings indicate that the shape effect on the transport initiation is predominant for smaller shells. The use of the nominal diameter is satisfactory to improve the bioclastic and siliciclastic data correlation.     

多源遥感数据在新疆卡拉麦里地区岩矿识别中的应用

遥感技术广泛应用于地质基础调查、矿产资源勘探、环境评估和地质灾害调查等方面。它已从多光谱发展到高光谱阶段,Landsat- 8是目前最具有代表性和最常用的多光谱数据,ASTER具有高的分辨率和多波段特征,资源一号02D(ZY1- 02D)卫星是我国2019年发射的高光谱业务卫星。为了更好地了解多源遥感数据在岩矿识别中的作用,在新疆东天山卡拉麦里地区进行了相关研究。结果表明：Landsat- 8 OLI的PCA变换结果清晰识别了研究区不同的岩性和地层;使用Landsat- 8 OLI、ASTER和ZY1- 02D高光谱数据,分别采取不同的图像端元提取方法,在进行光谱分析的基础上,利用光谱角填图（SAM）即可得到研究区的主要矿物分类图件。通过野外验证,应用GIS技术进行集成和分析,修正相关图件后,便得到了精准的矿物分类综合图。研究表明：多源遥感数据的集成在岩矿识别方面效果良好、前景巨大。     

基于易滑地质结构与多源数据差异的岩溶山区大型崩滑灾害识别研究

岩溶山区地质环境复杂且脆弱,重特大崩滑地质灾害时有发生。如果对岩溶山区的地质环境认知不准,将直接导致对灾害识别能力不足。文章围绕岩溶山区裸露型岩溶陡崖、复合岩组型斜坡以及非裸露型岩溶斜坡3类基本易滑地质结构差异,探讨多源数据条件下更具适用性的识别探测方法。对于空间影响面积小的厚层岩溶陡崖结构,星-地组合识别方法更加适用,基于GNSS的识别探测方式可在获得动态变形趋势基础上,对可能发生的失稳模式进行初步预判,同时可对InSAR解译的地表位移进行矢量化校正,有利于提高对具有相同或相近SAR数据条件地区的灾害识别程度。对于具有较大空间影响面积的斜坡区域,可优先选用基于InSAR的遥感技术来获取地表变形结果,对于有致灾风险的大变形区还可结合易滑地质结构及外部影响因素对其可能失稳模式进行预判或反演分析。任何灾害识别方式都有其局限性,在实践中可根据不同地质结构特征与灾害类型特点,通过多源、多维度监测来构建综合识别体系,探索更具适用性的识别探测与数据分析新思路。     

自组织竞争人工神经网络在砂岩型铀矿测井数据解释中的应用

详细介绍了自组织竞争人工神经网络模型结构、原理和钻孔岩性自动识别过程,给出了神经网络模型在钻孔岩性自动识别过程中的有效性实例。自组织竞争人工神经网络具有自组织能力、自适应能力和较高的容错能力;与BP算法相比较,计算量小,收敛速度快,且不需要已知的先验信息而自动确定分类类别。钻孔岩性识别结果与岩心地质编录的对比试验表明,在砂岩型铀矿测井数据的解释中,应用自组织竞争人工方法可较好地完成钻孔岩性自动分类。     

化学与稳定同位素指纹示踪原油类污染:以广东南海两次小型溢油事件为例

化学和稳定同位素指纹是目前国际上用于示踪石油类污染来源及其环境命运的有效技术。通过气相色谱-质谱(GC—MS)分析可疑重油与被污染水体及植物表面污染物的饱和烃和芳烃分布以及生物标志化合物姥姣烷、植烷、“不可分辨的混合物”(UCM)等化学指纹特征,对比可疑重油与被污染水体表面漂浮重油的沥青质同位素组成,追踪了发生在广东省南海市的两次小型重油泄漏事件。结果揭示,2002年10月16日晚发生的污染事件源于某饲料公司锅炉房的重油泄漏;而2002年10月25日的泄漏事故则是某加油站重油渗漏所致。