Electrical analogy for modelling thermal regime and moisture distribution in sandy soils

The soil mass is subjected to temperature variation due to several human activities (viz. tanks storing heated fluids, buried cables and pipelines, air-conditioning ducts, disposal of nuclear and thermal power plant wastes etc.), which result in heat-induced migration of the moisture in it. Though several studies have been conducted in the past to investigate the mechanism of heat migration through the soil mass, a methodology for ‘real-time measurement of the variations in temperature, flux and moving moisture front, in tandem, with respect to space' has rarely been attempted. In this context, extensive laboratory investigations were conducted to measure real-time flux and temperature variations in the sandy soils, and the validation of results has been done by employing an equivalent electrical circuit programme, LTspice. Subsequently, a mathematical model PHITMDS (i.e. Prediction of Heat-Induced Temperature and Moisture Distribution in Soil) has been developed and its utility and efficacy, for predicting the depth-wise temperature and heat-induced moisture migration, due to evaporation, in terms of position of moving moisture front in the sandy soil has been critically discussed and demonstrated.     

RS & GIS-based landslide susceptibility mapping of the Balason River basin,Darjeeling Himalaya,using logistic regression (LR) model

The present study deals with the preparation of a landslide susceptibility map of the Balason River basin, Darjeeling Himalaya, using a logistic regression model based on Geographic Information System and Remote Sensing. The landslide inventory map was prepared with a total of 295 landslide locations extracted from various satellite images and intensive field survey. Topographical maps, satellite images, geological, geomorphological, soil, rainfall and seismic data were collected, processed and constructed into a spatial database in a GIS environment. The chosen landslide-conditioning factors were altitude, slope aspect, slope angle, slope curvature, geology, geomorphology, soil, land use/land cover, normalised differential vegetation index, drainage density, lineament number density, distance from lineament, distance to drainage, stream power index, topographic wetted index, rainfall and peak ground acceleration. The produced landslide susceptibility map satisfied the decision rules and ?2 Log likelihood, Cox &; Snell R-Square and Nagelkerke R-Square values proved that all the independent variables were statistically significant. The receiver operating characteristic curve showed that the prediction accuracy of the landslide probability map was 96.10%. The proposed LR method can be used in other hazard/disaster studies and decision-making.     

Calibration of cyclic constitutive models by oscillating functions

Most structures are subjected to more cyclic loads during their life time than static loads. These cyclic action could be a result of either natural or man-made activities and may lead to soil failure. In order to understand the response of the foundation and its interaction with these complex cyclic loadings, various researchers have over the years developed different constitutive models. Although a lot of research is being carried out on these relatively new models, little or no details exist in literature about the model-based identification of the cyclic constitutive parameters which to a large extent govern the quality of the model output. This could be attributed to the difficulties and complexities of the inverse modeling of such complex phenomena. A variety of optimisation strategies are available for the solution of the sum of least-squares problems as usually done in the field of model calibration. However, for the back analysis (calibration) of the soil response to oscillatory load functions, this article gives insight into the model calibration challenges and also puts forward a method for the inverse modeling of cyclic loaded foundation response such that high-quality solutions are obtained with minimum computational effort.     

Probabilistic calibration of a coupled hydro-mechanical slope stability model with integration of multiple observations

Multiple types of responses, such as displacements, ground water level, pore water pressures, water contents, etc., are usually measured in comprehensive monitoring programmes for rainfall-induced landslide prevention. In this study, a probabilistic calibration method for coupled hydro-mechanical modelling of slope stability is presented with integration of multiple types of measurements. A numerical example of a soil slope under rainfall infiltration is illustrated to compare the effects of single and multiple types of responses on parameter estimation and model calibration. The results show that the soil parameters can be estimated with less uncertainty and total uncertainty bounds are narrower with multiple types of responses than with a single type of response. Model calibration based on multiple types of responses can compromise different responses and hence the means and standard deviations of model error are the smallest. A feasible correlation coefficient between soil modulus and permeability can be obtained from model calibration with multiple types of responses and single type of response as long as the responses include displacement data.     

扬子地台东南缘下寒武统清虚洞组风暴沉积特征及其重要意义

在扬子地台东南缘,下寒武统龙王庙阶清虚洞组主要由浅水碳酸盐岩组成。在野外露头剖面实测和室内镜下薄片观察的基础上,大量风暴沉积被发现于不同剖面清虚洞组的不同层位中,同时大量风暴诱发形成的沉积构造被识别出来,包括侵蚀基底、粗粒滞留沉积、粒序层理、平行层理、丘状交错层理(少见并且值得怀疑)以及沙纹层理,组成了多种类型的风暴沉积序列。结合更靠扬子东南缘的深水剖面中重力流沉积的缺乏,可以推断早寒武世龙王庙期扬子地台的沉积模式为碳酸盐缓坡。结合风暴的形成机制以及清虚洞组风暴沉积的发育特征(尤其是粗粒滞留砾屑的定向排列和典型丘状交错层理的缺乏),可以推断研究区风暴沉积形成于强烈的冬季风暴作用,并且早寒武世龙王庙期华南的古地理位置应当位于中纬度地区,这一结论对一些著名的全球古地理重建方案提出了质疑。同时中纬度地区大规模发育蒸发岩和碳酸盐岩还佐证了寒武纪地球处于热室(Hothouse)时期。     

碳酸盐台地的类型、特征和沉积模式--兼论华北地台寒武纪陆表海-淹没台地的沉积样式

随着对现代碳酸盐沉积环境的系统调查和解释、以及对碳酸盐沉积原理认识的深化,自20世纪60年代,一系列碳酸盐沉积相模式得以建立,其中最引人注目的是Wilson和Tucker的工作。但在镶边陆棚及缓坡模式得到了广泛认可和使用的同时,对陆表海和淹没台地型沉积未能予以足够的重视。与过去相比,现今的海平面是相对较低的,因而没有出现陆表海广泛发育的情况。但在漫长的地质历史时期,陆表海曾经覆盖了广泛的克拉通区域,是碳酸盐沉积最重要的场所之一。本文在系统总结前人成果的基础上,将用于描述大尺度碳酸盐岩沉积环境的碳酸盐台地分为镶边陆棚、缓坡、陆表海、孤立台地和淹没台地5种类型分别描述,并重点强调了陆表海和淹没台地的沉积模式。华北地台寒武系大面积分布的潮坪沉积、鲕粒滩相灰岩和竹叶状风暴砾屑灰岩,以及频繁出现的台地淹没事件,为阐明陆表海和淹没台地的沉积提供了绝佳实例。这些实例和研究表明了碳酸盐沉积环境的多样性和沉积过程的复杂性,以及将今论古的困难性,从而为碳酸盐沉积原理的认识和沉积环境的解释提供新认识和新思路。     

新疆奥尔托喀讷什锰矿含锰岩系地质特征及成矿条件分析

新疆阿克陶县奥尔托喀讷什地区锰矿在近年来取得重大找矿突破,目前该锰矿区已累计查明资源储量1206.74万吨,矿床平均品位37.82%。本文通过钻探、坑探和各类地质测量全面分析了奥尔托喀讷什地区的区域地质特征、赋矿地层及锰矿的矿床地质特征和成因。查明了区内地层层序,并确定上石炭统喀拉阿特河组第三岩性段（C2k3）是本区主要的含锰岩系,是锰矿体的主要赋存层位。探明了区内矿体的产出形态、规模、产状、矿石类型及结构构造,分析了区内锰矿形成的地质背景、成矿条件,并初步建立了奥尔托喀讷什锰矿的成矿模式,进而为该区找矿突破提供了理论支撑。     

甘肃省肃南县桦树沟铁铜矿床地质特征及成矿模式

甘肃北祁连西段桦树沟铁铜矿床是西北地区一个非常重要的铁铜矿床,对其地质特征及成矿模式的研究,将会对研究该成矿带铁铜矿床的成矿模式具有深远意义。通过大量的工作,认为桦树沟铁铜矿床为产于长城系上岩组的一套陆源碎屑岩夹碳酸沉积建造的同生海底喷流沉积矿床。铁矿体控矿构造主要是区域褶皱带,主要赋存于长城系上岩组的含铁细碎屑—粘土岩建造中,具体岩性为千枚岩。铜矿体的产出明显受后期韧性剪切带和层间滑动带共同控制,主要矿石类型有含铁碧玉岩型和蚀变千枚岩型两种。     

大数据环境下内蒙古浩布高地区铅锌多金属矿智能矿产预测研究

传统机器学习算法已广泛应用于矿产预测,但面对地质大数据的高维稀疏、不平衡小样本等特性仍缺乏有效处理和分析的方法,设计适合地质大数据特点的机器学习算法是智能矿产预测亟需解决的新问题。本文以内蒙古浩布高地区的铅锌多金属矿产预测为例,提出了一种面向地质大数据的半监督协同训练矿产预测模型。首先对研究区地质找矿信息和地球化学异常信息进行定量分析,提取断裂构造、二叠系地层、燕山期侵入岩、地层与岩体接触带、围岩蚀变及Pb、Zn、Sn、Cu地球化学异常共9种找矿因子。然后利用递归特征消除法优选找矿因子组合,不包括Sn异常在内的8个找矿因子组合被选为最优组合。最后,利用支持向量机和随机森林算法作为基分类器进行半监督协同训练矿产预测,绘制成矿概率分布图。ROC曲线和预测度曲线分析结果表明,半监督协同训练模型的AUC值和预测效率都高于随机森林和支持向量机模型。研究结果也为大数据环境下的智能矿产预测提供了一种新的思路。     

青藏铁路对西藏各经济部门发展影响的定量评估

青藏铁路对西藏经济发展影响重大,定量评估其对各经济部门发展的影响程度,是全面评价铁路交通基础设施效益、分析未来冰冻圈变化对线性工程及经济社会重大影响的基础。将灰色关联分析法与投入产出法相结合,既填补了关联度分析的黑箱式缺陷,又弥补了西藏投入产出调查缺乏长时间序列数据的问题,以此来认识青藏铁路对西藏经济发展的影响机理与路径。以2006-2016年统计数据为基础,采用灰色关联度模型计算青藏铁路与西藏各经济部门发展的灰色关联度值,表明铁路运输水平与西藏地区生产总值（GDP）、第三产业高度相关,其中与货运邮电业、住宿餐饮业两个部门关联度达到了0.9以上。在灰色关联度结果的基础上,运用西藏2012年投入产出表及投入产出模型计算铁路的直接作用,以及对各经济部门的间接波及作用,研究发现：青藏铁路建设及运营的劳动密集程度高,且通过灰色关联度较高行业的产品及服务影响其他行业,以直接作用、后向和前向波及作用、消费波及作用三种路径对区域经济的发展产生重要影响,扣除消费波及作用的总体贡献达到41.7亿元,相当于2012年西藏GDP的5.95%。由于铁路交通基础设施重要的直接作用及间接波及作用,建议在工程条件适宜地区加快铁路运输网络建设,同时,将工程设施的社会经济效益纳入冰冻圈服务功能核算中。