实验变差函数计算方法的研究与运用

本文系统、详尽地分析讨论了不同样品数据条件下实验变差函数的计算方法。在实验变差函数计算流程的设计和有效样品搜索域的确定方面提出了自己独特的见解。最后用一个矿山的控矿工程教据对文中介绍的方法进行了测试。结果表明,利用本文的方法,容易得到稳健、准确、信息量高的实验变差函数。     

基于UML的地质数据库设计方法的研究

为了存储和管理复杂的地质数据需要一个合理有效的数据模型,以确保数据库中的所有数据时象得到精确和完整的表达。本文讨论了用UML的面向对象的方法来设计,给出了基于GeoDatabase模型建立地质数据库的具体过程。     

构建基于GIS的房产管理

阐述了基于GIS房产管理的关键是建立统一的数据分类与编码标准,核心是建立房屋的空间地理属性信息、自然属性信息、社会人文属性信息的链接,基础是建立房产地理信息数据库。并提出了建立房产地理信息数据库的方法、设计思路和方式。     

基于免疫粒子群优化算法的影像纹理分类

粒子群优化算法是基于群智能的随机全局优化方法,它源于对鸟群简化社会系统的模拟。为了提高标准粒子群优化算法的收敛性能,将生物免疫系统的记忆能力和多样性引入标准粒子群优化算法,提出一种免疫粒子群优化算法。在提取纹理样本Laws纹理能量模板特征、小波特征等纹理特征的基础上,提出针对分类问题的粒子表达方法和群体寻优策略,实现了基于免疫粒子群算法的纹理分类。实验结果表明,与标准粒子群优化算法相比,免疫粒子群优化算法在获取训练样本类别中心时具有较好的收敛性能,并且基于该算法的影像纹理分类具有较高的分类精度。     

上海市长江口及邻近海域地质调查现状及展望

海洋区域地质调查近年来逐渐得到重视,海洋地质调查技术的发展也为开展海洋区域地质调查奠定了基础。上海地区社会经济发展对地质工作的需求,为摸清上海市长江口及邻近海域的地质现状提出了必然要求。本文在系统整理长江口及邻近海域地质资料的基础上,重点分析了区内存在的重点地质问题和研究存在的问题,根据海洋地质调查的技术发展,结合国内相关地区的调查经验,对长江口及邻近海域内区域地质调查进行了展望,提出了采用综合物探技术、地质取样和测试分析进行综合地质环境调查的建议,并对具体采用的调查技术和调查内容进行了论述。     

Automatic classification of volcanic earthquakes by using Multi-Layered neural networks

The application of neural networks as classifiers of seismic events is described with the aim of developing an automatic system for the classification of explosion quakes at the Stromboli volcano. The architecture of the network that we trained to identify four different classes of shocks was a Multi-Layer Perceptron, using the Back Error Propagation algorithm. Five different approaches for representing the information embedded in the seismograms, both in the time and in the frequency domain, were considered, and the results compared. The direct use of the time series of the shocks was not satisfactory. The auto-correlation function worked well, but in some cases it was misleading. A better performance was obtained with a frequency domain representation. Finally, the use of the envelope function did not work well. Combining parameters such as the auto-correlation and envelope functions can improve one source of error, but it may introduce new ones. The performance obtained highlights the importance of the data attributes used for the training of the network. Topologies with eight neurons in a single hidden layer gave, on average, the best results among the considered neural network structures. The overall results provide a large number of events (89% with the best performance) correctly classified, indicating that this automatic technique is reliable, and encouraging further applications in the field of volcanic seismology.     

Engineering geological studies and tunnel support design at Sulakyurt dam site, Turkey

This paper presents the results of engineering geological investigations and tunnel support design studies, carried out at the Sulakyurt dam site, northeast of Ankara, Turkey. The Sulakyurt dam will be used for flow control and water storage for irrigation projects. Studies were carried out both in the field and the laboratory. Field studies include engineering geological mapping, intensive discontinuity surveying, core drilling and sampling for laboratory testing. The diversion tunnel will be driven in rock mass, consisting of granite and diorite. Empirical, analytical and numerical methods were combined for safe tunnel design. Rock mass rating (RMR), Rock mass quality (Q) and Geological strength index (GSI) systems were used for empirical rock mass quality determination, site characterization and support design. The convergence–confinement method was used as analytical method and software called Phase², a 2D finite element program, was utilized as numerical method. According to the results acquired from the empirical, analytical and numerical methods, tunnel stability problems were expected in both granite and diorite rock masses. The support system, suggested by empirical methods, was applied and the performance of suggested support system was evaluated by means of numerical modelling. It was concluded that the suggested support systems were adequate, since after applying the suggested support system to granite and diorite, tunnel deformation and the yielded elements around the tunnel decreased significantly. Thus, it is suggested that for more reliable support design empirical, numerical and analytical methods should be combined.     

Modeling of the classification behavior of the diaphragms used in multi-chamber cement mills

A new approach has been developed for describing the classification that arises at the diaphragm in multi-chamber ball mills. Fourteen industrial scale cement mills have been sampled in this study and after mass balancing, model fits of the equipment were done. Successive mill product predictions for the sampled conditions were achieved, and requirements to build up an optimization capable model are discussed.     

A Connectivity Index for Discrete Fracture Networks

Connectivity is an important measure for assessing flow transport in rock, especially through fractures. In this paper, rock fracture systems are modelled by a discrete fracture model simulated by a marked point process. A connectivity index is then introduced to quantify the connectivity between any two points in space. Monte Carlo simulation is used to evaluate the connectivity index for stationary cases and relationships between the connectivity index and the parameters of the discrete fracture model are analysed. The average number of intersections per fracture, X_f, and the fracture intensity, P12 (P32), are calculated and the relationships between these parameters and the connectivity index are investigated, concluding that X_f is the more suitable parameter for the classification of rock mass flow properties. The relationships between the connectivity index and the percolation state of the fractured medium are also discussed. An edge correction is briefly discussed and a practical example is used to demonstrate the method of computing the connectivity index.     

A Solution to the Problem of Predicting the Suitability of Silty–clayey Materials for Cement-stabilization

Major geotechnical problems in construction involving silty–clayey soils are due to their low strength, durability and high compressibility of soft soils, and the swell–shrink nature of the overconsolidated swelling soils. Confronted with these problems, a suitable ground improvement technique is needed, for deep excavations in soft clays, for stability, durability and deformation control. Cement-stabilization is one of the alternatives. An increase in strength and durability, reduction in deformability are the main aims of this method. Conventional cement-stabilization methods are used mainly for surface treatment. However, the use of cement has recently been extended to a greater depth in which cement columns were installed to act as a type of soil reinforcement (deep cement–soil mixing and cement jet grouting). In situ engineering properties of these silty–clayey soils are often variable and difficult to predict. For this reason cement-stabilization methods have a basic target to control the aforementioned engineering properties of these clays so that the properties of a silty–clayey soil become more like the properties of a soft rock such as clayey shale or lightly cemented sandstone. So cement-stabilization of these soils is essential to control their engineering properties and to predict their engineering behaviour for construction. In an effort to predict, classify and study the suitability of silty–clayey soils for cement-stabilization both slaking and unconfined compressive strength tests were carried out on clayey–sand mixtures consisted of two types of clays, kaolin and bentonite. Finally diagrams were prepared to study the variation of slaking and strength due to compaction, curing time and cement percentage and also to predict areas of efficient cement-stabilization.