Magnetic fabrics and rock magnetism of Proterozoic dike swarm from the southern São Francisco Craton, Minas Gerais State, Brazil

Magnetic fabric and rock magnetism studies were performed on 32 mafic dikes of a Proterozoic dike swarm from the southern São Francisco Craton (SFC; Minas Gerais State, SE Brazil). Magnetic anisotropies were determined by applying anisotropy of low-field magnetic susceptibility (AMS) and anisotropy of remanent magnetization (ARM). The latter was performed imposing both anhysteretic (total (AAR) and partial pAAR)) and isothermal remanence magnetizations (AIRM). Partial anhysteretic remanence anisotropy was performed based on remanent coercivity spectra from a pilot specimen of each site. In most sites, AMS is dominantly carried by ferromagnetic minerals, however, in some sites, the paramagnetic contribution exceeds 70% of bulk susceptibility. Rock magnetism and thin section analysis allow classifying the dikes as non-hydrothermalized and hydrothermalized. Magnetic measurement shows that the mean magnetic susceptibility is usually lower than 5×10⁻³ (SI). Ti-poor titanomagnetites up to pure magnetite pseudo-single-domain (PSD) grain sizes carry the majority of magnetic fabrics for non-hydrothermalized dikes whereas coarse to fine grained Ti-poor titanomagnetites carry the majority of magnetic fabrics for hydrothermalized dikes.Three primary AMS fabrics are recognized which are coaxial with ARM fabric, except for two dikes, from both non-hydrothermalized and hydrothermalized dikes. Normal AMS fabric surprisingly is not dominant (31%). The parallelism between AMS, pAAR_0–30, pAAR_30–60 and pAAR_60–90 fabrics in the hydrothermalized dikes indicates that magnetic grains formed due to late-stage crystallization or to remobilization of iron oxides due to hydrothermal alteration after dike emplacement have acquired a mimetic fabric coaxial with the primary fabric given by coarse-grained early crystallized Ti-poor titanomagnetites. This fabric is interpreted as magma flow in which the analysis of K_max inclination permitted the inference that the dikes were fed by horizontal or subhorizontal fluxes (K_max<30°). Intermediate AMS fabric is the most important (41%) in the investigated swarm. It is interpreted as due to vertical compaction of a static magma column with the minimum stress along the dike strike. ARM determinations for these sites also remained intermediate except for two dikes. In one of them, AIRM fabric resulted in normal AMS fabric while for the other AAR fabric resulted in inverse AMS fabric. A combination of AMS and ARM fabrics suggest that magmatic fabric for both dikes were overprinted by some late local event, probably related to Brasiliano orogenic processes after dike emplacement. InverseInverse AMS fabric is a minority (four dikes). ARM determinations also remained inverse suggesting a primary origin for inverse AMS fabric.     

Groundwater and geotechnical aspects of deep excavations in Hong Kong

Consideration of groundwater is a key element in almost every construction project. The design of deep excavations for basements or underground railway station concourses below the water table require that the water pressures are taken into account. Whilst these can be considered to be hydrostatic in soil, the decreasing permeability of rock with depth and the fact that groundwater flow is invariably along discrete fractures means that the water pressure is unlikely to be hydrostatic at depth.

Groundwater control for deep excavations can be achieved by a number of methods such as grouting, pumping or structural walls or a combination of these. For tunnelling projects grouting is extensively used, but the development of sophisticated tunnelling machines has led in many cases to the demise of compressed air as a means of groundwater control.     

Fuzzy set approaches to classification of rock masses

Rock mass classification is analogous to multi-feature pattern recognition problem. The objective is to assign a rock mass to one of the pre-defined classes using a given set of criteria. This process involves a number of subjective uncertainties stemming from: (a) qualitative (linguistic) criteria; (b) sharp class boundaries; (c) fixed rating (or weight) scales; and (d) variable input reliability. Fuzzy set theory enables a soft approach to account for these uncertainties by allowing the expert to participate in this process in several ways. Hence, this study was designed to investigate the earlier fuzzy rock mass classification attempts and to devise improved methodologies to utilize the theory more accurately and efficiently. As in the earlier studies, the Rock Mass Rating (RMR) system was adopted as a reference conventional classification system because of its simple linear aggregation.

The proposed classification approach is based on the concept of partial fuzzy sets representing the variable importance or recognition power of each criterion in the universal domain of rock mass quality. The method enables one to evaluate rock mass quality using any set of criteria, and it is easy to implement. To reduce uncertainties due to project- and lithology-dependent variations, partial membership functions were formulated considering shallow (<200 m) tunneling in granitic rock masses. This facilitated a detailed expression of the variations in the classification power of each criterion along the corresponding universal domains. The binary relationship tables generated using these functions were processed not to derive a single class but rather to plot criterion contribution trends (stacked area graphs) and belief surface contours, which proved to be very satisfactory in difficult decision situations. Four input scenarios were selected to demonstrate the efficiency of the proposed approach in different situations and with reference to the earlier approaches.     

深基坑支护方案的分析与优化

针对武汉市南湖岸边复杂的地质条件及周边环境,在某高层建筑的深基坑支护结构设计中,结合实际因地制宜地对基坑的支护方法进行了分析比较。支护效果及实测数据表明,该工程所采用的混合式支护实施方案技术安全可靠,经济合理,可为同类型基坑工程设计提供借鉴。     

基坑防渗体局部失效渗流场变化特征

采用三维有限元方法分析了基坑开挖工程在防渗体出现局部失效情况下，引起渗流在失效部位的集中及渗流场空间状况。提出了以一维通道嵌入三维块体的方法模拟管涌发展过程及渗流场变化特征。讨论了管涌通道渗透性对基坑管涌发展规律的影响。     

Localization of mining-induced horizontal fractures along rock layer interfaces in overburden: field measurements and prediction

The locations of mining-induced horizontal fractures along rock interfaces in the overburden of Donetsk Coal Basin were identified using an original experimental device. The device traps methane from horizontal fracture zone (100–fold coal seam thickness) over an active longwall mining excavation. Presence or absence of horizontal fractures along rock layer interfaces is correlated with physical characteristics of the overburden, such as thickness, uniaxial compressive strength of overburden rock layers, location of rock layer interfaces and thickness of extracted coal seams. As a result, a combined criterion based on these physical characteristics is proposed to predict the presence of overburden horizontal fracturing in coal mine operations.     

Prediction of creep characteristic of rock under varying environment

The strain developed due to creep is mainly proportional to the logarithm of the time under load, and is mostly proportional to the stress and temperature. At higher temperature the creep rate falls slowly with respect to time, and the creep strain is proportional to a fractional power of time, with the exponent increasing as the temperature increases and reaching a value approximately one-third at temperatures of about 0.5°C. At these temperatures, the creep increases with stress according to a power greater than unity and possibly exponentially. It increases with temperature as (−U/kT), where U is an activation energy and k is Boltzman’s constant. There are different methods to determine the creep strain and the energy of Jog (B) including experimental methods, multivariate regression analysis, and by numerical simulation. These methods are less cumbersome and time consuming. In the present investigation, artificial neural network technique has been used for prediction of the creep strain and energy of Jog (B). Two different networks have been tested and validated. Both the networks have four input neurons and one hidden layer with five neurons, and one output neuron. The data for different rocks at temperatures up to 750°C under conditions of compressive or tortional stress are taken from the literatures. The training and testing data sets used were 163 and 14, respectively. To deal with the problem of overfitting of data, Bayesian regulation has been used and network is trained with suitable training epochs. The coefficients of correlation among the predicted and observed values are found high and they improve the confidence of the users. The mean absolute percentage error obtained are also very low.