Discontinuous Modelling of Stratum Cave-in in a Longwall Coal Mine in the Arctic Area

This paper presents a discontinuous numerical approach for studying roof cave-in mechanisms and obtaining the required support capacity of longwall shields in a case study site, the Svea Nord coal mine in Svalbard. The block size in the roof strata and the mechanical parameters of the discontinuities for the numerical model were obtained through back-calculations. The back-calculations were conducted with a statistical method of design of experiment. Numerical simulations revealed that voussoir jointed beams are formed before the first cave-in occurs. The maximum deflection of a roof stratum in the study site prior to the first cave-in is about 70 % of the stratum thickness. The maximum span of the roof strata prior to the first cave-in depends upon the in situ horizontal stress state. The roof beams have a large stable span when they are subjected to high horizontal stress; but horizontal stress would increase the possibility of rock crushing in deflected roof beams. The simulations and field measurements show no periodic weighting on the longwall shields in the study site. Stiff and strong roof beams would result in large first and periodic cave-in distances. As a consequence of having large cave-in distances, the longwall shields must have high load capacity, which can be calculated by the presented numerical approach.     

Neuro-fuzzy modeling based genetic algorithms for identification of geochemical anomalies in mining geochemistry

A genetic algorithm (GA)-based neuro-fuzzy approach is used for identification of geochemical anomalies by implementing a Takagi, Sugeno and Kang (TSK) type fuzzy inference system in a 5-layered feed-forward adaptive artificial neural network. This paper investigates the effectiveness of GA-based neuro-fuzzy for separating zone dispersed mineralization (ZDM) from blind mineralization, and its application for identification of geochemical anomalies in the arid landscape of the Lut metallogenic province in eastern Iran. Other classification algorithms such as metallometry, zonality, criteria, and back-propagation artificial neural network classifiers are also used for comparison. The genetic operators are carefully designed to optimize the artificial neural network, avoiding premature convergence and permutation problems. The results show that the GA-based hybrid neuro-fuzzy model can provide accurate results in comparison with those results obtained by other techniques. Neuro-fuzzy and GA-based neuro-fuzzy techniques appear to be well-suited for routine exploration geochemistry applications. In conjunction with statistics and conventional mathematical methods, hybrid approaches can be developed and may prove a step forward in the practice of applied geochemistry.     

Milgromian dynamics and dwarf galaxies in galactic voids

We use kinematic data of 103 dwarf galaxies, obtained from the Sloan Digital Sky Survey catalog, to test the Milgromian dynamics (MOND) inside a galactic void. From this data, we compute the line-of-sight velocity dispersions of the dwarf galaxies in the frameworks of MOND and Newtonian dynamics without invoking any dark matter. The prediction for the line-of-sight velocity dispersions from MOND of 53 selected dwarf galaxies is compared with their measured values. For appropriate mass-to-light ratios in the range 1 to 5 for each individual dwarf galaxy, our results for the line-of-sight velocity dispersions predicted by MOND are more compatible with observations than those predicted by Newtonian dynamics.     

Analytical methods to estimate the hydraulic conductivity of jointed rocks

Hydrogeology Journal - The hydraulic conductivity of jointed rocks is one of the main input parameters to predict water inflow to engineering structures that are located in the jointed rocks....     

Battered minipile response to low-frequency cyclic lateral loading in very dense sand

Acta Geotechnica - This experimental study investigates the response of vertical and battered minipiles to two-way symmetrical low-frequency (0.1 Hz) cyclic lateral loading. Laboratory...     

Sea level in the Mediterranean Sea: seasonal adjustment and trend extraction within the framework of SSA

The sea level change is a crucial indicator of our climate. The spatial sampling offered by satellite altimetry and its continuity during the past years are the major assets to provide an improved vision of the Mediterranean sea level changes. In this paper, an automatic signal extraction approach, based on Singular Spectrum Analysis (SSA), is utilized for analysis and seasonal adjustment of the Mediterranean Sea level series. This automatic approach enables us to overcome the difficulties of visual identification of trend constituents that sometimes we encounter when using the conventional SSA method. The results indicate that the Mediterranean mean sea level is dominated by several harmonic components. The annual signal is particularly strong and almost covers 73.62 % of the original sea level series variation whiles its amplitude is about 15 cm. The extracted trend also indicates that the Mediterranean main sea level has significantly been raised during the period 1993–2012 by 2.44?±?0.4 mm yr^?1. As an important consequence, considering the current situation, if this trend continues, the Mediterranean Sea level will be raised about 22 cm by the end of this century, which makes a dramatic effect on several issues such as land, flora, fauna, and people activities established along the Mediterranean coastlines.     

Geochemical and mineralogical pattern recognition and modeling with a Bayesian approach to hydrothermal gold deposits

The Bayesian approach is an effective method of identifying the probability of mineralogical and geochemical type (MGT) mineralization of trace elements in galena, pyrite and other distributions in ore mineralization. Monomineralic samples have been identified using a computer-based Bayesian method and exploration geochemical techniques of Au deposits for MGT. In order to employ the method, a data bank was used consisting of the results of analysis of more than 12,000 monomineralic samples collected from the main hydrothermal Au deposits in Tajikistan (a territory of CIS). The Bayesian approach applied to geochemical data, such as posterior probabilities and discriminant analysis, provide numerical and graphical means through which the relationships between the trace elements and samples can be studied. The method used here, along with GIS, to find MGT can be used as geochemical indicators of regions with Au mineralization. The results of analyzing 100 monomineralic samples of pyrite from the Au–Ag Shkolnoe deposit (Tajikistan) show a multi-MGT anomaly superposition which is a combination of three MGT: (1) Au–Ag type (85% and more), (2) Au–sulfide-polymetallic type (46%), and (3) Au–sulfide type (40%). Mineralogical and geochemical maps (MGM) can be drawn based on results of MGT anomalies in a GIS environment. These maps can replace traditional metallogenic maps. The advantage of MGM substitutions is that a qualitative tool is replaced by a quantitative one. This helps one to make optimal managerial and more economical decisions.     

Inversion of surface gravity data for 3-D density modeling of geologic structures using total variation regularization

We develop an inversion procedure using the total variation (TV) regularization method as a stabilizing function to invert surface gravity data to retrieve 3-D density models of geologic structures with sharp boundaries. The developed inversion procedure combines several effective algorithms to solve the TV regularized problem. First, a matrix form of the gradient vector is designed using the Kronecker product to numerically approximate the 3-D TV function. The piecewise polynomial truncated singular value decomposition (PP-TSVD) algorithm is then used to solve the TV regularized inverse problem. To obtain a density model with depth resolution, we use a sensitivity-based depth weighting function. Finally, we apply the Genetic Algorithm (GA) to select the best combination of the PP-TSVD algorithm and the depth weighting function parameters. 3-D simulations conducted with synthetic data show that this approach produces sub-surface images in which the structures are well separated in terms of sharp boundaries, without the need of a priori detailed density model. The method applied to a real dataset from a micro-gravimetry survey of Gotvand Dam, southwestern Iran, clearly delineates subsurface cavities starting from a depth of 40 m within the area of the dam reservoir.     

Rayleigh–Taylor instability in an ionized medium

We study the linear theory of the magnetized Rayleigh–Taylor instability in a system consisting of ions and neutrals. Both components are affected by a uniform vertical gravitational field. We consider ions and neutrals as two separate fluid systems that can exchange momentum through collisions. However, ions have a direct interaction with the magnetic field lines but neutrals are not affected by the field directly. The equations of our two-fluid model are linearized and by applying a set of proper boundary conditions, a general dispersion relation is derived for our two superposed fluids separated by a horizontal boundary. We found two unstable modes for a range of wavenumbers. It seems that one of the unstable modes corresponds to the ions and the other one is for the neutrals. Both modes are reduced with increasing particle collision rate and ionization fraction. We show that if the two-fluid nature is considered, the RT instability would not be suppressed and we also show that the growth time of the perturbations increases. As an example, we apply our analysis to the Local Clouds which seem to have arisen because of the RT instability. Assuming that the clouds are partially ionized, we find that the growth rate of these clouds increases in comparison to the fully ionized case.     

High‐frequency streamflow acquisition and bed level/flow angle estimates in a mountainous river using shallow‐water acoustic tomography

The acquisition of reliable discharge estimates is crucial in hydrological studies. This study demonstrates a promising acoustic method for measuring streamflow at high sampling rate for a long period using the fluvial acoustic tomography system (FATS). The FATS recently emerged as an innovative technique for continuous measurements of streamflow. In contrast to the traditional point/transect measurements of discharge, the FATS enables the depth‐averaged and range‐averaged flow velocity along the ray path to be measured in a fraction of a second. The field test was conducted in a shallow gravel‐bed river (0.9 m deep under low‐flow conditions, 115 m wide) for 1 month. The parameters (stream direction and bottom elevation) required for calculating the streamflow were deduced by a nonlinear regression to the discharge data from the well‐established rating curve. The cross‐sectional average velocities were automatically calculated from the acoustic data, which were collected on both riverbanks every 30 s. The FATS was connected to the internet so that the real‐time flow data could be obtained. The FATS captured discharge variations at a cut‐off frequency of approximately 70 day^?1. The stream exhibited temporal discharge changes at multiple time scales ranging from a few tens of minutes to days. Copyright © 2016 John Wiley & Sons, Ltd.