Volume 63 (2016): Issue 2 (July 2016)

This study presents an innovative approach for determining the unconfined yield strength σ_c during the excavation of coal from the earth’s crust by using an equipment that was developed for measuring the mechanical properties of bulk materials stored in silos. Highly productive excavation of coal with a hanging wall top caving leads to intensive deformations in the hanging wall and the broken coal can be considered as bulk material. In this research, the shear tester Johanson Hang-Up Indicizer was used to measure the unconfined yield strength of the tested samples, even though such a tester cannot produce stress-strain conditions similar to those occurring during the excavation. An attempt was made to estimate the real unconfined yield strength of broken coal deep under the surface through a combination of measured data and extrapolation.

We present a method that utilizes multichannel analysis of surface waves (MASW), which was used to measure shear wave velocities, with a view to establishing the probable causes of road failure, subsidence and weakening of structures in some local government areas in Lagos, Nigeria. MASW data were acquired using a 24-channel seismograph. The acquired data were processed and transformed into a two-dimensional (2-D) structure reflective of the depth and surface wave velocity distribution within a depth of 0–15 m beneath the surface using SURFSEIS software. The shear wave velocity data were compared with other geophysical/ borehole data that were acquired along the same profile. The comparison and correlation illustrate the accuracy and consistency of MASW-derived shear wave velocity profiles. Rigidity modulus and N-value were also generated. The study showed that the low velocity/ very low velocity data are reflective of organic clay/ peat materials and thus likely responsible for the failure, subsidence and weakening of structures within the study areas.

In accordance with the regulations of the Energy Agency of the Republic of Slovenia, each natural gas supplier regulates and determines the charges for the differences between the ordered (predicted) and the actually supplied quantities of natural gas. Yearly charges for these differences represent up to 2% of supplied natural gas costs. All the natural gas users, especially industry, have huge problems finding the proper method for efficient natural gas consumption prediction and, consequently, the decreasing of mentioned costs. In this study, prediction of the natural gas consumption in Štore Steel Ltd. (steel plant) is presented. On the basis of production data, several models for natural gas consumption have been developed using linear regression, genetic programming and artificial neural network methods. The genetic programming approach outperformed linear regression and artificial neural networks.

An integrated geophysical (involving two-dimensional [2D] electrical resistivity) and petrophysical study was conducted in the Precambrian Crystalline Basement area of Iwaro-oka Akoko, southwestern Nigeria. Five 2D resistivity profiles, both around the perimeters and inside the dump, were investigated with maximum lengths of 100 m. Results of the resistivity imaging delineated the leachate plumes as low-resistivity zones, with values ranging from 3 Ω m to 55 Ω m. The coefficient of permeability ranged from 4.33 × 10^-6 to 7.82 × 10^-3, and the average porosity ranged from 32 Ω m to 169 Ω m, thus indicating migration of leachate plume to the groundwater due to the high coefficient of permeability and the porosity.

The banded iron ore mineralization at Ero was investigated using aeromagnetic, resistivity and induced polarization (IP) methods with the aim of characterizing the deposit. Analysis of the aeromagnetic data involved the application of reduced-to-equator transformation, derivative filters, analytic signal and source parameter imaging techniques. Computer modelling of some of the identified anomalies was undertaken. The electrical resistivity and IP methods helped in discriminating between the iron ore and the host rock. The results showed that the banded iron formations (BIFs) were characterized by spherical analytic signal anomalies ranging from 0.035 nT/m to 0.06 nT/m within the granite gneiss and magnetic susceptibility of 0.007-0.014 SI. The iron ore had low chargeability (0.1-5.0 msec) and resistivity (1.5 × 10² to 2.5 × 10³ Ωm). Structural features trending in the NE-SW, E-W, and NW-SE were identified, suggesting that the area had undergone many episodes of tectonic events. Depth to the BIF varied from the surface up to about 200 m. The chargeability response of the iron bodies suggested an average grade of 20%-40%, making the prospect for economic exploitation attractive.