Safety and reliability are the main requirements for brake devices in the mining winding installations. Therefore, selection of the right materials for the friction brake elements (pads and discs) is the most challenging task for brake system designers. The friction coefficient for such friction couples should be relatively high but, above all it should be stable. In order to achieve the desired brake friction couple performance, a new approach to the prediction of the tribological processes versus friction materials formulation is needed. The paper shows that the application of the artificial neural network can be productive in modelling complex, multi-dimensional functional relationships directly from experimental data. The artificial neural network can learn to produce the model of friction brake behaviour.

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The paper is devoted to finite element method based study of stress field heterogeneity at microstructure level of two-phase cemented carbides. Special attention is put on investigation of influence of the microstructure model type on the stress field distributions. Two- and three-dimensional models of the microstructures have been generated. Moreover, two different representations of the microstructure have been considered. The first one assumes uniformly distributed cobalt phase forming continuous boundaries between tungsten carbide particles. The second one assumes that the cobalt phase shape and distribution are created in a way that allows for no differentiation of continuous boundaries between tungsten carbide grains. Finite element analyses have been carried out with different microstructure models. The results of the simulations are stress distributions in each phase of the material. Furthermore, a numerical homogenization has been conducted to investigate the phase properties’ influence on the effective elastic constants of the cemented carbide.

This article describes a new design solution for a hybrid bearing intended for use in prosumer wind turbines with a vertical axis of rotation of the turbine rotor. The automatic rotational speed-dependent load-switching, lubrication and cooling systems applied in the hybrid bearing ensure a particularly long service life and highly quiet running while maintaining high energy efficiency over the full rotational speed range of shafts with turbine rotors. The hybrid bearing design has been adapted to the use of lubricating fluids with the lowest possible viscosity, including oil-water emulsions and even water itself. The use of water as a lubricant makes the bearing system highly environmentally friendly and completely fire-safe.

Economic analysis allows for determining the required daily output under certain natural and mining conditions based on the costs of the production process in a particular mine infrastructure. Therefore, there is a need to determine the potential daily output of a longwall using the technical equipment at the disposal of the mine. In the case of mines, when exploiting a few longwalls simultaneously in the conditions of bumping hazards, it is indispensable to ensure safety. Due to a necessity of keeping a safe distance among the longwall fronts, when planning their exploitation, developing a prediction of the longwalls in advance during the planning period is needed. To predict the daily production from a longwall and daily advance of the longwall in the analyzed period, it is necessary to know the current operating time of machines and the capacity of the shearer under given conditions. The current working time of machines results from the available time and the degree of its utilization, which is determined by the sum of unplanned breaks in the production process. The shearer productivity is determined by its haulage speed. Both factors mentioned above are random. Hence, a calculation module has been developed, whose task is to estimate the distribution parameters of these indicators based on empirical data. The algorithm for estimating the parameters of one of the distributions: normal, steady or gamma and its special case of the exponential distribution and Poisson for the obtained input empirical data, constituting a sample from the population, is proposed. The input data are a sequence of numbers obtained from the measurement of the current operating time of machines. These data can be obtained from the longwall shearer memory card, on which its operating parameters are recorded in each longwall. On this basis, it is possible to generate random values of both parameters for individual days of operation. The possibility of determining the haulage speed, based on the longwall shearer’s characteristics obtained from the computer simulation of the mining process, is also discussed. The simulation of the mining process is carried out using the GeneSiSv.3.1 software, developed for designing a picks layout on the drum. The characteristics of the shearer production potential also take into account the capacity of loading the cutting drum. It results from the presented characteristics that, when mining coal with a compressive strength of 27 MPa, the haulage speed is limited by the loading capacity of the cutting drum and, with greater cuttability, by the power of the electric motor driving the drum. The paper presents algorithms describing the procedure of generating random values necessary for determining the longwall production potential and the daily advance during the assumed period. The subject matter presented in the paper is part of a bigger project which concerns planning of a mine operation and developing a few longwalls in the conditions of bumping hazards.