This article describes an approach of mathematical processing of signals (seismograms) from five blasthole charges from experimental blasting, each 3 m deep, with equal explosive weight (1 kg), and equidistant (3 m) from one other. The seismic explosive waves were measured at a 13 to 25 m distance. This article provides spectral analysis, wavelet analysis, and fractal analysis results. It defines the dependence of dominant frequency and amplitude on the distance to the blast center. According to the experimental data, the dominant frequency is calculated as y = 1.0262x0.2622 and the amplitude dependency as y = 18.139x−2.276. Furthermore, the analysis shows that 80% of the entire signal is concentrated in half the area of frequency range, i.e., the low frequency zone is of the most interest. This research defines the dependence of distance on the energy value of signal wavelet analysis. It is demonstrated that, according to the experimental data, the 12th frequency range is closely correlated with the distance values. This article gives the definitions of entropy, correlation dimension, and predictability time. This experiment shows that entropy and correlation dimension decrease but predictability time increases when the distance to the blast center increases. This article also describes the method for determining optimal drilling and blasting parameters, and concludes with the possibility of applying the analytical results to predicting and enhancing drilling and blast-ing operations.

The energy and its entire related infrastructure are the main drivers for a economic development and for ensuring a good level of employment. As part of a global study about international energy sector, we evaluate here the impact of technological changes on the state of the energy infrastructure. This study includes a detailed analysis of the global challenges facing the energy industry. We propose scenarios for the development of a modernized energy infrastructure with an assessment of the entire energy system. Our evaluation indicators are chosen in terms of the reliability of the energy infrastructure, of its quality, of the accidents that may happen and of the consequent environmental risks. This study is particularly adapted for forecasting the necessary measures (of technical nature, of governance kind) that have to be implemented to reduce the acceleration of the infrastructure deterioration rate. Our results reveal that the use of digital and information technologies has many positive impacts on the development and on the control of an efficient consumption of energy. In addition, our predictions, due to the further modernization of the energy sector, can contribute and help in the creation of preconditions that will be highly stimulating and profitable to the growth of investments in the energy infrastructure.

This work presents results of experimental researches of influence of various hightemperature thermomechanical treatment (HTMT) modes in 35KhGSA steel – material applied in rock-destroying cutters – on hardness and wear rate for the most common abrasive rock in mining operations – sandstone. It has been found out that HTMT leads to increase of steel hardness and reduction of wear rate compared to heat treatment applied at manufacture of cutters. The maximal increase of hardness (by 23%) and reduction of wear rate (by 38%) corresponds to the mode of distortion accumulation of ∼1,5 at 900 °С at water quenching and tempering at 230 °C. A conclusion that thermomechanical treatment is an effective way to increase the wear resistance of steels applied in the conditions of abrasion wear has been drawn.