An underground mine is a very complex production system within the mining industry. Building up the underground mine development system is closely related to the installation of support needed to provide the stability of mine openings. The selection of the type of support system is recognized as a very hard problem and multi-criteria decision making can be a very useful tool to solve it. In this paper we developed a methodology that helps mining engineers to select the appropriate support system with respect to geological conditions and technological requirements. Accordingly, we present a novel hybrid model that integrates the two following decision-making components. First, this study suggests a new approach for calculating the weights of criteria in an objective way named the Modified Preference Selection Index (MPSI) method. Second, the Magnitude of the Area for the Ranking of Alternatives (MARA) method is proposed as a novel multi-criteria decision-making technique for establishing the final rank of alternatives. The model is tested on a hypothetical example. Comparative analysis confirms that the new proposed MPSI–MARA model is a very useful and effective tool for solving different MCDM problems.

Ammonium nitrate (AN) primarily is used as a fertilizer but it is also very important compound in the production of industrial explosives. The application of ammonium nitrate in the production of industrial explosives was related with the early era of Nobel dynamite and widely increased with the appearance of blasting agents such as ANFO and Slurry, in the middle of the last Century. Throughout the world millions of tons of ammonium nitrate are produced annually and handled without incident. Although ammonium nitrate generally is used safely, accidental explosions involving AN have high impact resulting in loss of lives and destruction of property. The paper presents the basic properties of ammonium nitrate as well as hazards in handling of ammonium nitrate in order to prevent accidents. Several accidents with explosions of ammonium nitrate resulted in catastrophic consequences are listed in the paper as examples of non-compliance with prescribed procedures.

The uncertainty that dominates in the functioning of the electricity market is of great significance and arises, generally, because of the time imbalance in electricity consumption rates and power plants’ production capacity, as well as the influence of many other factors (weather conditions, fuel costs, power plant operating costs, regulations, etc.). In this paper we try to incorporate this uncertainty in the electricity price forecasting model by applying interval numbers to express the price of electricity, with no intention of exploring influencing factors. This paper represents a hybrid model based on fuzzy C-mean clustering and the interval-valued autoregressive process for forecasting the short-term electricity price. A fuzzy C-mean algorithm was used to create interval time series to be forecasted by the interval autoregressive process. In this way, the efficiency of forecasting is improved because we predict the interval, not the crisp value where the price will be. This approach increases the flexibility of the forecasting model.

When considering data and parameters in hydrogeology, there are often questions of uncertainty, vagueness, and imprecision in terms of the quantity of spatial distribution. To overcome such problems, certain data may be subjectively expressed in the form of expert judgment, whereby a heuristic approach and the use of fuzzy logic are required. In this way, decision-making criteria relating to an optimal groundwater control system do not always have a numerical value. Groundwater control scenarios (alternatives) are identified through hydrodynamic modeling of the aquifer, providing an indication of their effectiveness. The paper develops a fuzzy-stochastic multi-criteria decision-making model to deal with a topical problem: selection of the most suitable groundwater control system for an open-cast mine. Both real numerical and linguistic variables are used to express the values of all criteria that affect the final decision. In particular, it should be pointed out that the values of the criteria are varied over a predefined time horizon. For mathematical calculations, fuzzy dynamic TOPSIS and the stochastic diffusion process—geometric Brownian motion—were used. The proposed method is tested in a case study: the selection of an optimal groundwater control system for an open-cast mine.

Knowing mechanical properties of rocks incorporated with ultrasonic waves velocities investigations provide a secure basis for mine modelling. Uniaxial compressive strength, dynamic elastic modulus and ultrasonic waves velocities are just some of the rock properties that indicate on presence of discontinuities, stratification and fissures of rocks. Determining the relationship of these rock properties testing the rock samples that are corresponding to different rock types extracted from different mineral deposits represents the core of this study. In this paper, we statistically analyzed measured and calculated rock properties. We established the connection between these parameters creating empirical correlation equations. Using least squares method and simple linear regression analysis, we defined correlation coefficients and also developed empirical correlation equations.

This paper presents an analysis of the influence of burden deviation from the designed one on the intensity of blasting vibrations through the use of laboratory and field examinations. By definition, the burden represents the shortest distance from the axis of an explosive column charge to the free surface. It should be measured along the entire hole length, although, in practice, it is often measured only on the bench surface as the shortest distance from the axis of the explosive column charge to the crest. The real surface of the bench slope (free face) can be very irregular and should be considered during every blast. The deviation of burden in the blast pattern represents a serious problem in the field during blasting operation. Burden deviation from the designed one can be greater or lesser, affecting the results of blasting through poor fragmentation and sometimes causes unwanted effects like increased blasting vibrations or fly rock. The influence of burden deviation on the intensity of blasting vibrations was tested on a laboratory model, where 8 mm diameter holes were drilled into blocks with certain dimensions. The small explosive charges placed in blastholes were initiated. The design burden was set at 30 mm, as the distance from blastholes to the free face of the blocks. Any deviation in distance greater than the designed burden was taken as a parameter for comparison. During each initiation, vibrations were measured using a seismic instrument at a distance of 150 mm from the borehole. At the same time, the free face in the front of the blastholes was photographed to create a detailed 3D model of the blasted surface of the blocks for each blasting. Each measurement is presented on a diagram and classified depending on the values of the burden in the cases where the value of the burden is equal to the designed one, as well as any deviation that is smaller or larger than 30 mm. A total of 55 tests were carried out. The results were analyzed, and the model of dependence of each burden deviation from the designed one on the intensity of blasting vibrations was established under laboratory conditions. To verify the model, the same experiments were also applied in the field. The basic parameter of the model, the coefficient K, which represents the ratio of peak particle velocity and the surfaces of the blasted material from laboratory and field testing, indicates that there is a connection between these values. The deviation of the coefficient K, obtained from laboratory and field measurements, was 5.5%.