Underground mine tunnels, drifts, and mine headings are susceptible to the impact of convergence. The convergence has a big influence on further measurements such as airflow and the volume concentration of methane and other gases. In most cases, deformation of arch supports lead to getting a smaller cross-section area. A comparison is made between five methods of measuring the cross-sectional area of a mine tunnel. The reference size of the six cross-section mine drift areas were obtained by Terrestrial Laser Scanning, which were then compared with the cross-section areas obtained by four other methods. The following methods were considered: area calculation using CAD software, an empirical method, approximation by a semi-ellipse and approximation by a semi-ellipse with attached straight sections. This article presents the quantitative and qualitative differences of the obtained results. Differences in the calculated cross-sectional areas of the mine drift are discussed, and reasons for the differences are determined. In addition, the advantages and disadvantages of each method are indicated.

The article shows the results of research on methane concentration changes along mine galleries. The experiment was conducted in a longwall area mined using a U-type system, and the results were obtained in situ. The main goal was to measure methane concentration by function of gallery length and dividing segments of methane data into segments, which ultimately enabled separate analysis of these methane data. The analysis led to the diagnosis of methane hazard through the detection of exceedance of the assumed tolerance area.

Methane (CH₄) is one of the most important greenhouse gases, and substantially impacts climate change. Over a 20-year period, its global warming potential (GWP) is approximately 80 times higher than that of carbon dioxide (CO₂). One of the significant sources of methane emissions is the hard coal mining industry, particularly regarding the release of methane with mine ventilation air. Methane released from coal seams during mining operations and discharged into the atmosphere through exhaust shafts is referred to as VAM (Ventilation Air Methane). In the context of the European Union’s climate policy, activities aimed at reducing and utilizing VAM emissions are gaining increasing importance. One initiative supporting the development of such solutions is the research project ProVAM (Reduction of Ventilation Air Methane Emissions in the Coal Mining Transformation Process), implemented by a consortium of scientific and industrial institutions from EU member states. The project focuses on developing guidelines and selecting technologies dedicated to the utilization of VAM. This article presents a methodology for assessing parameters associated with VAM emissions and provides a characterization of the selected mine exhaust shafts analyzed within the ProVAM project. Key technical factors affecting the feasibility of using oxidation technologies to reduce methane emissions from hard coal mining are identified.

This study presents the results of electrochemical impedance spectroscopy (EIS) conducted on a commercial 38120S cylindrical LiFePO₄ cell with a nominal capacity of 10 Ah. Measurements were performed at various states of charge, and the parameters of an equivalent circuit model were subsequently identified. The model consists of an inductance, ohmic resistance, two resistor–constant phase element (R-CPE) pairs, and a CPE representing diffusion effects. To ensure high measurement repeatability and minimize data dispersion, a surrogate model was used for equipment calibration, and a custom fixture was designed to maintain consistent cell positioning. Each measurement session was preceded by an open-circuit voltage reading and a relaxation period of approximately 24 h to ensure steady-state conditions. Furthermore, impedance spectra were analyzed over a range of frequencies by simulating model responses using various CPE constants. These simulations were visualized in LTspice and discussed, providing practical insights into the initialization of equivalent circuit model identification algorithms.

This article discusses the challenges of coal mine safety, particularly methane hazards, in the context of decreasing workforce and the need for more autonomous solutions. As hard coal production faces a phase-out due to international energy policies, the mining industry struggles with retaining skilled workers. The Sectional Methane Hazard Detection System (SDZM) is proposed as an autonomous solution to detect methane hazards by measuring methane concentrations along underground workings. The system operates using a series of algorithms that analyze the concentration data and identify hazard zones without the need for highly qualified personnel. The SDZM method involves collecting methane concentration data from different sections of the mining operation and comparing them to reference profiles to assess potential hazards. A study conducted in the 841A longwall area of KWK B mine used simulations to assess methane distribution, which was then used to test the SDZM system’s algorithms. The results show that the system can accurately detect high methane hazard levels, with sensitivity varying depending on the parameters set, such as the tolerance field for methane concentration changes. The study concluded that the SDZM system is effective in detecting methane hazards, requiring minimal additional skills from workers. The system’s performance can be enhanced by adjusting parameters like the methane concentration tolerance field, though excessively narrow tolerances could lead to false positives. Overall, the SDZM provides a valuable tool for enhancing safety in mines by autonomously identifying high-risk areas related to methane emissions.