Search

The thermal regime of underground mines, shaped by air temperature, velocity, and relative humidity, is a crucial factor for production and the health and safety of miners. While many aspects of this thermal regime have been thoroughly studied in the literature, local heat sources from mechanized equipment, such as load–haul–dump machines, conveyors, and auxiliary fans, have received comparatively little attention despite their significant impact on the thermal environment in mining development areas and stopes. This paper presents findings from a comprehensive study of the microclimatic air parameters in several nickel–copper and potash mines. We focus specifically on variations in air temperature in areas where mining equipment is operational. The heat output from different types of equipment, including load–haul–dump units, cutter–loaders, drilling rigs, conveyors, and auxiliary fans, has been quantified. We established empirical relationships for heat emissions from these machines and conducted a comparative analysis of their heat outputs. The main advantage of these relationships is their simplicity and the minimal number of input parameters required, making them practical for use in the field.

Abstract The paper explores the 3D stationary vortex structure of turbulent airflow near the dead-end face of a blind heading, ventilated via a forcing ventilation system. Despite its significance in blind heading ventilation, previous studies primarily focused on temporal dynamics of harmful impurities, overlooking flow structure details crucial for mass transfer processes. Our study delves into the ventilation flow structure across diverse parameters of the auxiliary ventilation system. Alongside standard flow visualization tools, we introduce three dimensionless indicators to comprehensively characterize flow structure, facilitating analysis of its variations with parameter changes and quantitative evaluation of system efficiency. Analysis revealed the formation of a single large-scale vortex within the entire range of considered ventilation system parameters in the heading. This vortex induces a significant increase in air circulation, approximately 2.5–3.5 times greater than airflow emerging from the ventilation duct’s end, thus intensifying mass transfer processes within the heading. We found that ventilation efficiency of the dead-end face zone in a blind heading with a 29.2 m² cross-section decreases linearly with increasing distance between the ventilation duct’s end and the dead-end face. However, compensating for this distance by increasing duct velocity is feasible, bearing significant implications for mine ventilation safety, particularly in ventilating blind headings with distant ducts from the dead-end face.

In recent years, there has been a notable integration of artificial intelligence (AI) technologies into mine ventilation systems. A mine ventilation network presents a complex system with numerous interconnected processes, some of which pose challenges for deterministic simulation methods. The utilization of machine learning techniques and evolutionary algorithms offers a promising avenue to address these complexities, resulting in enhanced monitoring and control of air parameter distribution within the ventilation network. These methods facilitate the timely identification of resistance faults and enable prompt calculation of ventilation parameters during emergency scenarios, such as underground explosions and fires. Furthermore, evolutionary algorithms play a crucial role in the advancement of methods for visual analysis of ventilation systems. However, it is essential to acknowledge that the current utilization of AI technologies in mine ventilation is limited and does not encompass the full spectrum of challenging-to-formalize problems. Promising areas for AI application include analyzing changes in air distribution caused by unaccounted thermal draft and gas pressure, as well as developing novel approaches for calculating shock losses. Moreover, the application of AI technologies in optimizing large-scale mine ventilation networks remains an unresolved issue. Addressing these challenges holds significant potential for enhancing safety and efficiency in mine ventilation systems.

Effective fire prevention in mine workings and tunnels requires a thorough theoretical analysis of the heat and mass transfer processes within these structures. This involves using established models to calculate non-isothermal air flow dynamics in long tunnels and mine workings. While the ventilation of tunnels has been extensively studied, significant challenges persist regarding mine ventilation systems, particularly due to their complex and branched topology. This study aimed to address these challenges and gaps in mine ventilation. We designed a laboratory bench to simulate an inclined mine working with a heat source (fire) and validated a mathematical model of heat and mass transfer in such settings. Using experimental measurements, we verified the model’s accuracy. It is important to note that our experimental and theoretical analyses focused solely on the thermal effects of a fire, without considering the release of harmful impurities. Using the validated model, we conducted multiparameter simulations to identify the conditions leading to the formation of a thermal slug in an inclined mine working and the subsequent reversal of air flow. The simulation data enabled us to determine the dependency of the critical heat release rate on the aerodynamic parameters of the mine working. Additionally, we evaluated the changes in average air density within a mine working at the critical heat release rate. These findings are crucial for the further development of a network-based method to analyze air flow stability in mine ventilation networks during fires.

The calculation of air distribution in large mine ventilation networks is usually carried out by numerically solving a system of equations representing Kirchhoff’s circuit laws. This formulation of the problem traditionally only considers the frictional air resistance of straight sections of mine airways. However, when analyzing the changing ventilation modes, it is also important to correctly consider the shock losses, which sufficiently affect the redistribution of airflows. The reason is that the shock loss factor strongly depends on the airflow rates at the junctions of mine airways. This paper presents a mathematical model of a ventilation network that considers shock losses. The model considers steady-state air distribution as well as natural draft. The significance of the shock was confirmed with a practical example; we describe the application of the proposed mathematical model for the analysis of air distribution in the ventilation network of a potash mine during planned airflow reversal.

The dynamics of methane–air mixtures in a dead-end drift of a potash mine are investigated in this study. Methane release is associated with the destruction of potash ore during mining operations. The studied dead-end drift is ventilated using an exhaust ventilation system in which fresh air is supplied through the drift, and polluted air is removed through a ventilation duct equipped with a fan. The regularities of the stationary distribution of methane in the drift are described using a 3D multiparametric numerical simulation. The size and shape of the methane cloud at the roof of the dead-end drift were analyzed depending on the ratio of the main mass transfer mechanisms in the system: forced convection due to the action of the fan, free convection due to the differing densities of the methane–air mixture, and turbulent diffusion. A criterion linking the Reynolds number, the gas Grashof number, and the length of the accumulated methane cloud is determined. Overall, the results of this study have important implications for developing new effective auxiliary mine ventilation systems that can improve the safety of mining operations.