Atmospheric monitoring systems (AMS) are required when using air from conveyor belt entries to ventilate working sections in U.S. underground coal mines. AMS technology has the potential to increase fire safety mine-wide, but research is needed to determine the detection and response times for fires of a variety of combustible materials. To evaluate the potential of an AMS for fire detection in other areas of a coal mine, a series of full-scale fire experiments were conducted to determine detection and response times from fires of different combustible materials that are found in U.S. underground coal mines, including high- and low-volatility coals, conveyor belts, brattice materials, different types of wood, diesel fuel, and a foam sealant. These experiments were conducted in the Safety Research Coal Mine (SRCM) of the U.S. National Institute for Occupational Safety and Health (NIOSH) located in Pittsburgh, PA, using a commercially available AMS that is typical of current technology. The results showed that through proper selection of sensors and their locations, a mine-wide AMS can provide sufficient early fire warning times and improve the health and safety of miners.

A calibrated and well-tuned ventilation network model plays a critical role in mine ventilation planning, optimization, and ventilation control. Moreover, it is critical to the mine fire simulation program as well since the fire simulation is built upon the mine ventilation model. The contaminants generated from a fire are transported by airflows throughout the mine ventilation system. The accuracy of the fire simulation results not only depends on the fire source model itself but also on the ventilation network model. With the increasing use of atmospheric monitoring systems in underground mines, airflow is continuously monitored using airflow sensors in the key areas of mines to ensure a steady and reliable ventilation. Experimental studies have been conducted at an experimental mine, the Safety Research Coal Mine (SRCM), to gain a better understanding on how to use the continuously monitored airflow data to improve the calibration of the mine ventilation network model. This paper introduces an improved method to calibrate a ventilation network using continuous airflow monitoring and addresses the practical problems encountered while calibrating and tuning the ventilation network of the SRCM using continuously monitored airflow data. In this study, the fluctuation of the air velocity sensor readings is analyzed, and the sensor location correction factors are applied to obtain a more accurate average air velocity for the ventilation network calibration. © 2022, This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply.

Mining vehicle manufacturers are developing lithium-ion (Li-ion) battery electric vehicles as an alternative to diesel-powered vehicles. In gassy underground mines, explosion-proof (XP) enclosures are commonly used to enclose electrical ignition sources to prevent propagation of an internal methane-air explosion to a surrounding explosive atmosphere. Li-ion batteries can create pressurized explosions within sealed enclosures due to thermal runaway (TR). NIOSH researchers measured TR pressures of nickel manganese cobalt (NMC) cathode type 18650 Li-ion cells, model MH1, as a function of free space within sealed enclosures and observed an inverse power relationship. TR pressure-rise rates, gas quantities, and temperatures were also measured. A confined NMC cell with 92.5 mL of free space produced 232 bar of pressure, far exceeding minimum pressure containment specifications for conventional XP enclosures. Approximately 287 times the cell volume of free space would be needed to reduce the TR pressure of these cells to 8.62 barg (125 psig) per U.S. Code of Federal Regulations, Title 30, Part 18. The NMC cell TR pressures were significantly higher than those measured previously for iron phosphate cathode Li-ion cells under comparable confinement conditions. 2022

This paper presents the results of large-scale fire experiments on evaluating the performances of carbon monoxide (CO) and smoke sensors at low ventilation velocities. Experiments using three different combustibles—conveyor belt, coal, and diesel fuel—were conducted in the Experimental Mine at the National Institute for Occupational Safety and Health (NIOSH) Bruceton Research Facility. A total of eight sensor stations were located downstream of the fire with each station containing CO, smoke, carbon dioxide, oxygen, humidity, barometric pressure, temperature sensors, and two airflow sensors. The airflow velocity ranged from 0.22 to 0.26 m/s (44 to 51 fpm) in the tests. The response times were recorded for the CO and smoke sensors at each sensor station when smoke and gaseous products of combustion of each burning combustible reached the station. The response times of the CO sensors were used to determine the appropriate sensor spacing in the belt entry with a low air velocity. The performance of the smoke sensor was found to be affected by the high humidity in the experiments. The results on proper selection of sensors and the determination of sensor spacing at a low ventilation velocity can be helpful for ensuring sufficient early fire warning for underground workers, thereby improving the health and safety of miners.

Hydrogen (H2) gas released during battery charging can result in cross-interference for carbon monoxide (CO) sensors used for early fire detection and compromise the integrity of the mine atmospheric monitoring system (AMS). In this study, a series of laboratory-scale and full-scale experiments were conducted to evaluate the responses of different CO sensors to H2 gas. In the laboratory-scale experiments, constant H2concentrations in the airflow, from 100 to 500 ppm, pass through sensors. While in the full-scale experiments, increasing H2concentrations generated as a byproduct from charging the batteries at the battery charging station rise to the sensors under different ventilation scenarios. The H2 concentrations at the CO sensor location were measured using H2 sensors and were correlated with the CO sensor response. The effects of ventilation and sensor location on the CO sensors responses were also analyzed. The results of this study can help mining companies to select appropriate CO sensors and improve the deployment of these sensors to ensure the safeguard of underground miners.

The primary danger with underground mine fires is carbon monoxide poisoning. A good knowledge of smoke and carbon monoxide movement in an underground mine during a fire is of importance for the design of ventilation systems, emergency response, and miners escape and rescue. Mine fire simulation software packages have been widely used to predict carbon monoxide concentration and its spread in a mine for effective mine fire emergency planning. However, they are not highly recommended to be used to forecast the actual carbon monoxide concentration due to lack of validation studies. In this article, MFIRE, a mine fire simulation software based on ventilation networks, was evaluated for its carbon monoxide spread prediction capabilities using experimental results from large-scale diesel fuel and conveyor belt fire tests conducted in the Safety Research Coal Mine at The National Institute for Occupational Safety and Health. The comparison between the simulation and test results of carbon monoxide concentration shows good agreement and indicates that MFIRE is able to predict the carbon monoxide spread in underground mine fires with confidence. The Author(s) 2018.

With the increased use of mobile diesel-powered equipment in underground mines, the fire risk posed by underground diesel fuel storage areas is a concern. To reduce the risk associated with the storage and transfer of large quantities of diesel fuel in permanent underground mine storage areas, an experimental study was conducted to investigate the responses of different sensors for early detection of diesel fuel fires in a storage area. Fire sensors tested in this study were four carbon monoxide (CO) sensors, two smoke sensors, and one flame sensor. A series of fire tests were conducted in the NIOSH Safety Research Coal Mine, Bruceton, PA, using various fire sizes at different ventilation airflow velocities and fire locations. Response times for different sensors were analyzed, and the results suggest that the flame sensor and smoke sensors resulted in shorter response times in most tests compared to the CO sensors. Based on the test results, the appropriate sensor locations for early fire detection in a diesel fuel storage area were identified. The results of this study can help mining companies to select appropriate fire sensors for underground diesel fuel storage areas and improve the deployment of these sensors to ensure the safety of underground miners.

When combustible materials ignite and burn, the potential for fire growth and flame spread represents an obvious hazard, but during these processes of ignition and flaming, other life hazards present themselves and should be included to ensure an effective overall analysis of the relevant fire hazards. In particular, the gases and smoke produced both during the smoldering stages of fires leading to ignition and during the advanced flaming stages of a developing fire serve to contaminate the surrounding atmosphere, potentially producing elevated levels of toxicity and high levels of smoke obscuration that render the environment untenable. In underground mines, these hazards may be exacerbated by the existing forced ventilation that can carry the gases and smoke to locations far-removed from the fire location. Clearly, materials that require high temperatures (above 1400 K) and that exhibit low mass loss during thermal decomposition, or that require high heat fluxes or heat transfer rates to ignite represent less of a hazard than materials that decompose at low temperatures or ignite at low levels of heat flux. In order to define and quantify some possible parameters that can be used to assess these hazards, small-scale laboratory experiments were conducted in a number of configurations to measure: 1) the toxic gases and smoke produced both during non-flaming and flaming combustion; 2) mass loss rates as a function of temperature to determine ease of thermal decomposition; and 3) mass loss rates and times to ignition as a function of incident heat flux. This paper describes the experiments that were conducted, their results, and the development of a set of parameters that could possibly be used to assess the overall fire hazard of combustible materials using small scale laboratory experiments.

Atmospheric monitoring systems (AMS) have been widely used in underground coal mines in the United States for the detection of fire in the belt entry and the monitoring of other ventilation-related parameters such as airflow velocity and methane concentration in specific mine locations. In addition to an AMS being able to detect a mine fire, the AMS data have the potential to provide fire characteristic information such as fire growth - in terms of heat release rate - and exact fire location. Such information is critical in making decisions regarding fire-fighting strategies, underground personnel evacuation and optimal escape routes. In this study, a methodology was developed to calculate the fire heat release rate using AMS sensor data for carbon monoxide concentration, carbon dioxide concentration and airflow velocity based on the theory of heat and species transfer in ventilation airflow. Full-scale mine fire experiments were then conducted in the Pittsburgh Mining Research Division's Safety Research Coal Mine using an AMS with different fire sources. Sensor data collected from the experiments were used to calculate the heat release rates of the fires using this methodology. The calculated heat release rate was compared with the value determined from the mass loss rate of the combustible material using a digital load cell. The experimental results show that the heat release rate of a mine fire can be calculated using AMS sensor data with reasonable accuracy.

The objective of this study was to develop a laboratory-scale method to rank the ignition and fire hazards of commonly used underground mine materials and to eliminate the need for the expensive large-scale tests that are currently being used. A radiant-panel apparatus was used to determine the materials' relevant thermal characteristics: time to ignition, critical heat flux for ignition, heat of gasification, and mass-loss rate. Three thermal parameters, TRP, TP1 and TP4, were derived from the data, then developed and subsequently used to rank the combined ignition and fire hazards of the combustible materials from low hazard to high hazard. The results compared favorably with the thermal and ignition hazards of similar materials reported in the literature and support this approach as a simpler one for quantifying these combustible hazards.

Conveyor belt fires in an underground mine pose a serious life threat to the miners. This paper presents numerical and experimental results characterizing a conveyor belt fire in a large-scale tunnel. Acomputational fluid dynamics (CFD) model was developed to simulate the flame spread over the conveyor belt in a mine entry. Thermogravimetric analysis (TGA) tests were conducted for the conveyor belt and results were used to estimate the kinetic properties for modeling the pyrolysis process of the conveyor belt burning. The CFD model was calibrated using results from the large-scale conveyor belt fire experiments. The comparison between simulation and test results shows that the CFD model is able to capture the major features of the flame spread over the conveyor belt. The predicted maximum heat release rate, and maximum smoke temperature are in good agreement with the large-scale tunnel fire test results. The calibrated CFD model can be used to predict the flame spread over a conveyor belt in a mine entry under different physical conditions and ventilation parameters to aid in the design of improved fire detection and suppression systems, mine rescue, and mine emergency planning.