Mining Contract: Digital Technologies Improve Mine Safety and Health
Many advancements have been made in mining through automation and remote operation, and further adoption of digital technologies could address several persistent problems and serve many mines that face these same issues. From a safety and health perspective, removing the miner from hazards such as proximity to machinery and exposure to dust, gases, and roof falls makes mines safer, but remote operation may create new hazards, including unexpected equipment activation, accidents caused by software errors, and mechanical or electrical malfunctions.
Contract Status & Impact
This contract is ongoing. For more information on this contract, send a request to email@example.com.
This capacity-building contract provides for five distinct PhD dissertations that have in common the utilization of digital technologies to sense safety and health hazards in mines and to improve mine design, engineering, and administrative controls to mitigate these hazards and/or warn miners and mine management of their existence. By way of five subprojects, as detailed below, these efforts will support research investigating the safety and health impact of digital technologies that are finding increasingly broad application in the mining industry.
Mine workers continue to suffer from overexposures to respirable dust. Despite having a near real-time dust exposure vs. time record from the Personal Dust Monitor (PDM) 3700, miners’ working locations, along with their associated dust exposure levels, are not tracked. Location monitoring is necessary to predict hazardous exposure levels and implement mitigating engineering and administrative controls before a miner is exposed. For the first subproject, "Mine dust localization, mapping and visualization for engineering control interventions," the students and faculty lead will add geolocating capability to the PDM to obtain spatio-temporal dust exposure mapping to improve engineering and management controls for mine dust control.
Mine ventilation systems must dilute and render harmless toxic and explosive gases and dusts. The second subproject, "Adaptive mine ventilation design and explosion hazard visualization through real-time methane monitoring with data analytics," will identify and warn of harmful methane concentrations to prevent fires and explosions in underground coal mines through the following:
- An arrangement of real-time sensors whose location is either stationary or mobile (shield-mounted, longwall machine-mounted, or person-worn).
- Corresponding air flow and quality simulation using computational fluid dynamics (CFD) modeling.
- Digital feedback, visualization, and warning of fire and explosion hazards. Hazard feedback will focus on visualization and ventilation control to increase air flow as well as direct control of mining machinery to initiate a shutdown if an imminent danger exists.
For the third subproject, researchers will pursue two similar avenues of investigation: (1) assessment of support system performance in underground mines, and (2) assessment of slope stability hazards in open pit mines. Following preliminary investigations during the first year of the project, the participating student will select one of these as the primary focus area for a PhD dissertation. As such, the subproject is tentatively titled, "Leverage artificial intelligence to analyze remotely sensed data for ground control."
The fourth subproject, "A digital platform for collaborative mine design in VR, AR, and VRX," will develop a digital platform for a safe mine design in a collaborative environment where various system operations can interact with each other (e.g., haulage and ground control, haulage, and ventilation). The platform will allow for users to visualize the mining systems and their interactions in the design phase so that the system operators understand the complexity and make necessary design updates for safe mine operations. A key component in this package is visualization of safety and health hazards, including dust, explosive gases, unstable roof or ribs, and proximity of equipment. The platform will integrate mine design data and models to be visualized by collaborative teams in virtual reality (VR), augmented reality (AR), and virtual reality experience (VRX) environments.
The final subproject involves the growing use of lithium-ion (Li-ion) battery technologies in mines, which represents a change in the work environment and necessitates better understanding of the nature of the fire safety control structure. Compared to diesel equipment, battery equipment produces fewer respiratory hazards and much less waste heat, giving it significant advantages in deep, hot underground mines. The major disadvantage of Li-ion batteries is their high-energy density, which can cause thermal runaway fires with temperatures exceeding 600°C. Also, Li-ion batteries vent explosive hydrogen, methane, and carbon monoxide gas mixtures during overheating, prior to full-on thermal runaway. This subproject, "Systems theoretic process analysis (STPA) for mine fire risk assessment of lithium-ion (Li-ion) batteries," will reveal an overall system safety control structure for Li-ion battery fires so that the necessary fire safety controls needed for the industry can be identified. The research will also identify not only the role of sensors in fire monitoring but will show their interaction with the overall socio-technical mine system.
- Atmospheric Monitoring
- Calibration and Verification of Longwall Stress Models
- Continuous Monitoring of Airflow and Methane in Coal Mines
- Method for Improving Ventilation & Gas Monitoring with an Advanced Fiber Optic Based Mine-Wide Monitoring System
- New Developments with the Coal Mine Roof Rating
- Numerical Model Calibration for Simulating Coal Pillars, Gob and Overburden Response
- Remote Methane Sensors
- Roof Support
- Technology News 516 - ARMPS-HWM: New Software for Sizing Pillars for Highwall Mining
- Technology News 526 - Proceedings of the International Workshop on Rock Mass Classification in Underground Mining