Underground » Ventilation, Gas Drainage and Monitoring
Long term exposure to dust particles, in particular respirable dust, continues to present a health and safety hazard to mine workers in underground coal mines. Workers who are exposed to coal dust can develop occupational lung diseases including coal workers' pneumoconiosis (CWP) or 'black lung', progressive massive fibrosis (PMF), and chronic obstructive pulmonary disease (COPD). This project aims to develop an immersive simulation tool for dust and ventilation flow dynamics in an interactive virtual environment to demonstrate the exposure impact of certain working conditions and dust mitigation practices in longwall development panels.
An evaluation of dust exposures within underground mines from historical data has found that the longwall development panel was the second highest location for dust exposures. A critical examination of the monitoring data clearly demonstrated that the top three contributing factors to high levels of dust exposure included the cutting of stone, the position of ventilation tubes, and the rate of ventilation. This project focused on development panels utilising Joy12CM30 miners due to their widespread use in industry. This allowed the definition of three overarching scenarios in development panels with due consideration of the top three contributing factors to be extensively studied in mine site dust monitoring, computational fluid dynamics (CFD) modelling and Virtual Reality (VR) development process. The scenarios mainly include cutting coal or roof stone, ventilation tube advanced to a good standard or a poor condition, and varying ventilation rates. Dust flow has also been a concern in the process of breaking-away and holing through of cut-through drivage which is considered and modelled as additional scenarios in this project.
Dust monitoring was undertaken in a development panel on three shifts, using both real-time and static dust monitors. For the most part the monitoring data matched expectations with the highest dust concentrations measured closest to the ventilation tube. It was also found the high dust concentrations occur centrally on the far side (from the vent tube) of the miner which was attributed to a combination of dust roll back, dust from loading the shuttle car and dust flowing up underneath the miner. These dust monitoring data was then used with other site-specific information for CFD simulations and modelling results validation and calibration.
Three dimensional (3D) CFD models were developed to conduct transient simulations of ventilation and respirable dust flow patterns based on mining conditions (e.g., panel layout, ventilation and equipment) and dust monitoring data. The CFD modelling used an integrated CFD-Discrete Element Method (DEM) approach allowing for the modelling of air and dust particle dispersion from a Lagrangian view and a discrete perspective. Based on the three main overarching scenarios, in total 12 cases were simulated to allow various aspects of the gateroad development process to be understood. The simulation results allow for increased insight and understanding of the dust and ventilation behaviour in various development operations and cutting scenarios and the effectiveness of applied controls. Setup of the simulations relied on the dust monitoring data recorded on site to develop a calibrated model thus allowing for various other scenarios to be simulated with confidence, and the development of a CFD-VR tool to visualise the large but authentic simulation data of ventilation and dust flow. The results of the computational simulations generally aligned with expectations, however, the CFD modelling represents a key technology in allowing the project to be successfully advanced to the development of the VR environment.
To overcome challenges, the project required the development of a novel method to convert and filter the data into a suitable form that could be transferred and loaded on a portable Meta Quest 2 VR headset for interactively visualising dust data. The overall process consists of three steps to process the raw CFD data and to filter it to significantly reduce the volume of data while preserving the visual fidelity of the resulting data. The goal was to enable real-time rendering of CFD data on a VR headset with limited memory and computational power. The results demonstrate that the developed method managed to preserve fidelity while significantly reducing the total amount of CFD data. Hence, the developed method managed to solve the problem of how to reduce the raw CFD data into a form suitable for real-time visualisation in VR.
The implementation of dust simulation data in VR presented some technical challenges. Simulation data were sampled in such a way that they can be imported and rendered in the VR environment. The VR environment was designed to maximise the resources allocated to the simulation data. Novel methods were developed for rendering the dust particles at each time step and the particle would have no other movement, while the dust velocity is visualised using a separate option that showed colour based on a gradient scale. This allowed us to visually convey particle speed at different positions throughout the simulation without the need for the actual movement of the particles to be simulated. In order to have the airflow data visualised in a useful manner the velocity was discarded and instead focus is placed on the path of the air. The developed tool is a self-guided learning experience where users can fit the headset and be taken through a predefined learning experience with moderate user interaction. The VR tool guides users through a number of cutting scenarios that demonstrate safe and unsafe situations. The dust simulations clearly show where the dust is going under different circumstances. Voice-over is used to educate users about what they are seeing and encourages them to engage with the content. Users are able to teleport around the room and view the miniature development panel from many different angles. The user can also enter the mine at a 1:1 scale to see the simulation from the point of view of an operator. Finally, the menu shows a quiz button that tests users on what they have learned.
The CFD-VR system has been validated in the form of independent assessments conducted throughout the project from the VR consultant on the team and via a series of industry showcases. The evaluation of an independent VR consultant proved invaluable for the project, allowing the team to receive regular feedback on the development of the project with advice on how it could be improved. This was further aided through the industry workshop where a varied cross-section of users could be surveyed for feedback ranging from specific development heading operators' perspectives to people who had never been underground. The team would recommend a similar approach be taken for other projects in the future.
A number of industry showcase activities have been organised to gain feedback from the industry and promote technology transfers and applications of the CFD-VR system. These showcases include a dedicated workshop for industry participants, invited on-campus (UOW) review, gas outburst seminars, the NSW Standing Dust Committee Forum, and presentations to the Australian Institute of Occupational Hygienists Conference (AIOH 2022). These industry showcases enable stakeholders or interested parties to gain a better understanding of dust and ventilation behaviour in various development operations and cutting scenarios, and provide feedback on the developed intuitive VR training tool. Significant improvements have been made according to feedback and an improved VR training tool has been developed for stakeholders to start to use in their operations. The implementation of the CFD-VR on the portable VR headsets (Meta Quest 2) is a game-changer to allow future industry training to take place on site for improving efficiency, safety and productivity of mining operations. Further requests for industry showcases and training using the CFC-VR tool have been received from operating mines.
This project has successfully developed a robust methodology integrating several advanced modelling and computational technologies for a VR visualisation and educational tool that can more intuitively and comprehensively communicate the results of CFD simulation data to mine workers.