Computer aided ventilation design in underground mining

Ventilation systems in underground mining play a vital role in ensuring worker safety and health. In this study, a comprehensive optimization process was conducted to enhance the performance of the ventilation network in the Horzum lead-zinc mine. The primary objective was to reduce energy consumption and direct airflow more efficiently throughout the mine. To achieve this, the Ford–Fulkerson algorithm was implemented to model airflow, where the capacity of each connection between galleries was individually evaluated to determine the system's maximum flow rate. The resulting optimization data were integrated into the Ventsim™ software and successfully visualized over a three-dimensional representation of the mine geometry. Prior to optimization, the total energy demand was approximately 90,235 kW per hour; following the optimization, this value was reduced to 79,309 kW, yielding an energy saving of roughly 12%. Similar improvements were observed at the level of individual fans—for instance, one fan consuming 18,235 kW was reduced to 13,709 kW after optimization. Furthermore, simulations conducted under fire scenarios demonstrated significant advantages in emergency response management. While extinguishing a fire under the previous ventilation configuration took an average of 6 hours, the optimized system reduced this time to 4.5 hours, resulting in a 90-minute improvement in firefighting and cooling operations. Within the scope of the study, a specialized software tool was developed to analyze the performance differences between the existing and optimized ventilation networks designed using the Ford–Fulkerson algorithm. This tool not only identifies optimal escape routes but also calculates the latest possible time each route must be passed, allowing evacuation plans to be optimized with a time-sensitive approach. The system, which operates in integration with real-time sensor data obtained from the Ventsim™ software, enables engineers to develop dynamic, time-aware, and effective evacuation strategies. Consequently, it supports quick and well-informed decision-making during emergency situations. In conclusion, the optimization efforts led to notable improvements in energy efficiency and significantly enhanced the system's performance in emergency scenarios, thereby contributing positively to occupational safety. However, under a one-hour active fire scenario, the optimized and existing systems showed no substantial difference in terms of evacuation time.