A Mine Ventilation Program Integrated with Gob Flow Field Simulation

Feng-liang, WU; Xin-tan, Chang; Dan, Zhuo

doi:10.1007/978-981-13-1420-9_76

Cited by 3 publications

(3 citation statements)

References 5 publications

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“…Real-time airborne dust monitoring is adopted to identify different exposure zones or tasks or characterise the dust generation sources in mines (Gillies and Wu 2008; Wu and Gillies 2019). Therefore, Grimm aerosol spectrometers (model 1.108), which record the concentration of various dust particle sizes in real-time, were used to measure the dust concentration in this study.…”

Section: Field Measurements and Methodsmentioning

confidence: 99%

Airborne dust pollution due to mechanised scaling in underground metalliferous mine cross-cut drive under buoyancy-driven airflow

Paluchamy

Mishra

2022

Mining Technology

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Nowadays, mechanised scaling is extensively used in fully mechanised underground metalliferous mines (FMUMM) for removing potentially dangerous loose rocks from the mine roof and side walls. This study measures and analyses the generation and dispersion of airborne dust due to mechanised scaling operation by scaler in cross-cut (X-cut) drive of an underground mine using real-time aerosol spectrometers. The airborne dust is analysed in terms of the concentration of various size particles in total airborne dust (TAD). The analyses of different dust sizes, viz. ≤20 μm, ≤15 μm, ≤10 μm, ≤5 μm and ≤1 μm revealed that the per cent proportion of ≤1 μm and ≤10 μm varies from 2.6 to 22.4% and 60.5 to 88.3%, respectively, in the cross-cut. Moreover, the concentration proportions of alveolic and thoracic dusts in TAD during the 20-min retention time are assessed. This study can aid in developing safe re-entry periods and efficient dust control appliances.

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Section: Field Measurements and Methodsmentioning

confidence: 99%

Airborne dust pollution due to mechanised scaling in underground metalliferous mine cross-cut drive under buoyancy-driven airflow

Paluchamy

Mishra

2022

Mining Technology

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“…In general, literature contains many works on the graphical methods for analyzing topologically complex mine ventilation networks (Maleki et al, 2018 ; Wu et al, 2019 ; Liu et al, 2022b ; Bosikov et al, 2023 ), but we do not discuss these works here, since they are not use AI technologies.…”

Section: Application Areas Of Ai Technologiesmentioning

confidence: 99%

Application of artificial intelligence in mine ventilation: a brief review

Semin,

Kormshchikov

2024

Front. Artif. Intell.

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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.

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“…They have also been useful in modelling the spread of blast fumes, heat and contaminants within the mine ventilation circuit. These softwares have also played key roles in accident control system by simulating several scenarios to support decision-making process in the event of incident in the mine to address various issues such as gas or fire control problems underground (Wu et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Calibration of LKAB’s Konsuln test mine ventilation model using barometer Pressure-Quantity (PQ) survey

Gyamfi¹,

Halim²,

Martikainen³

2021

Mine Ventilation

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Ventilation projects such as installation of primary fans, refrigeration system, heating systems, and Ventilation of Demand (VOD) system require some simulations to ascertain their benefits and fulfilment of their purpose before the actual financial commitment is made to execute such projects. Ventilation models used for the simulations should provide some degree of accuracy to ensure that their results will reflect the actual mine ventilation circuit. This paper outlines a barometer Pressure-Quantity (PQ) survey that was done to calibrate the existing ventilation model of LKAB's Konsuln test mine before it was used in a VOD design study to determine whether it will be feasible for Konsuln mine to install the system. The results show a good correlation between the simulated airflows in the calibrated model and the actual underground measured airflow quantities and primary fans pressure. This good correlation has validated the model for its use in Konsuln VOD design study.

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A Mine Ventilation Program Integrated with Gob Flow Field Simulation

Cited by 3 publications

References 5 publications

Airborne dust pollution due to mechanised scaling in underground metalliferous mine cross-cut drive under buoyancy-driven airflow

Airborne dust pollution due to mechanised scaling in underground metalliferous mine cross-cut drive under buoyancy-driven airflow

Application of artificial intelligence in mine ventilation: a brief review

Calibration of LKAB’s Konsuln test mine ventilation model using barometer Pressure-Quantity (PQ) survey

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