If you have any problems related to the accessibility of any content (or if you want to request that a specific publication be accessible), please contact us at firstname.lastname@example.org.
Managing and Controlling the Thermal Environment in Underground Metal Mines
AdvisorKocsis, Karoly C.
Mining and Metallurgical Engineering
AltmetricsView Usage Statistics
The main aim of this research work was to discuss the methods of identifying and control heat in underground mine environments. The research contains three main sections as follow:1. Selecting an appropriate heat stress index for underground mining applicationMethods: The aim of this research study was to discuss the challenges in identifying and selecting an appropriate heat stress index for thermal planning and management purposes in underground mines. A method was proposed coupled to a defined strategy for selecting and recommending heat stress indices to be used in underground metal mines in the US and worldwide based on a thermal comfort model. Results: The performance of current heat stress indices used in underground mines varies based on the climatic conditions and the level of activities. Therefore, by carefully selecting or establishing an appropriate heat stress index is of paramount importance to ensure the safety, health and increasing productivity of the underground workers.Conclusions: This method presents an important tool to assess and select the most appropriate index for certain climatic conditions in order to protect the underground workers from heat related illnesses. Although complex, the method presents results that are easy to interpret and understand than any of the currently available evaluation methods.2. Best practices in use of continuous climatic monitoring systems for assessment of underground mine climatic condition:Methods: Major heat sources in an underground metal mine in Nevada was quantified using over one year of climatic data collection in both primary and auxiliary ventilation systems. Furthermore, auxiliary ventilation systems were examined in a development heading and a production area at our partner mine. Climatic models were developed and validated to simulate the climatic conditions based on intake airflow conditions and the heat load along the ducting system. Considerations were also given to the fact that arsenic concentrations may be present at the face. Different scenarios were studied to design and optimize the auxiliary ventilation systems in order to minimize the heat generated by multiple auxiliary fans and minimize arsenic concentration in the production workings.Results: The results show that the heat generated by different major heat sources can change throughout the mine as a function of surface temperature. Furthermore, current auxiliary ventilation design cannot maintain the comfort limits of the underground workers. In some cases, some type of cooling system must be utilized to retain the thermal comfort in production workings. Conclusions: In many instances, by simply adjusting or upgrading the auxiliary ventilation system in a problem area of a mine will effectively dilute the pollutants that are generated during production operations and provide adequate climatic conditions to the mine workers. This can be achieved through various methods such as: (1) extending the auxiliary duct towards the face, (2) installing an additional auxiliary fan to overcome the added pressure losses in the system, (3) changing the size of the fan, (4) switching from an “exhausting” arrangement to a “forcing” arrangement, and (5) installing an “overlap” auxiliary ventilation system.3. Quantifying the thermal damping effect in underground vertical openings using artificial neural network:Method: A nonlinear autoregressive time series with external input (NARX) algorithm was used as a novel method to predict the dry-bulb temperature (Td) at the bottom of the shaft as a function of surface air temperature. Furthermore, an attempt was made to quantify typical “damping coefficient” for both production and ventilation shafts through simple linear regression models.Results: The performance of the model was examined using climatic data collected at two underground mines during summer and winter. Analyses demonstrated that the artificial neural network (ANN) model could accurately predict the temperature at the bottom of a shaft. Comparisons between the collected climatic data and the regression-based predictions show that a simple linear regression model provides an acceptable prediction of the Td at the bottom of intake shafts. The same approach can be used to predict the thermal damping effect on the wet-bulb temperature (Tw) at the bottom of production and ventilation shafts.Conclusions: A comparison between collected data and the climatic modeling demonstrates that the ventilation or climatic modeling software packages do not have the ability take into account the “thermal damping effect (TDE)” (also known as thermal flywheel effect) when modeling the thermal environment in deep and hot underground mines. The major difficulty in incorporating TDE comes from a large number of variables interacting with each other plus the time-dependent heat and mass transport processes that control the flow of strata heat into/from the mine airways.