Influence of rock properties on emission rate of Particulates Matter (Pm) during drilling operation in surface mines

Iranian Journal of Earth Sciences

مقاله 2، دوره 13، شماره 1، فروردین 2021، صفحه 14-20   

نوع مقاله: Original Research Paper

شناسه دیجیتال (DOI): 10.30495/ijes.2021.677471

نویسندگان

Koneti Nagesha¹؛ Harinandan Kumar^{* 2}؛ Muralidhar Munisingh¹

¹Madanapalle Institute of Technology and Science, Madanapalle, India

²Department of Petroleum and Earth Sciences, University of Petroleum and Energy Studies, Bidholi, Via Prem Nagar, Dehradun, Uttarakhand 248007, India

چکیده

The mining process generates significant amount of dust in the form of particulate matters into the atmosphere. Out of different mining process, opencast mining produces more dust than that of underground mining because of exposure in the ambiance. The mining operations are directly or indirectly involved in the production of dust particles. The activities like drilling operation, Blasting and haul road operations produce fugitive dust and causes significant deterioration of mine atmosphere. This fugitive dust consists of particulate matters (PM), which are more harmful to the human respiratory system. The prevention measures is only possible when the actual prediction of emission of those fugitive dust particles are possible. There is several model that predict the emission of the dust particles, but there is very less model to predict fugitive dust produced from a drilling operation in surface mines. In this paper, study was carried out to develop dust prediction model and to assess the influence of rock properties on dust emission. Based on the results obtained the developed model exhibit close proximity of predicted as well as field measured values with a regression coefficient of 0.75. Thus, the development of the model with effective prediction capability is the novelty of this paper. Decrease in dust emission rate was observed with increased moisture content present in drill cuttings, higher compressive strength, and density.

کلیدواژه‌ها

Dust؛ Emission؛ ANN؛ Multiple Regression Analysis؛ Rock Properties

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