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Surface mining
Published in A.J.S. (Sam) Spearing, Liqiang Ma, Cong-An Ma, Mine Design, Planning and Sustainable Exploitation in the Digital Age, 2023
A.J.S. (Sam) Spearing, Liqiang Ma, Cong-An Ma
The aim of drilling and blasting is to cost effectively break the rock (initially overburden then the ore itself) to a size that can be easily and effectively loaded and transported using the equipment suite available.
The Anatomy of a Mine
Published in Karlheinz Spitz, John Trudinger, Mining and the Environment, 2019
Karlheinz Spitz, John Trudinger
Environmental impacts due to drilling and blasting include dust emissions, noise, vibration, and greenhouse gas emissions. Visible dust plumes from blasting are classed more as an aesthetic impact or a source of neighborhood annoyance, rather than a health risk. For most mining operations, however, the major sources of dust emission are the haul roads rather than the more transient dust clouds caused by blasting. Peak noise is used to assess overpressure from blasting. Planners limit blast noise by using good stemming in drill holes, and by limiting the Maximum Instantaneous Charge detonated simultaneously, through the incorporation of delays. Dust, noise and vibration due to blasting are among the most noticeable effects of mining and hence figure prominently among complaints from neighboring communities.
Blasting
Published in Duncan C. Wyllie, Christopher W. Mah, Rock Slope Engineering, 2017
Duncan C. Wyllie, Christopher W. Mah
The quality of blast has a significant effect on components of the rock excavation cost such as secondary drilling and blasting of oversize boulders, loading rate, the condition of the haul roads, and loader and truck maintenance. For example, oversized fragments, hard toes, tight areas and low muck piles (caused by excessive throw) have the most significant detrimental effect on the excavation rates. Therefore, careful evaluation of the blast to determine how improvements could be made to the design is usually worthwhile.
A new optimisation model for the selection of optimal cut-off grade using multi-sequential decision algorithm in open-pit metalliferous deposits
Published in International Journal of Mining, Reclamation and Environment, 2023
Pritam Biswas, Rabindra Kumar Sinha, Phalguni Sen
The stripping ratio () is a crucial metric that plays an important role in determining the of the reserves;. Mining firms earn revenue by mining mineral deposits and refining them into a product to sell. Revenue is calculated using the product of tonnes of ore processed, average mill head grade, percent recovery over concentrating and refining, and the product’s selling price. During production, the mine system has both variable and fixed expenses. Variable expenditures are further subdivided into those connected to mineral extraction and smelting and those associated to waste excavation and treatment. Variable expenses include drilling and blasting, hauling, dumping, rehabilitation, and other costs. Fixed costs include general administrative expenses and any other costs that are not reliant on production. By discounting capital costs and removing them from the discounted cash flow, the can be determined. Now, utilising all of the above-mentioned parameters consecutively, construct the equation for calculating is determined by Equation 12:
Optimisation of open-pit mine production scheduling considering optimum transportation system between truck haulage and semi-mobile in-pit crushing and conveying
Published in International Journal of Mining, Reclamation and Environment, 2022
Mohammad Shamsi, Yashar Pourrahimian, Mehdi Rahmanpour
The preparation starts with the block’s information inside the final pit limit. This information is the coordinates of the blocks and each block’s grade, density, tonnage, and rock type. In the second step, candidate locations of crushers are considered. These candidate locations are the input of the model. Each location can be the optimal point for the ore or waste crusher, which the model will determine as the optimisation output. In the next step, capital costs (CAPEX), operating costs and in-depth operation costs (OPEX) are calculated. These costs are drilling and blasting, loading, transportation (conveyers, SMC, and trucks), processing, smelting, and refining, which calculated based on the rock type, mine life, expected lifespan, production capacity, and the location of the processing plant, waste dump, and candidate crushers. According to the problem assumptions, the costs calculated at this stage are deterministic.
Computer-aided design of rational parameters for the location of blasthole charges in horizontal underground development
Published in Mining Technology, 2022
B. R. Rakishev, A. A. Orynbay, A. B. Mussakhan, A. I. Tuktibayev
Until now, the parameters of the location of blasthole charges in the development workings are mainly established on the basis of experimental data. The specific consumption of explosives is taken as the main criterion, which predetermines the required number of holes in a given underground mines (Kutuzov and Andrievsky 2002; Kozyrev and Fattakhov 2007; Kutuzov 2007; Khomenko et al. 2011; Labinsky 2013; Vokhmin et al. 2014; Kirsanov et al. 2015). A similar situation takes place at foreign mining enterprises (Langefors and Kihlström 1978; Chakraborty et al. 1998; Hustrulid and Bullock 2001; Lu et al. 2011; Catalan and Onederra 2016; Chai et al. 2019; Chandrakar et al. 2021). Rational parameters of drilling and blasting operations (D&B) in the faces of preparatory and working underground mines: the type of cut, schemes and parameters of the location of blasthole charges in the cut and the rest of the blasted layer depends on its size, physical and mechanical properties of rocks, and physicochemical characteristics of the proposed explosive. In view of their importance and relevance, these issues are constantly in the centre of attention of specialists engaged in improving blasthole blasting technologies during underground mining (Langefors and Kihlström 1978; Chakraborty et al. 1998; Hustrulid and Bullock 2001; Kutuzov and Andrievsky 2002; Kozyrev and Fattakhov 2007; Kutuzov 2007; Khomenko et al. 2011; Lu et al. 2011; Labinsky 2013; Vokhmin et al. 2014; Kirsanov et al. 2015; Catalan and Onederra 2016; Chai et al. 2019; Chandrakar et al. 2021).