Rock Mechanics
M. Lotfi; B. Tokhmechi
Abstract
Nowadays, Barton’s Joint Roughness Coefficients (JRC) are widely used as the index for roughness and as a challenging fracture property. When JRC ranking is the goal, deriving JRC from different fractal/wavelet procedures can be conflicting. Complexity increases when various rankings outcome from ...
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Nowadays, Barton’s Joint Roughness Coefficients (JRC) are widely used as the index for roughness and as a challenging fracture property. When JRC ranking is the goal, deriving JRC from different fractal/wavelet procedures can be conflicting. Complexity increases when various rankings outcome from different calculation methods. Therefore, using Barton’s JRC, we cannot make a decision based on the proven mathematical theories because each method has a different rank. Ideally, these rankings must be equal but, in practice, they are different for each method. To solve this problem and to achieve a robust and valid ranking for JRC, Condorcetand Borda count methods have been used. These methods have been proposed as fusion approaches. Re-ranking of JRC using different methods integrated with Condorcet showed confusion in ranking of the JRC4, JRC5, and JRC6 profiles. This ambiguity is equal to equalizing decision conditions about all the three at the examination of the winners, losers, and draws in pairwise matrices. Therefore, Borda Count was applied and resulted in robust rankings. In fact, a new approach for a roughness measurement is presented. A new JRC ranking called JRCN is introduced. This new ranking shows a lower sum of squared errors (0.00390) in comparison with the original JRC ranking method (0.00410) and ranked JRCN1 to JRCN10. Thus it is proposed to consider JRCN as a new and improved version of JRC rankings.
Exploitation
S. Soltani-Mohammadi; A. Soltani; B. Sohrabian
Abstract
Due to the nature of the geological and mining activities, different input parameters in the grade estimation and mineral resource evaluation are always tainted with uncertainties. It is possible to investigate the uncertainties related to the measurements and parameters of the variogram model using ...
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Due to the nature of the geological and mining activities, different input parameters in the grade estimation and mineral resource evaluation are always tainted with uncertainties. It is possible to investigate the uncertainties related to the measurements and parameters of the variogram model using the fuzzy kriging method instead of the kriging method. The fuzzy kriging theory has already been the subject of relatively various research studies but the main weak point in such studies is that the results of the fuzzy estimations are not used in decision-making and planning. A very common, but key, tool of decision-making for mining engineers is the tonnage-average grade models. Under conditions where measurements or/and variogram model parameters are tainted with uncertainties, the tonnage-average grade model will be uncertain as well. Therefore, it is necessary to use the fuzzy tonnage-grade model instead of the crisp ones, and the next analysis steps and decision-makings are done accordingly. In this paper, the computational principles of the fuzzy tonnage-average grade curve and a case study regarding its usage are presented.
Exploitation
E. Bakhtavar; A. Jafarpour; S. Yousefi
Abstract
In order to catch up with reality, all the macro-decisions related to long-term mining production planning must be made simultaneously and under uncertain conditions of determinant parameters. By taking advantage of the chance-constrained programming, this paper presents a stochastic model to create ...
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In order to catch up with reality, all the macro-decisions related to long-term mining production planning must be made simultaneously and under uncertain conditions of determinant parameters. By taking advantage of the chance-constrained programming, this paper presents a stochastic model to create an optimal strategy for producing bimetallic deposit open-pit mines under certain and uncertain conditions. The uncertainties of grade, price per product, and capacities of the various stages in the process of production of the final product were considered. The results of solving the deterministic and stochastic models showed that the stochastic model had a greater compatibility and performance than the other ones.
A. Alipour; A. A. Khodaiari; A. Jafari; R. Tavakkoli-Moghaddam
Abstract
Open-Pit Production Scheduling (OPPS) problem focuses on determining a block sequencing and scheduling to maximize Net Present Value (NPV) of the venture under constraints. The scheduling model is critically sensitive to the economic value volatility of block, block weight, and operational capacity. ...
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Open-Pit Production Scheduling (OPPS) problem focuses on determining a block sequencing and scheduling to maximize Net Present Value (NPV) of the venture under constraints. The scheduling model is critically sensitive to the economic value volatility of block, block weight, and operational capacity. In order to deal with the OPPS uncertainties, various approaches can be recommended. Robust optimization is one of the most applicable methods in this area used in this study. Robust optimization based on the box counterpart formulation is applied to deal with the OPPS problem. To have a comparison between the solutions of the box counterpart optimization model and the deterministic model, a Two-Dimensional (2D) numerical study of a hypothetical open-pit mine is conducted followed by additional computations on the actual large-scale instances (Marvin orebody). This investigation shows that the different features of the robust planning under uncertainty can be scheduled. Also the price of robustness is obtained in different levels of conservatism.
