Browsing by Author "Chaves, Leonardo Soares"

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    Analysis of the impacts of slope angle variation on slope stability and NPV via two different final pit definition techniques.
    (2020) Chaves, Leonardo Soares; Carvalho, Luiz Alberto de; Souza, Felipe Ribeiro; Nader, Alizeibek Saleimen; Arroyo Ortiz, Carlos Enrique; Torres, Vidal Félix Navarro; Câmara, Taís Renata; Napa Garcia, Gian Franco; Valadão, George Eduardo Sales
    The traditionally and widely used Lerchs-Grossmann algorithm presents well-known limitations that newer propositions attempt to overcome. The direct block schedule (DBS) methodology, which has gained relevance with computational advances, obtains the final pit as a natural result of production sequencing, different from Lerchs-Grossmann-based algorithms. This process flow applies constraints in the final pit definition stage attempting to provide a more realistic result and to minimize risks. Slope instability is a common and inherent risk to open pit mining and may affect the project's net present value (NPV). A study of the impacts of slope angle variations on safety indexes and final pit NPV provides an auxiliary tool for the overall slope angle definition process. This article presents a case study in which the effects of variations of the overall slope angle on the safety factor (SF) and project NPV were analyzed. A total of 25 pits were generated by each studied final pit definition methodology, and each pit had the sections with the varied slope angles analyzed in the stability assessment, resulting in a total of 150 slopes analyzed. A comparison between the results obtained by the two different methodologies implemented in commercial software is presented. The results show no relationship between the NPV and the overall slope angle using the DBS methodology. An analysis of the results for each geotechnical sector obtained by the traditional methodology was conducted and may contribute to the trade-off analysis between the best slope angle to achieve a reasonable SF and the maximum NPV.
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    Classical and stochastic mine planning techniques, state of the art and trends.
    (2018) Torres, Vidal Félix Navarro; Nader, Beck; Arroyo Ortiz, Carlos Enrique; Souza, Felipe Ribeiro; Burgarelli, Hudson Rodrigues; Chaves, Leonardo Soares; Carvalho, Luiz Alberto; Câmara, Taís Renata; Fernandes, Eunírio Zanetti; Galery, Roberto
    Determination of the best possible ultimate pit for an open pit mine is a fundamental subject that has undergone a highly evolutionary process, reviewed in this study, since the correct choice carries substantial economic impact for the industry. The correct choice can be very beneficial for project analysis, whereas an incorrect choice has the potential to mask huge financial and economic future losses that could render a project unfeasible. The advent of computers in the 1960s allowed sophisticated analysis for the selection of the best ultimate pit determination, under specific modifying factors such as economic, social, environmental, and political, but only in deterministic situations, i.e., when the problem and variables for the ultimate pit determinations were considered deterministically and almost always based on average values. Techniques such as the Lerchs– Grossman algorithm and mixed-integer programming are among many standard tools now used by the mineral industry. Geological uncertainty and the associated risks as well as the need to consider the appropriate time to mine a block during a mine operation have a significant impact on the net present value of the resulting ultimate pits. Stochastic aspects embed a probabilistic component that varies in time and are now under intense investigation by researchers, who are creating algorithms that can be experimented with and tested in real mine situations. One can expect that once these algorithms demonstrate their efficiency and superior results, they will readily dominate the industry.
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    Direct block scheduling technology : analysis of avidity.
    (2018) Souza, Felipe Ribeiro; Burgarelli, Hudson Rodrigues; Nader, Alizeibek Saleimen; Arroyo Ortiz, Carlos Enrique; Chaves, Leonardo Soares; Carvalho, Luiz Alberto; Torres, Vidal Félix Navarro; Câmara, Taís Renata; Galery, Roberto
    This study is focused on Direct Block Scheduling testing (Direct Multi-Period Scheduling methodology) which schedules mine production considering the correct discount factor of each mining block, resulting in the final pit. Each block is analyzed individually in order to define the best target period. This methodology presents an improvement of the classical methodology derived from Lerchs-Grossmann’s initial proposition improved by Whittle. This paper presents the differences between these methodologies, specially focused on the algorithms’ avidity. Avidity is classically defined by the voracious search algorithms, whereupon some of the most famous greedy algorithms are Branch and Bound, Brutal Force and Randomized. Strategies based on heuristics can accentuate the voracity of the optimizer system. The applied algorithm use simulated annealing combined with Tabu Search. The most avid algorithm can select the most profitable blocks in early periods, leading to higher present value in the first periods of mine operation. The application of discount factors to blocks on the Lerchs-Grossmann’s final pit has an accentuated effect with time, and this effect may make blocks scheduled for the end of the mine life unfeasible, representing a trend to a decrease in reported reserves.
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    Direct stockpile scheduling : mathematical formulation.
    (2018) Souza, Felipe Ribeiro; Chaves, Leonardo Soares; Burgarelli, Hudson Rodrigues; Nader, Alizeibek Saleimen; Arroyo Ortiz, Carlos Enrique; Alberto, Luiz
    In a mining context, production scheduling’s main objective is to determine the best mining sequence of blocks to achieve the largest net present value and to maximize ore reserve exploitation. Stockpiling and blending procedures may represent very helpful alternatives for mine planning to ensure the ore quality and amount required by the processing plant. In order to satisfy industrial requirements of grades and tones, reducing stockpile fluctuations may represent a very important tool especially for medium and short term mine planning. Classical linear programing has been widely used to model blending problems at the mining industry, however this formulation allows only one objective formulation. The current work describes a system based on goal programing able to reach blending constraints desired by short/medium term planning. The proposed formulation achieves the best schedule scenario, ensuring cost constrains are respected. Hence, this study aims to provide support for both short and long term mine planning.