21 research outputs found

    Schematic diagram of boundary adjustment section of open pit mines.

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    (a)Open pit limit adjustment of the near level coal seam. (b)Adjustment of open pit limit in inclined coal seam.</p

    Sliding window method to determine optimal mining boundary.

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    Sliding window method to determine optimal mining boundary.</p

    Comparison of final state adjustment of open pit mines and coal price volatility.

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    (a) Fluctuation trend of coal price time series. (b) The trend of boundary change in the corresponding period of open-pit mine.</p

    Schematic diagram of the block model section of a small open-pit mine.

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    Schematic diagram of the block model section of a small open-pit mine.</p

    Principal economic indicators in the production chain.

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    Principal economic indicators in the production chain.</p

    Actual and predetermined coal prices were compared during the adjustment period.

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    Actual and predetermined coal prices were compared during the adjustment period.</p

    The flow chart of open-pit mine optimal boundary design.

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    The flow chart of open-pit mine optimal boundary design.</p

    The ACF and PACF diagrams of coal price time series.

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    (a) autocorrelation graphs of first-order difference sequences. (b) partial autocorrelation graphs of first-order difference sequences.</p

    Coal price ARIMA model prediction results.

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    The delineation of the open-pit mining boundary, particularly in the context of medium to long-term planning, forms the foundation of mining design. However, due to the non-linear and dynamic nature of the economic and technical parameters influencing boundary delineation, determining the optimal mining boundary can be exceedingly challenging. Currently, most boundary optimization methods assume that block parameters remain fixed, which results in enterprises assuming a certain level of risk when facing changes in internal and external conditions. In this regard, this paper introduces the concept of "achievement degree" to reflect the risk associated with the results of boundary design. Using coal prices as an example, this article applies the predicted coal price curve to boundary optimization adjustments by specifying the "achievement degree" requirements for various time periods, thereby facilitating risk-controlled and economically optimal boundary decisions. Taking the illustrative case of an idealized small-scale inclined coal seam open-pit mine, adjustments to the boundary closely track variations in coal prices, further enhancing returns. The results demonstrate that the method proposed in this paper can increase overall revenue by approximately 51.15% within the forecast period, while effectively managing risks.</div

    Comparison of raw coal pit price and thermal coal price trend.

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    Comparison of raw coal pit price and thermal coal price trend.</p
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